No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
BIG DATA ANALYTICS FOR DEVELOPING SECURE INTERNET OF EVERYTHING
Abstract
Storage and processing of information is the major application of big data analytics. Internet of Everything (IoE) is the smart connection between people, data, things and processes. This paper studies the available frameworks used for developing secure Internet of Everything with big data analytics. Big data is a collection of data generated from the sensors embedded in the surrounding physical objects. This information can be used for analysis of the surroundings and development based on the inference. Internet of Everything uses this data for automation of the electronic equipment in the surrounding environment. However, with the increasing level of automation, the vulnerability to attack also increases. This paper presents a detailed analysis of big data analytics that is used for developing a secure internet of everything.
... As mentioned previously, IoT connects a platform of embedded devices through the internet to ensure data collection [55]. It has changed the business models of many companies and consumer engagement with these companies [64]. ...
... Significant improvements in IoT and comprehensive communication provide IoE communication [70]. IoE affects people's lives, industrial processes, businesses, and real-time information collected from various sensors and applied to a people-centric automated process [55]. In the IoE framework, people play a pivotal role in exchanging data between network nodes and creating an area of many smart sensors. ...
... Moreover, these developments have granted considerable opportunities for IoE growth in health care, digital devices, home automation, energy conservation, security, information and communication exchanges, and environmental monitoring [27,32]. Therefore, IoE helps us achieve socioeconomic goals, environmental sustainability, and public policy goals [40,55,81]. ...
Preserving customers’ expectations and understanding factors affecting their purchasing decisions are crucial in designing effective marketing and advertising strategies. However, constantly and swiftly changing the customers’ interests and consumption behaviors make it inevitable to utilize sophisticated tools and approaches based on advanced technologies. Among them, by measuring the customers’ physiological and neural signals, studying the customers’ cognitive and affective responses to marketing stimuli, neuromarketing provides deep insight into the customers’ motivations, preferences, and decisions. Recently, the internet of everything (IoE) has brought many new opportunities to the industry and has attracted the attention of many researchers in recent years. The main objective of this paper is to address how the IoE would empower neuromarketing techniques. Hence, an in-depth understanding of current research issues as well as emerging trends would help meet this goal. In this paper, a comprehensive review has been done by reviewing numerous journal and conference papers from various academic databases (sciencedirect.com, IEEE Xplore, Springer, Elsevier, Wiley, ACM digital library) based on applying various filtrations on specific keywords to identify and categorize the IoE devices in the neuromarketing field. In particular, we discussed the importance and the applications of IoE gadgets and devices, especially wearable medical technologies in eight neuromarketing techniques. Finally, we described critical existing challenges and limitations in neuromarketing and IoE gadgets that researchers have dealt with in this field of research.
... As mentioned previously, the developments of sensor networks and computing capabilities have turn IoT into the future of information technology. IoT connects a platform of embedded devices over the Internet to ensure data collection (Karthiban & Raj, 2019), and it has changed the world as well as the business models of many companies and consumer engagement with these companies and other stakeholders (Langley et al., 2020). IoT is a view of a large network of unique smart things with different devices such as sensors connected at any time and any place, to work together to meet customer demand (Kang, Kim, & Choo, 2017). ...
... Liu, Dai, Wang, Shukla, & Imran, 2020). IoE affects people's lives, industrial processes, businesses, as well as real-time information that is not only collected from various sensors but also is applied to a people-centric automated process (Karthiban & Raj, 2019). People's involvement in exchanging of data between network nodes brings about the advent of the IoE, which creates an area of a large number of smart sensors that can change the information and can obtain information (AlSuwaidan, 2019). ...
... These developments have granted considerable opportunities for IoE growth in healthcare, digital devices, home automation, energy conservation, security, information and communication exchanges, and environmental monitoring (Fan, Liu, Hu, Zhong, & Lu, 2019;Galitsky & Parnis, 2019). Therefore, IoE helps us to achieve socio-economic goals, environmental sustainability, and public policy goals (Karthiban & Raj, 2019). ...
Preserving customers' expectations and understanding factors affecting their purchasing decisions would significantly affect designing effective marketing and advertising strategies. However, constantly and swiftly changing the customers' interests and consumption behaviors, make it inevitable to utilize the sophisticated tools and approaches based on advanced technologies. Among them, neuromarketing by measuring the customers' physiological and neural signals, studying the consumers' cognitive, and affective responses to marketing stimulus, provides deep insight into the customers' motivations, preferences, and decisions. Recently, the Internet of Everything (IoE) has brought many new opportunities to the industry and has attracted the attention of many researchers in recent years. The main objective of this paper is to address how the Internet of Everything (IoE) would empower neuromarketing techniques. In particular, applications of IoE gadgets and devices in eleven groups of neuromarketing techniques are discussed to present numerous solutions that would help meet this goal. Moreover, we present an in-depth understanding of current research issues as well as emerging trends.
... It offers a secure method for sharing data amongst a group of cloud-based users. In addition, each user is assigned a unique secret key for executing file operations [8]. It lets cloud users into group to share data, but only if they agree to keep their identities secret. ...
During cloud transactions, providing identity privacy, multiple owner access as well as dynamic data sharing for multiple users without any intervention with number of revoked cloud users is complicated mission. In this paper, secure data sharing scheme for dynamic cloud users using Linear Feedback Shift Register (LFSR) is proposed where any user of a cloud can utilize the cloud services like data sharing and data storing. Encryption's computational and storage costs are not affected by how many people have their access restricted. This algorithm will correlate the LFSR sequences by selecting random numbers with the output sequences generated by the ciphers. If the generated correlation value present below 0-1 then it proves that the channel is secure to communicate then the group user will be able to communicate with the cloud. If attack occurs then change the public key values. Proofs and cloudsim are used to conduct security analyses that will provide a cloud efficiency report.
