FIGURE 1 - uploaded by Ikram Ud Din
Content may be subject to copyright.
Source publication
The Internet of Things (IoT) is an emerging classical model, envisioned as a system of billions of small interconnected devices for posing state-of-the-art findings to real world glitches. Over the last decade, there has been an increasing research concentration in the IoT as an essential design of the constant convergence between human behaviors a...
Context in source publication
Similar publications
The natural and man-made disasters are inevitable in many circumstances. Thus, an effective disaster management system is vital for any community that can use state-of-the-art technologies to deal with such cataclysmic events. There is plethora of latest technologies such as Internet of Things (IoT), Cloud and Fog Computing that have provided the r...
Convenience is an important factor for people in daily activities particularly for users who consume goods and services and also for retailers who provide such services. The retail industry took infant steps in the early 20th century across most of Europe and America. However, there was a considerable surge in the rise of supermarkets and hypermark...
Citations
... Fog computing is an emerging paradigm that extends cloud computing capabilities to the network edge, closer to end-users and devices [14]. It leverages the concept of the three-tier architecture, which consists of three distinct layers: the cloud, the fog, and the edge [15][16][17]. The cloud represents centralized data centers with high computational and storage capabilities. ...
The Internet of Things (IoT) has revolutionized connected devices, with applications in healthcare, data analytics, and smart cities. For time-sensitive applications, 5G wireless networks provide ultra-reliable low-latency communication (URLLC) and fog computing offloads IoT processing. Integrating 5G and fog computing can address cloud computing’s deficiencies, but security challenges remain, especially in Authentication and Key Agreement aspects due to the distributed and dynamic nature of fog computing. This study presents an innovative mutual Authentication and Key Agreement protocol that is specifically tailored to meet the security needs of fog computing in the context of the edge–fog–cloud three-tier architecture, enhanced by the incorporation of the 5G network. This study improves security in the edge–fog–cloud context by introducing a stateless authentication mechanism and conducting a comparative analysis of the proposed protocol with well-known alternatives, such as TLS 1.3, 5G-AKA, and various handover protocols. The suggested approach has a total transmission cost of only 1280 bits in the authentication phase, which is approximately 30% lower than other protocols. In addition, the suggested handover protocol only involves two signaling expenses. The computational cost for handover authentication for the edge user is significantly low, measuring 0.243 ms, which is under 10% of the computing costs of other authentication protocols.
... Nowadays, all kinds of objects are connected to the Internet and can communicate without human intervention. The autonomy and performance of these devices depend on the technologies present in each functional block of IoT systems [1][2][3]. Wireless sensor networks (WSNs) and low-power and lossy networks (LLNs) are the building blocks of the IoT. They provide scalability and support for diverse applications, such as environmental monitoring and remote sensing, patient monitoring and telemedicine, logistics and transportation industries, asset tracking, and other smart city applications [4]. ...
... Using (2), (3), and the expected value definition, we derive the average time needed for a join-seeker to get associated with a synchronizer as the following: ...
Time slotted channel hopping (TSCH) has become the standard multichannel MAC protocol for low-power lossy networks. The procedure for associating nodes in a TSCH-based network is not included in the standard and has been defined in the minimal 6TiSCH configuration. Faster network formation ensures that data packet transmission can start sooner. This paper proposes a dynamic beacon transmission schedule over the TSCH mechanism that achieves a shorter network formation time than the default minimum 6TiSCH static schedule. A theoretical model is derived for the proposed mechanism to estimate the expected time for a node to get associated with the network. Simulation results obtained with different network topologies and channel conditions show that the proposed mechanism reduces the average association time and average power consumption during network formation compared to the default minimal 6TiSCH configuration.
... Major enablers for the rollout of IoT are networks like Low Power and Lossy Networks (LLNs), consisting of a number of devices with minimum resources. Real-world examples of heavy reliance on such networks include [2] smart houses, healthcare and smart cities. Throughout the IoT, routing is a crucial procedure for linking together the various network nodes that make up the various apps. ...
Routing Protocol for Low-Power and Lossy Networks (RPL) has been used in the Internet of Things (IoT) with Wireless Sensor Networks (WSNs), but it is does not give much focus to protect against routing attacks. Therefore, it is possible for an attacker to utilize the RPL routing system as an initial platform for devastating and crippling attacks on an IoT network. In IoT based networks, RPL provides a minimal level of protection against a wide variety of attacks, which are unique to RPL and are launched in WSNs. Moreover, the traditional Internet and routing security solutions also have memory, processing, and resource limitations that make them ineffective for IoT devices. Several mitigation schemes, such as those based on rule-based learning algorithms, Intrusion Detection Systems (IDSs), and trust computation and management techniques were proposed in the past to improve the safety of IoT networks and routing, but they do not provide the required security. To overcome these security issues, we propose an intelligent IDS in this article to detect and isolate the RPL attacks. For this purpose, we propose a new classification algorithm based on neural networks and genetic algorithms. Moreover, the proposed Neuro Genetic Classification Algorithm (NGCA) detects the nodes which launch RPL and other attacks more accurately and hence it increases the network security in IoT. From the experiments done with NSL-KDD data-set, it is proved that the proposed NGCA is detecting the attacks with higher accuracy than the other classifiers namely Decision Trees, Logistic Regression and Support Vector Machines. It also helps to reduce the RPL attacks in the routing process with enhanced detection rate with reduced false positives.