... It offers a secure method for sharing data amongst a group of cloud-based users. In addition, each user is assigned a unique secret key for executing file operations [8]. It lets cloud users into group to share data, but only if they agree to keep their identities secret. ...
... It is essential to combine big data analytics with IoE as IoE by itself cannot deal with the complete interaction between its subsystems and extract meaning from the data. IoE platforms are scalable, easy to use, offer flexibility for deployment, clear system architecture and has user interface that are developer-friendly (Raj, 2019). We have been seeing Internet-of-Things (IoT) being deployed to ensure that smart system and smart system of systems (like smart cities) are possible with the use of right variety of connected sensors, and data analytics. ...
With the evolution of internet various things related to the internet have rapidly increased which can relatively be termed as the Internet of Every things (IoE). A lot of success has been recorded especially in daily life application and business sphere. Published studies have signified the need for further research on cloud based security for the Internet of Everything (IoE). The vision that everything will one day be connected to the internet will surely come with some security problems. Some of these envision challenges have been studied broadly in literatures. However, there is need to critically review some of this information to ascertain security vulnerabilities as a result of complexity in systems. In this study, we provide current information (2018-2021) on security risks for internet of everything; necessity of cloud based Security, and the expected benefits of cloud based security. We also reviewed current and future technology trend in cloud based security as it regards to Internet of Everything. This paper provides insights into some of the important challenges and possible solutions of cloud based security for Internet of everything (IoE).
... • Technology for privacy and security and storage issue (Das et al., 2018;Karthiban & Raj, 2019) • Awareness programme (Gouri & Uddin, 2019) • Research and development investment • Cloud-based or web-based electronic data interchange systems for data integration issue (Johri et al., 2017) in India is found due to bribery and inefficiency. The telecom company, Reliance Jio, revealed more than 110 million users' Aadhaar information (MacIntyre et al., 2021). ...
... But the simulation, it can be demonstrated that GPSO based learning techniques offer reliable, robust, and scalable solutions. The authors in [12] analyzed the existing structures utilized to develop secure IoE with big data analytics. Big data is a group of data created in the sensor embedding from nearby physical objects. ...
Recent developments of semiconductor and communication technologies have resulted in the interconnection of numerous devices in offering seamless communication and services, which is termed as Internet of Everything (IoE). It is a subset of Internet of Things (IoT) which finds helpful in several applications namely smart city, smart home, precise agriculture, healthcare, logistics, etc. Despite the benefits of IoE, it is limited to processing and storage abilities, resulting in the degradation of device safety, privacy, and efficiency. Security and privacy become major concerns in the transmission of multimedia data over the IoE network. Encryption and image steganography is considered effective solutions to accomplish secure data transmission in the IoE environment. For resolving the limitations of the existing works, this article proposes an optimal multikey homomorphic encryption with steganography approach for multimedia security (OMKHES-MS) technique in the IoE environment. Primarily, singular value decomposition (SVD) model is applied for the separation of cover images into RGB elements. Besides, optimum pixel selection process is carried out using coyote optimization algorithm (COA). At the same time, the encryption of secret images is performed using poor and rich optimization (PRO) with multikey homomorphic encryption (MKHE) technique. Finally, the cipher image is embedded into the chosen pixel values of the cover image to generate stego image. For assessing the better outcomes of the OMKHES-MS model, a wide range of experiments were carried out. The extensive comparative analysis reported the supremacy of the proposed model over the rennet approaches interms of different measures.
... This indicates that the data set developed cannot be used when topology changes. Hence the predictions that are made using the historical data and its subsequent trained or developed model will not result in an accurate value as there is a shift in distribution of data leading to two unrelated old findings that will not have any impact on the new findings [12]. ...
In order to increase the utilization of artificial intelligence in smart grids, it is necessary to have an accurate state estimation. This criterion is an essential aspect, along with other functionalities for successful control and monitoring. As the internet and utility network form an increasing interconnectivity, it leaves the state estimators in a state of vulnerability to various attacks like bad data detection and false data injection. Though there are many research-works done on detectors for false data detection, depending on the contingencies, the counter measure will also vary. A sudden change physically will have a high impact on the available data, resulting in incorrect classification of the future instances. As a means of addressing this issue, we have analyzed the differences between data manipulation change and physical grid change for better understanding. Focusing on distribution change, we used outage and have introduced analysis of historical data. The goal is to determine the important aspects thereby identifying the scope. We have also used statistical hypothesis and dimensionality reduction for testing purpose. We have used IEEE 14 bus system for evaluation based on the scenario of attack: under concept drift and without concept drift. The result shows a more accurate output when compared with the other previously existing methodologies using concept drift.
... In this digital era, digital images are shared between entities is at an all-time high. Thus the combination of medical images and internet gives the tremendous improvement in medical field, not only for diagnosing the disease but also for encouraging the telemedicine and e-health applications [1]. Remote medical consulting requires the communication of medical image likes MRI, CT and X-ray images through online. ...
... The approach failed to effectively optimize query processing with big data. A distributed Distance Join Queries (DJQ) algorithm was introduced in [6] for processing the queries with big spatial data. The execution time was not minimized using the DJQ algorithm. ...