... The actual value of IoT for enterprises can be fully realized when entire connected devices are capable of communicating with each other, and the protocol is so rugged that it can integrate with heterogeneous vendor-managed inventory systems, customer support systems, business intelligence applications, and business analytic (Lee and Lee, 2015). IoT has a wide range of applications, such as Smart Industries, Smart Agriculture, Smart Homes, Intelligent Transport Systems, Security Systems, and Smart Healthcare (Qiu et al., 2018;Din et al., 2018). Fig. 1 describes the conventional IoT architecture in the bottom-totop hierarchy. ...
The Internet of Things (IoT) is an emerging field of technology with a huge scope of its applicability in various industries and a wide range of societal needs, including medical sciences. However, IoT suffers from many limitations like energy, resource constraints, scalability, security, availability, etc. Software-Defined Networking (SDN) is another similar technology that has many features that are capable of solving many of the limitations of the conventional IoT system. So, suitably incorporating SDN technology into the conventional IoT system, an improved version of IoT namely an SDN-based IoT network system has been evolved. This system is capable of resolving many of the limitations of IoT. Since this newer SDN-based IoT version is enriched with better energy and resources, it can undertake higher computational loads to resolve security issues. In the security domain, Blockchain is a state-of-the-art security-based technology in recent times which has already been implemented in the fields of cryptocurrency effectively. So, Many research opportunities emerge out in adapting Blockchain-based technology suitable for the SDN-based IoT Networking domain. This paper deals with the investigations carried out by the past researchers on various security aspects of the IoT, SDN, and SDN-based IoT systems and their solutions using various technologies, including that of Blockchain. It was concluded that the convergence of Blockchain in IoT and SDN and its combination (SDN-based IoT) resolved many security issues. Many prominent research gaps still persist here to be resolved. This can be dealt with as a future scope of research opportunities in the domain.
... Because social networks have a high degree of transitivity, if two users have the same neighbors, the two users have the opportunity to know, so the similarity between users can play a more important role in information dissemination, for example, if the similarity between these two users is relatively low, it will take more time to transmit the same length of information, so the similarity can be used to calculate the sociability and friendliness between two mobile users, according to the literature [31], get nodes (s, t) The similarities of friendship between the two are expressed as follows: ...
With the development of computing technology, the storage space and computing power of IoT devices have developed rapidly. Due to the social nature of people, users who have social relationships with each other IoT devices are relatively close in some time periods, but are far away from traditional edge nodes. It is far away, so service providers can temporarily rent suitable IoT devices to act as edge storage nodes based on the storage computing power and social status of user equipment. In the process of selecting edge nodes by service providers, this paper firstly describes the social relationships of users to which the edge nodes belong and some requirements for storage. Then, based on the above considerations, a method based on social and The edge node selection algorithm of equipment storage, and the subsequent modeling of the problem of service providers' selection of edge nodes as the problem of maximizing social benefits, through the use of matching algorithms, proves that the algorithm proposed in this paper can effectively select edge nodes, and subsequent simulation experiments The experimental results also show that the proposed algorithm can maximize the social benefits of service providers and users.
... In cases where the devices cannot meet their own computational and storage needs because the temporary edge nodes may cache some resources needed by users, it can be considered to offload computational tasks from the devices to the temporary edge nodes for execution. [11][12][13][14] If the memory of the temporary nodes is not sufficient, the tasks can be directly offloaded to traditional edge servers for processing. In the process of offloading, this paper mainly considers reducing user energy consumption and latency while also considering user preferences to minimize the total cost of offloading based on user satisfaction. ...
After the service provider temporarily selects the required edge nodes based on social and storage capabilities, application execution causes the edge nodes to cache part of the application data. Therefore, offloading part of the application computing tasks to the selected edge nodes can effectively improve application execution performance. However, in cases where the resources of user’s IoT devices are insufficient, tasks can be further offloaded to traditional edge servers or even to the cloud to maximize application execution efficiency. In this paper, the entire uninstall utility is modeled as a weighted sum of task completion time and energy consumption. Under the premise of considering users’ preferences for completion time and energy consumption, a game-based uninstallation algorithm is proposed. The algorithm performs uninstallation by optimizing the uninstallation decision. Based on user preferences, the total system overhead is relatively small. The subsequent simulation experiments show that the algorithm can reduce system overhead on the basis of satisfying user preferences and has relatively good adaptability.