With large volumes of data being generated in recent years and the inception of big data analytics on social media necessitates accurate user query processing with minimum time complexity. Several research works have been conducted in this area, to address accuracy and time complexity involved in query processing, in this work, Wald Adaptive Prefetched Boosting Classification based Czekanowski Similarity MapReduce (WAPBC–CSMR) technique is introduced. The WAPBC–CSMR technique uses the big dataset for processing large number of user queries. First, a technique called, Wald Adaptive Prefetched Boosting is employed with the objective of classifying the big dataset into different classes. To reduce the time involved in classification, in this paper a classifier called Gaussian distributive Rocchio is used that achieves significant classification in minimum time. With the classified results, a Likelihood Radio Test is applied to integrate the weak learner results into strong classification results. Then the classified and refined data are stored on the prefetcher cache. Upon reception of multi-dimensional user queries by the prefetch manager, the queries are now split into multiple keywords and are fed into the map phase, where mapping function is performed using Czekanowski Similarity Index with the objective of identifying the repeated jobs with maximum query processing accuracy. Followed by which the relevant data are retrieved from the prefetcher cache and repeated user query task is removed in the reduce phase via statistical function, therefore contributing to minimum time. Result analysis of WAPBC–CSMR is performed with big dataset using different metrics such as query processing accuracy, error rate and processing time for varied number of user queries. The result shows that WAPBC–CSMR technique enhances query processing accuracy and lessens the time as well as the error rate than the conventional methods.
... Nowadays, a massive amount of data is generated, stored, and exchanged through the internet. Therefore, the security of data, the internet, and communication networks is becoming of ext reme importance [11], [12]. Cryptography and steganography provide a high level of security through data encoding and information hiding Image steganography have become well known in which data are embedded and masked behind an image using various digital cover objects and algorithms. ...
... The symmetric encryption algorithm is a process of encrypting and decrypting data or information by using the same key [4][5][6]. Nowadays the most used Advanced Encryption Standard [AES] algorithm is issued by the National Institute of Standard and Technology (NIST) in 2001. It is developed by two Belgian cryptographers, Vincent Rijmen and Joan Daemen. ...
In this digital era, people are moving fast towards cloud and big data; hence, it becomes very important for the organization to encrypt the data. To enable secure data communication, the user needs different encryption algorithms. The encryption algorithms are RC4, RC5, SHA, DES,3DES, AES, etc. The mostly used algorithm is the Advanced Encryption Standard [AES]. This utilizes symmetrical keys, where the keys are shared between transmitter and receiver, i.e., the key will be easily hijacked by attackers. In this paper, we proposed the system working on three phases. Firstly, the custom replacement for input values like one character replaced by another character. Secondly, encrypt the data by using AES dynamic keys. To generate a key using 16 bytes, data frame is sending sequentially. Based on the order of this sequence, the key is changed dynamically with encrypted data and finally add padding bits to the ciphertext to provide more security to data or information.
... The analytical results indicates that the accuracy of the proposed model performance than the other two classifiers. A secure internet of everything [4] was designed to safer the big data from the attack vulnerability. The general IoT systems are equipped with more number of sensors based on the application. ...
Water is one of the basic resource need for every human in the world. The improper management of water storage system can lead a human life to any extent. As a result of technology development, the proposed model is developed to manage the water storage systems like dam and lake through remotely placed sensor signals. The sensors which are placed in the storage places gives the strength and storage capacity of the dam and lakes. Similarly the sensors which are placed at the sender dam or lake are used to predict the incoming water level to the receiver lake. This improves the prediction rate of flood in the river paths and this prediction allows the incoming dam to send off some waters outside to allocate some space for incoming waters. The data which are generated by the connected dams are stored in a cloud space for analyzing the water flow management. The sensors connected in a lake or dam is connected with IoT platform to avoid wire connections. Hence this model avoids sudden floods during rainy conditions and it ensures the physical strength of the lake and dam by continuous monitoring process.
... Real-time data processing requirements are met by big data analytics. The power consumption of processing this voluminous data can be reduced by implementing efficient protocols for data communication [13][14][15][16][17][18][19][20][21][22][23][24][25]. ...
Smart cities with smart infrastructure is a rapidly flourishing field of research in the modern days. Open areas, agricultural land, forests, office, homes and several areas can have occurrences of fire accidents leading to loss of significant resources. Unmanned Aerial Vehicle (UAV) and wireless sensor network technologies are used fir detection of fire at an early stage in this paper. This helps in avoiding serious fire accidents. The environmental parameters are monitored using the sensor architecture. The sensors uses IoT based applications for processing the gathered environmental data. Cloud computing, IoT sensors, wireless technology and UAVs are combined for the purpose of fire detection in this paper. In order to improve the accuracy of the system, integration of image processing schemes is done in this system. The rules are formulated such that the true detection rate is improved. The existing state-of-the-art models are compared with the proposed system. The simulation results show that the rate of fire detection of the proposed system is improved for up to 98% when compared to the traditional models.
... The WSN node energy consumption issue is addressed in this paper using a novel routing algorithm that uses extended smart ant colony optimization algorithm. Here, the next hop of the node is selected within the network area by dividing the best area on the basis of delay and energy [13]. The ant's optimal position is proposed for ensuring the global optimal solution. ...
The Internet of Things networks comprising wireless sensors and controllers or IoT gateways offers extremely high functionalities. However, not much attention is paid towards energy optimization of these nodes and enabling lossless networks. The wireless sensor networks and its applications has industrialized and scaled up gradually with the development of artificial intelligence and popularization of machine learning. The uneven network node energy consumption and local optimum is reached by the algorithm protocol due to the high energy consumption issues relating to the routing strategy. The smart ant colony optimization algorithm is used for obtaining an energy balanced routing at required regions. A neighbor selection strategy is proposed by combining the wireless sensor network nodes and the energy factors based on the smart ant colony optimization algorithm. The termination conditions for the algorithm as well as adaptive perturbation strategy are established for improving the convergence speed as well as ant searchability. This enables obtaining the find the global optimal solution. The performance, network life cycle, energy distribution, node equilibrium, network delay and network energy consumption are improved using the proposed routing planning methodology. There has been around 10% energy saving compared to the existing state-of-the-art algorithms.
... Gradient descent approach and mixed kernel function encapsulation schemes are applied for improving the SVM by incorporating the dropout functionality for revamping the performance of RBM. We design a routing scheme for multi-objective flow based SDN and delivery of end-to-end social media traffic [15]. Energy utilization and consumption, bandwidth, latency and such trade-offs exists on implementation of this scheme. ...
Social multimedia traffic is growing exponentially with the increased usage and continuous development of services and applications based on multimedia. Quality of Service (QoS), Quality of Information (QoI), scalability, reliability and such factors that are essential for social multimedia networks are realized by secure data transmission. For delivering actionable and timely insights in order to meet the growing demands of the user, multimedia analytics is performed by means of a trust-based paradigm. Efficient management and control of the network is facilitated by limiting certain capabilities such as energy-aware networking and runtime security in Software Defined Networks. In social multimedia context, suspicious flow detection is performed by a hybrid deep learning based anomaly detection scheme in order to enhance the SDN reliability. The entire process is divided into two modules namely – Abnormal activities detection using support vector machine based on Gradient descent and improved restricted Boltzmann machine which facilitates the anomaly detection module, and satisfying the strict requirements of QoS like low latency and high bandwidth in SDN using end-to-end data delivery module. In social multimedia, data delivery and anomaly detection services are essential in order to improve the efficiency and effectiveness of the system. For this purpose, we use benchmark datasets as well as real time evaluation to experimentally evaluate the proposed scheme. Detection of malicious events like confidential data collection, profile cloning and identity theft are performed to analyze the performance of the system using CMU-based insider threat dataset for large scale analysis.
... II. RELATED WORK In recent times, the field of technology has attracted so much attention from people around the world. With technology being multifaceted, scientists and researchers have harnessed the opportunities offered by IoT in the field of the healthcare industry, as well as the practical challenges it faced [5] [15]. Over the years, the application of internet-based technologies in healthcare rehabilitation has become more prominent, most especially after the introduction of new concepts, such as Smart City and Smart Planet [4] [16]. ...
... Applications of IoT has entered into all areas of our day to day activity. It is also used in smart grid, traffic control and planning, automation, eleaning, remote monitoring, fossil fuel mining and various other industries [13].Agriculture is an application of IoT that requires much attention. By using IoT in agriculture field, farmers can increase the production of the crop, reduce the decay of crops and reduce the cost of fertilizers and other resources by using it time to time. ...
Centered on its inherent data sharing and low latency features, cloud infrastructure is considered as an effective alternative to conventional information technology. Cloud service providers (CS Ps) like Amazon, are capable of providing cloud users with various services by integrating the powerful data centers. Users may utilize high-quality software to move their local data processing systems to cloud storage and save considerable investments in their local infrastructures. Annotation techniques by utilizing the pairs of meaning attributes are usuall y more descriptive, as they provide more details than the untyped methods. A new solution to use more concise queries with such annotations is the "pay-as-you-go" querying technique in data spaces.
This chapter explores Big Data’s huge volume, velocity, and diversity add to its complexity. Big data is used to make informed decisions with real-time dynamic updates for any business. Hadoop is an Apache open-source software framework for storing data and running applications on commodity hardware clusters, featuring HDFS and MapReduce capabilities. It maintains the dataflow, with distributed parallel processing in real-time. This chapter contains the following sections:Introduction to Big DataHadoop Architecture: HDFS and MapReduceHadoop ecosystem: YARN, Pig, Hive, HBase, Cassandra, Sqoop and Flume, Apache SparkHadoop 3.0 UpgradationApplications & Future Introduction to Big Data Hadoop Architecture: HDFS and MapReduce Hadoop ecosystem: YARN, Pig, Hive, HBase, Cassandra, Sqoop and Flume, Apache Spark Hadoop 3.0 Upgradation Applications & Future A robust and gracious file system like Hadoop is required to learn, reason, respond, and interact with huge data in hand which is expanding exponentially. The need of the hour is to address new areas like health, contactless personal assistants, and single window systems. Hadoop has become almost synonymous with Big Data, leading to social analytics and Algorithmic Approach to Business in the future.
Internet of Everything (IoE) is a revolutionary information technology discovery impacting the lives of human beings. If we look at how IoE captures the idea of how a human being communicates with an object, including those used in daily life, we’ll see that every device on the IoE uses sensors to detect and record information and forward it to an actuator. For instance, as in today’s market, an electricity gadget (electricity counter) connects to the Wi-Fi and calculates how much electricity has been consumed at home or a corporation. Thus, in the same way, through the IoE, every object has a unique IP that is recognized by IPv6 that offers a large IP address pool and serves as the logical connection between people and people and objects by converting data into different formats that aid in making the right decision. The existing method of exchanging data via the Internet as plain texts or unprotected data may lead to security issues through malicious attacks. With this apparatus in hand, the introduction of blockchain technology with distributed ledgers into the IoE has made it a decentralized, distributed database as opposed to the single database of the traditional method. In IoE, each node has a database to store all copies of the shared information. To this, the blockchain technology adds more advantages, like the security of the IoE data, blockchain ensures cost transparency and true tractability, provides encryption features to assure data confidentiality, integrity, and availability and strengthens the protection of data through the Internet. Thus, the blockchain with distributed ledgers has more security features than centralized management. A blockchain uses consensus protocols between the partner’s networks whereby the device has the ability to participate, is conscious about improving the security of the people and their sensitive data, and protects information from malware like man-in-the-middle, denial of services, network phishing attacks, hackers, and SQL injection threats.