... This need has led to the innovation of Rapid Recover Map Reduce (RR-MR), a groundbreaking approach designed to elevate failure recovery mechanisms within the realm of Big Data processing. 1 In the realm of Big Data, where vast amounts of information are processed to extract valuable insights, the occurrence of failures is not uncommon. Hardware glitches, software bugs, network interruptions, and other unforeseen issues can disrupt the seamless execution of data processing jobs, leading to delays, data loss, and increased operational costs. ...
The rapid growth of Big Data applications has brought forth unprecedented opportunities for insights and innovation, but it has also exposed the inherent vulnerabilities of data processing pipelines to failures. Hardware glitches, software anomalies, and network interruptions can disrupt the smooth execution of critical tasks, leading to extended downtimes, compromised reliability, and increased operational costs. In response to these challenges, we introduce Rapid Recover Map Reduce (RR-MR), an innovative framework designed to revolutionize failure recovery mechanisms within the context of Big Data applications. RR-MR addresses the shortcomings of conventional Map Reduce frameworks by presenting a novel approach to failure recovery that focuses on expeditious restoration of processing tasks. By leveraging advancements in distributed systems, fault tolerance, and parallel processing techniques, RR-MR introduces a multi-faceted strategy that enhances both the efficiency and reliability of recovery processes. URN:NBN:sciencein.jist.2024.v12.773
... The characteristics of quantum mechanics have been utilized by Bennet and Brassard [2] to create the very first Quantum Keys Distribution (QKD) method -the BB84 protocolwhich is used to distribute session keys for two end users. Certain investigations have found that the BB84 protocol is a binding security protocol. ...
... The semi-quantum distribution key protocol and the independent measurement instrument (MDI) QKD Key were presented to enhance the feasibility of QKD protocols under the presence of quantum technologies. Different quantum protocols for multiple applications have also been suggested, such as quantum secure direct interaction, quantum secrecy (QSS), quantum comparison of private use, and quantum information sharing [2]. However, contrary to the existing public-key cryptographic systems in the current network environment, QKD protocols cannot provide the service of key distribution as core infrastructure, due to limits of quantum computing (e.g., the reachable distance of qubit transmission and the accuracy of the qubit detector). ...
The globe is observing the emergence of the Internet of Things more prominently recognized as IoT. In this day and age, there exist numerous technological apparatuses that possess the capability to be interconnected with the internet and can amass, convey, and receive information concerning the users. This technology endeavors to simplify existence, however, when the users' information is the central concern for IoT operation, it is necessary to adhere to security measures to guarantee privacy and prevent the exploitation of said information. The customary cryptographic algorithms, such as RSA, AES, and DES, may perform adequately with older technologies such as conventional computers or laptops. Nevertheless, contemporary technologies are heading towards quantum computing, and this latter form possesses a processing capability that can effortlessly jeopardize the aforementioned cryptographic algorithms. Therefore, there arises an imperative necessity for a novel and resilient cryptographic algorithm. To put it differently, there is a requirement to devise a fresh algorithm, impervious to quantum computing, that can shield the information from assaults perpetrated utilizing quantum computing. IoT is one of the domains that must ensure information security against malevolent activities. Besides the conventional cryptography that enciphers information into bits, quantum encryption utilizes qubits, specifically photons and photon polarization, to encode data.
... Hardware security is beneficial in the Internet of Things (IoT) environment. The IoT defines as the connection between physical objects over the Internet via smart computing devices [8], [9], [10]. It has expanded its arm towards every aspect of modern life, including the critical sector in applications like e-health care, banking, energy sector, defense applications, etc. Nowadays, all types of businesses, hospitals, companies, shopping malls, financial institutions, home appliances, and space science research facilities are gradually converting to smart platforms, connecting all electronic devices for collecting, processing, and transmitting data quickly. ...
... An architecture-level reservationassisted security enhancement scheme was also suggested to enhance security in DWDM-based PNoCs. The proposed method combines the circuit-and architecture-level schemes into a comprehensive framework called SOTERIA and analyzes it on the Firefly [8] and Flexishare [9] crossbars. SOTERIA has just modest overheads of up to 10.6% in average latency and up to 13.3% in the Energy-Delay Product (EDP), significantly improving the hardware security in dense-wavelength division-multiplexing (DWDM) based PNoCs. ...
... Heterogeneity of devices proposes a huge challenge to the routing process. Other challenges include the network architecture, security requirements, reliable traffic management, effectiveness of the storage systems used etc. [6]. The network can sometimes be dynamic in nature resulting in failure of communication between the nodes. ...
Wireless IoT has been one of the major breakthroughs of the current decade. It has improved the quality of life and has also aided in several improvements in domains like healthcare. Effective routing and energy conservation has been the major challenges in creating and maintaining a successful IoT network. This work presents a checkpoint based routing model, CSPR, to improve the transmission efficiency by reducing retransmission. This work selects checkpoints in the network prior to transmission. The checkpoints are used to build the final path. This process ensures that the routes created are dynamic and reactive, leading to improved security and increased path reliability. Comparison with existing routing model shows improved network lifetime and reduced selection overhead levels, exhibiting the high efficiency of CSPR.