The analysis of trafficPaudyal, Amit load and its impact on road bridges has become an important method to ensure the longevity of the bridges.Bhattarai, Nirdesh Heavy and rapid moving vehicles cause huge strain and deflection of bridges.Bhandari, Shiva The study of the dynamic response of bridges and their trend over a period allows the continuous assessment of their deteriorating conditions.Rai, Nabin Visual inspections and surveys only give an outlook on the condition of the exterior of the bridge.Rimal, Ram Prasad A network of wireless sensors measuring dynamic characteristics such as strain, deflection, and vibration can assist in understanding the overall bridge structure conditions.Adhikari, Nanda Bikram In our study, an array of high-precision inertial sensors has been deployed on both the old and the new sections of the Bagmati bridge. Huge amounts of data are extracted from each sensor and then preprocessed to remove corrupt data, outliers, and obtain clean datasets. This process is followed by visualization of the preprocessed data to derive initial observations. Statistical analysis is carried out to study the nature of obtained data, and machine learning algorithms have been applied to predict the future trends.
The prime aspect in data handling is the invulnerability of Data, therefore, Encryption is the most conventionally used technique for data security. for instance, Data Encryption Standard (DES), Rivest–Shamir-Adleman (RSA), Advanced Encryption Standard (AES) to attain it moreover, with the exponentially growing of data over time leads to the concept of Big Data which involves not only the structured but also unstructured data such as images, audio, video, and other data formats. Encrypting such varied and immense data is a challenge in itself. In this paper, we delve into some of the major algorithms and techniques for efficient encryption and decryption of the data. Moreover, we have also done a comparative analysis of the different encryption and decryption techniques to predict the use of these techniques based on application requirements. The main objective of this work is to convey a better focus on data encryption approaches and to bring out the major issues and application areas where these encryption algorithms best suit.
In recent days, the development in the Internet takes a significant part in all types of activities that have been driven specialists to consider research frameworks to help the clients and applications in getting the directions by conveying nature of administration in systems. Some sorts of strategies are appropriate for giving security in correspondence to seized conditions, for example, portable registering, internet business, media transmission, and system administration. In such cases, service providers are focusing more on enriching the service access to end users. Since, there is an intermediate data theft or attack that was occurred during the broadcast process. Hence, an overview on different detection schemes are considered for successful determination and arrangement for attack recognition with various neural systems and some swarm computations has been proposed. The proposed strategies have been valuable for adequately identifying the system interruptions with the objective to give security to the Internet and to upgrade the nature of administration.
Malicious URLs play a very important role in today’s critical scam and attacks. They are harmful to every aspect of the usage of computers. Identification and detection of these malicious URL are very crucial. Malignant codes are synchronized with malicious software by invaders or hackers. Malicious content can be like Trojan horses, worms, backdoors, etc.; detection of these URLs is done previously by the usage of blacklists and whitelists. Blacklist itself cannot be sufficient to check the malicious URLs because they suffer from a shortage in the capacity in terms of newly created malicious URLs. These conventional approaches shortfalls by effectively dealing with evolving technologies and web searching mechanisms. In recent years, systems have been explored and evolved with the increasing research attention on enhancing the ability to detect malicious URLs. In this research paper, an innovative classification method was proposed to solve the difficulties encountered in malicious URL detection by using the existing mechanisms. The proposed classification model is based on high-performance machine learning methods which not only takes the syntactic essence of the URL into consideration but also the semantic and lexical meaning of these dynamically changing URLs. It is expected that the proposed approach will overcome the drawbacks of the existing techniques. A comparative analysis of Logistic regression, Support Vector Machine, and Naïve Bayes classification has also been performed. The tests of computer simulation have developed SVM with greater accuracy than logistic regression and Naive Bayes. Support Vector Machine has been obtained with an accuracy of 85.35%.
In the modern world, software plays an integral role, following an effective methodology while developing these software have become crucial to accomplish the project goal. Agile approach is a methodology which have been introduced as an effective approach for developing software to increase productivity and efficacy of software development process compare to traditional methodologies. The rapid deployment of solutions, early and continuous delivery of valuable product to the customers, resource utilization, rapid issue detection, customer focus, effective collaboration and communication, adapting changes and flexibility are the key principles of Agile. Meeting the deliverables of the project without compromising its scope, quality and timeline within a limited budget is a key to success. Use of effective project management methodology and identification of critical success factors to achieve project success is essential to understand for any organization whether it is software or non-software.
IoT is being greatly used for designing a proper waste management system i.e. collection and disposal techniques. In the smart cities concept, sustaining water, energy and management of waste which includes some basic restrictions on the use of greenhouse gases in the areas concerned. This paper reviews various waste collection and disposal techniques such as smart bins, recycling and open sky incineration, secured landfilling, composting, incineration & waste to energy (WTE), lagooning etc. as well as the planning and operations required with their challenges. There are various changes taking place in the environment causing global warming due to the human activities. To maintain the environmental sustainability, there has to be proper planning, management and operations to be carried out. Fortunately, IoT has the answer to assist the utilization method at each stage of the waste management.
To reform and enhance healthcare services, the use of information technology is increasing in an unprecedented manner. This technological advancement results in generating substantial medical data from various Healthcare related things. This Medical Big data has a maximum prospective to upgrade patients’ treatment and follow up. We anticipate to flare-up some preventable infections, and we can significantly reduce the Healthcare delivery cost, by using the Medical Big data. One specific pattern observed in the medical services industry is serial shifting data to the cloud. By shifting data to the cloud, the accessibility of the patient’s medical history in real-time is possible and it can reduce costs. Though we enjoy multiple advantages of cloud computing for Medical Big data, we face specific security issues of our data stored in the cloud. In this paper, a brief analysis on various approaches used to protect the healthcare related information stored in the cloud and further they are secured using cryptographic techniques.
Information available in the Infrared and visible NOAA (National Oceanic Atmosphere Administration) satellite imagery is in the form of brightness temperature and albedo. Three Techniques are constructed to retrieve the convective cloud portion using Singular Value Decomposition (SVD), 2D-DCT (Discrete Cosine Transform) and fuzzy logic methods provided within MATLAB®, and compared the accuracy of these methods. The results delineates that there is tradeoff between accuracy of effective cloud amount and execution time. Though the fuzzy logic method takes the time to train the data but gives the accurate detection and classification of clouds
In recent years, Big Data Analytics is used for the specification of a large amount of data to uncover or extract the information such as the hidden data. This allows the user or developer to utilize the large chunk or data in order to extract the correlations and patterns which may be present inside the large unstructured chunk of data. The term, Big Data was initially coined in the mid-1990s due to the seemingly increased volumes of data which were often stored in hardware devices, up until we obtained a permanent solution to the excess amount of storage space we know today as Cloud Computing. Cloud Computing, known as the phenomenon which involves mass storage of data and information among a certain entity which hosts no hardware, i.e. stored in an imaginary circumstance termed as ‘cloud’, has deemed beneficial to the Technology surrounding us and enabled an immense advantage when it comes to artificial storage. Over the years, there have been various technological improvements and studies surrounding this phenomenon in which this Technology is deemed to be present among almost every hardware component in the near future. In this paper we are going to view some of the advancements and achievements this technology has brought in our rapidly growing technological world.
The Internet of things is the basic paradigm with the cluster of techniques that ensure innovations in the service rendered in various applications. It aims to develop a seamless connection between the tangible objects around and the information network in turn to provide a well-structured servicing to its users. Though the IOT service seems to be promising, the risks still prevail in the form of privacy and the security in user acceptance in utilizing the internet of things services, and its application. This makes the trust management very important for the internet of things. So the paper puts forth the distributed block chain involved trust system to manage the conveyance infrastructures of the internet of things paradigm. The evaluation of the proposed model evinces the enhanced security provided for the nodes of the IOT as well as its information exchange.
The Internet of Everything (IoE), which aims to realize information exchange and communications for anything with the Internet, has revolutionized our modern world. Serving as the driving force for devices in the IoE network, power supply systems play a fundamental role in the development of the IoE. However, due to the complexity, multifunctionality and wide‐scale deployment of diverse applications, power supply systems face great challenges, including distribution, connection, charging technologies, and management. In this review, some challenges and advances in the development of both power supply systems and their units are presented. In the overall system‐level field, establishing sustainable and maintenance‐free power supply systems through wireless connections, efficient power management and integrated energy harvesting and storage systems is highlighted. Additionally, the main performance metrics of power supply units are discussed, including energy density, service life, and self‐power ability. In addition, some directions of power quality assessment for both the system and unit levels of power supply systems are presented, aiming to provide insight into the future development of high‐performance power supply systems for the IoE. This review highlights critical challenges and advances in the development of both power supply systems and their units for the Internet of Everything.
This paper gives insights into the most important existing problems of security and privacy of the Cloud Computing (CC), Internet of Things (IoT) and Cloud of Things (CoT) concepts especially confidentiality issue. With the evolution of ubiquitous computing, everything is connected everywhere, therefore these concepts have been widely studied in the literature. However, intrusions and vulnerabilities will be more recurrent due to the systems complexity and the difficulty to control each access attempt. To tackle this issue, researchers have been focused on various approaches enforcing security and privacy. In the present paper, risk factors and solutions regarding these technologies are reviewed then current and future trends are discussed.
The communication infrastructure among various interconnected devices has revolutionized the process of collecting and sharing information. This evolutionary paradigm of collecting, storing and analyzing data streams is called the Internet of Everything (IoE). The information exchange through IoE is fast and accurate but leaves security issues. The emergence of IoE has seen a drift from a single novel technology to several technological developments. Managing various technologies under one infrastructure is complex especially when a network is openly allowing nodes to access it. Access transition of infrastructures from closed networked environments to the public internets has raised security issues. The consistent growth in IoE technology is recognized as a bridge between physical, virtual and cross-cultural worlds. Modern enterprises are becoming reliant on interconnected wireless intelligent devices and this has put billions of user’s data in risk. The interference and intrusion in any infrastructure have opened the door of public safety concerns because this interception could compromise the user’s personal data as well as personal privacy. This research aims to adopt a holistic approach to devising a secure IoE architecture for cross-culture communication organizations, with attention paid to the various technological wearable devices, their security policies, communication protocols, data format and data encryption features to avoid the data exploitation. A systems methodology will be adopted with a view to developing a secure IoE model which provides for a generic implementation after analyzing the critical security features to minimize the risk of data exploitations. This would combine the ability of IoE to connect, communicate, and remotely manage an incalculable number of networked, automated devices with the security properties of authentication, availability, integrity and confidentiality on a configurable basis. This will help clarify issues currently present and narrow down security threats planning considerably.
This paper promotes the concept of smart and connected communities SCC, which is evolving from the concept of smart cities. SCC are envisioned to address synergistically the needs of remembering the past (preservation and revitalization), the needs of living in the present (livability), and the needs of planning for the future (attainability). Therefore, the vision of SCC is to improve livability, preservation, revitalization, and attainability of a community. The goal of building SCC for a community is to live in the present, plan for the future, and remember the past. We argue that Internet of Things (IoT) has the potential to provide a ubiquitous network of connected devices and smart sensors for SCC, and big data analytics has the potential to enable the move from IoT to real-time control desired for SCC. We highlight mobile crowdsensing and cyber-physical cloud computing as two most important IoT technologies in promoting SCC. As a case study, we present TreSight, which integrates IoT and big data analytics for smart tourism and sustainable cultural heritage in the city of Trento, Italy.
Big data storage and processing are considered as one of the main applications for cloud computing systems. Furthermore, the development of the Internet of Things (IoT) paradigm has advanced the research on Machine to Machine (M2M) communications and enabled novel tele-monitoring architectures for E-Health applications. However, there is a need for converging current decentralized cloud systems, general software for processing big data and IoT systems. The purpose of this paper is to analyze existing components and methods of securely integrating big data processing with cloud M2M systems based on Remote Telemetry Units (RTUs) and to propose a converged E-Health architecture built on Exalead CloudView, a search based application. Finally, we discuss the main findings of the proposed implementation and future directions.
Healthcare industry has been a significant area for innovative application of various technologies over decades. Being an area of social relevance governmental spending on healthcare have always been on the rise over the years. Event Processing (CEP) has been in use for many years for situational awareness and response generation. Computing technologies have played an important role in improvising several aspects of healthcare. Recently emergent technology paradigms of Big Data, Internet of Things (IoT) and Complex Event Processing (CEP) have the potential not only to deal with pain areas of healthcare domain but also to redefine healthcare offerings. This paper aims to lay the groundwork for a healthcare system which builds upon integration of Big Data, CEP and IoT.
The number of devices connected to the Internet of Things (IoT) by the year 2020 may be as high as 75 billion. Long before that, big data analytics will be needed to make use of the data generated by the Internet of Things. While the technical issues needed to create the Internet of Things are substantial, little attention has been given to the behavioral, organizational and business issues that are necessary for a better understanding of the adoption, usage and impact of the IoT. We propose a framework based on the idea that this technology will evolve from monitored “Things”, to “Networks of Things”, and ultimately to an “Internet of Things”. Each of these instantiations of the technology raises adoption, usage and impact issues that can be scrutinized at four levels of analysis: individual, organization, industry, and society. We apply the framework to propose research questions that need to be addressed by researchers.
Big Data has been playing a vital role in almost all environments such as healthcare, education, business organizations and scientific research. Big data analytics requires advanced tools and techniques to store, process and analyze the huge volume of data. Big data consists of huge unstructured data that require advance real-time analysis. Thus, nowadays many of the researchers are interested in developing advance technologies and algorithms to solve the issues when dealing with big data. Big Data has gained much attention from many private organizations, public sector and research institutes. This chapter provides an overview of the state-of-the-art algorithms for processing big data, as well as the characteristics, applications, opportunities and challenges of big data systems. This chapter also presents the challenges and issues in human computer interaction with big data analytics.
For high-security Internet-of-Everything (IoE) devices, a true random number (TRN)-based pseudohysteresis controller (PHC) is proposed to avoid both power side-channel attack (PSCA) and power injection attack (PIA) and reduce electromagnetic interference (EMI) without degrading performance of transient response and regulation. In addition, the TRN-based PHC uses an enhanced security randomizer to correctly generate a random number (RN) independent of the input power at the PSCA and PIA and converts the RN into a hysteresis window that constitutes the true random modulation switching frequency. Therefore, the TRN-based PHC ensures proper spread spectrum and low EMI. In addition, fast transient response is maintained due to inherent hysteresis control. Experimental results show that peak EMI noise is reduced from 89.72 to 54.32 dB
μ
V and meets the specification of EN 55032 Class B even under the PIA interference up to 1 V. Furthermore, in case of 0.2 A-to-0.8 A load step, the method achieves a recovery time of 7.3
μ
s and an output voltage drop of 53 mV at a switching frequency of approximately 1 MHz, and the peak efficiency is 92.4%.
Augmentation and virtualization of resource-poor wireless/ mobile smart things are opening the doors to novel contextaware crowd sensing applications, that allow geographically distributed people/machine users to capture, analyze and share environmental local features of social interest. In order to implement the resulting network of the so-called Internet of Everything (IoE), the emerging technological paradigm of Fog computing (FC) andCloudComputing (CC) are expected to provide the needed network-plus-computing support by allowing the on-the-fly instantiation of software clones (e.g. virtual surrogates) of the physical sensing things onto resource-equipped nearby clouds (e.g. Cloudlets) placed at the edge of the wireless access network. FC essentially involves various types of applications that run both in the Cloud and in smart devices, such as smart gateways and routers, where billions of devices are interconnected using the Internet of Things (IoT). On the basis of these considerations, the creation of dynamic local clouds can lead to a shorter service execution time and provide green computation and communication in order to manage the computation, storage, and communication capabilities of the cloud infrastructures, however, suffer from raising scalability and reliability issues in a highly dynamic environment. Therefore, it is essential to introduce novel techniques to merge the benefits of the CC and makes it applicable in highly volatile IoT devices. As a result, for a highly virtualized platform, where the processing of data and applications execution are no longer performed in the Cloud, FC is emerging as an option of choice with respect to CC. FC is able to handle an increasing number of interconnected devices and an evolving demand of the IoT. By the virtue of its proximity to the end users, FC is able to reduce the data traffic to the Cloud. This makes it timely to investigate new approaches for modeling the new network-aware applications accounts the IoE paradigm. Significant scientific advances on this topic can be made through both in-depth theoretical analyzes and integration of data from related real-world experimental studies. On the other hand, without proper security and privacy-preserving mechanisms, FC cannot be adopted despite its usefulness. Clearly, FC will suffer from the classical security and privacy issues which are inherited from cloud computing. In addition, it suffers from unique threats due to the adoption of Fog devices such as man-in-the-middle attacks.
The papers presented in this special issue provides insights in fields related to IoT and Fog/edge architecture, including parallel processing of the smart system, presenting new emerging models, performance evaluation and improvements, and IoT application developments. We wish the readers can benefit from insights of these papers, and contribute to these rapidly growing areas.
Wearable medical devices with sensor continuously generate enormous data which is often called as big data mixed with structured and unstructured data. Due to the complexity of the data, it is difficult to process and analyze the big data for finding valuable information that can be useful in decision-making. On the other hand, data security is a key requirement in healthcare big data system. In order to overcome this issue, this paper proposes a new architecture for the implementation of IoT to store and process scalable sensor data (big data) for health care applications. The Proposed architecture consists of two main sub architectures, namely, Meta Fog-Redirection (MF-R) and Grouping and Choosing (GC) architecture. MF-R architecture uses big data technologies such as Apache Pig and Apache HBase for collection and storage of the sensor data (big data) generated from different sensor devices. The proposed GC architecture is used for securing integration of fog computing with cloud computing. This architecture also uses key management service and data categorization function (Sensitive, Critical and Normal) for providing security services. The framework also uses MapReduce based prediction model to predict the heart diseases. Performance evaluation parameters such as throughput, sensitivity, accuracy, and f-measure are calculated to prove the efficiency of the proposed architecture as well as the prediction model.
The purpose of this paper is to illustrate the Internet of Everything based integrated security system designed for World War One commemorative Museum of Fogliano Redipuglia in Italy, capable of ensuring visitors security, cultural heritage preservâtion/protection and great usability for visitors, with particular reference to visitors with disabilities. Genetic Algorithms (GAs) have been used to design the integrated security system, in particular for wired network to ensure a reduction of final costs and a high level of reliability and resilience of the system itself, keeping, into consideration, the typical vincula and restrictions of already existing Museums. The proposed system, together with the GAs based optimization technique, thanks to its flexibility, can be used in any kind of museum or any kind of cultural site by means of a proper adaption.
IoT connects devices, humans, places, and even abstract items like events. Driven by smart sensors, powerful embedded microelectronics, high-speed connectivity and the standards of the internet, IoT is on the brink of disrupting today's value chains. Big Data, characterized by high volume, high velocity and a high variety of formats, is a result of and also a driving force for IoT. The datafication of business presents completely new opportunities and risks. To hedge the technical risks posed by the interaction between “everything”, IoT requires comprehensive modelling tools. Furthermore, new IT platforms and architectures are necessary to process and store the unprecedented flow of structured and unstructured, repetitive and non-repetitive data in real-time. In the end, only powerful analytics tools are able to extract “sense” from the exponentially growing amount of data and, as a consequence, data science becomes a strategic asset.
The cloud is increasingly being used to store and process the big data. Many researchers have been trying to protect big data in cloud computing environment. Traditional security mechanisms using encryption are neither efficient nor suited to the task of protecting big data in the Cloud. In this paper, we first discuss about challenges and potential solutions for protecting big data in cloud computing. Second, we proposed MetaCloudDataStorage Architecture for protecting Big Data in Cloud Computing Environment. This framework ensures that efficient processing of big data in cloud computing environment and gains more business insights.
SUMMARY This paper examines the relationship between so-called ‘Big Data’, the ‘Internet of Things’ (the ‘Internet of People and Things,’ and the ‘Internet of Everything’), and the ‘Internet of Signs.’ In particular, we investigate how the ‘things’ in the ‘Internet of Things’ generate ‘Big Data’, and how both are used to generate semiotic ‘signs’. In addition, we analyse the importance of context in and the relationships between ‘Big Data’, the ‘Internet of Things’, and the ‘Internet of Signs’. Copyright © 2013 John Wiley & Sons, Ltd.
Big data is changing the landscape of security tools for network monitoring, security information and event management, and forensics; however, in the eternal arms race of attack and defense, security researchers must keep exploring novel ways to mitigate and contain sophisticated attackers.
Data Management in the Internet of Things (lOT) Era: Common Policy Principles and Data-Handling Framework for Data Security and Privacy
- Media
Media.corporate-ir.net. "Data Management in the Internet of Things (lOT) Era: Common Policy Principles
and Data-Handling Framework for Data Security and Privacy". http://media.corporateir.net/media_files/IROLlI
A True Random Number Based Pseudo Hysteresis Controller for Buck DC-DC Converter in High-Security Internet-of-Everything Devices
- Wen - Yang
- Shao-Wei Hau
- Chun-Chieh Chiu
- Yen-Ting Kuo
- Yan-Jiun Lin
- Hung-Wei Lai
- Yu-Sheng Chen
- Ma
Internet of Everything (IoE): Top 10 Insights from Cisco’s IoE Value at Stake Analysis for the Public Sector
- Joseph Bradley
- Christopher Reberger
- Amitabh Dixit
- Vishal Gupta
- James Macaulay
Bradley, Joseph, Christopher Reberger, Amitabh Dixit, Vishal Gupta, and James Macaulay. "Internet of
Everything (IoE): Top 10 Insights from Cisco's IoE Value at Stake Analysis for the Public Sector." Economic
Analysis (2013).