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The security of sensitive information is an urgent need in today’s communication, principally in cloud and Internet of Things (IoT) environments. Therefore, a well-designed security mechanism should be carefully considered. This paper presents a new framework for secure information in fog cloud IoT. In the framework, the user in one location embeds...
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... Mitigation techniques such as quantum-secure encryption, cryptography, secure communication channels is required to keep users information confidential than other third-party applications [34,41,45,58,60,81] Authentication Secure channels are required for authentication. Quantum key distribution (QKD) must be employed to authenticate users [8, 34, 44-46, 58, 62, 66, 72, 74, 81] Vulnerability The quantum computing technology may not fully eliminate vulnerabilities issues due to outdated software, poor hardware, and various quantum channel attacks [11,16,34,48,66,106] Attacks Quantum computing systems pose significant security risks due to their vulnerability to viruses, malware, and electromagnetic emissions, which can be misused by nasty individuals [11,16,34,[37][38][39]. [17,40,46,52,63,66,72,106] Computation memory In-memory computation refers to the operation of a computer in its memory. Quantum process may not fully utilize the overall memory to perform various task due to outdated scheduling algorithms [8,35,67,70] Hardware Quantum computing faces significant hardware limitations due to its incompatibility with conventional hardware and requiring specialized knowledge for upgrades and modifications, limiting its application in medium-sized businesses. ...
... Quantum process may not fully utilize the overall memory to perform various task due to outdated scheduling algorithms [8,35,67,70] Hardware Quantum computing faces significant hardware limitations due to its incompatibility with conventional hardware and requiring specialized knowledge for upgrades and modifications, limiting its application in medium-sized businesses. Complex hardware architectures, and control techniques are required for qubit communication [8,35,41,50,61,66,71,[74][75][76] Transmissions Quantum computing faces challenges due to the intricate nature of quantum states, the need for secure communication over extended distances, specialized protocols, quantum entanglement, signal deterioration, error correction, quantum state susceptibility, which are restricted by conventional channels, networks, technologies, devices, and algorithms [11,44,46,64,68] Content courtesy of Springer Nature, terms of use apply. Rights reserved. ...
... The steganography protocol is exclusively responsible for transmitting and verifying the hidden message, without any involvement of other quantum communications or states. To ensure the security of the steganography protocol, a hash function is employed for verification purposes [46] Quantum election protocol The combination of quantum digital signature and quantum public key encryption, along with traditional public key encryption, creates a quantum election protocol suitable for large-scale elections with multiple candidates and voters, without requiring confidential key sharing or third-party involvement [63] Quantum security Hybrid IoT security A new security framework, incorporating quantum states, is introduced to protect against eavesdroppers and cyber threats. The BB84 protocol is modified for IoT, using the "One-Time pad" cryptographic technique. ...
With the advent of internet-enabled and hybrid technologies, information is becoming increasingly accessible to the general public. Smartphones and other gadgets are used extensively by people to share and promote ideas, in a variety of ways. Human interaction and communication has become more reliable and effective through advanced computing technologies. Quantum computing is an emerging paradigm that will change the lives of individuals and the operations of organizations. Quantum computers solve problems at high speed by operating in a superposition state in which the state can be either zero or one at the same instant. Quantum sensors can be used efficiently in technological research to make accurate measurements and collect data that provide new insights into the behavior of nanomaterials. The use of quantum computing could also speed up the manufacturing process of devices with remarkable properties such as superconductivity, high strength or improved signal performance. Quantum computing has the ability to dramatically speed up the development process of various organizations and increase their efficiency and effectiveness. The security and reliability of data and communication is improved by quantum computing techniques such as key generation and entanglement dispersion. Companies use cryptographic algorithms to protect their data. However, with the advent of quantum computing, cryptographic methods that rely on numerical aspects are no longer sufficient to protect data. Quantum computing is an emerging field that is being applied to various problems that previously could not be solved using conventional methods. Quantum computing plays an important role in the field of information processing, where information is precisely analyzed. Various quantum technologies and algorithms are used to secure company data. This paper provides a systematic review of the literature on the principles of quantum computing. The SLR focuses on achieving four aims “identifying a variety of quantum IoT devices, analyzing their importance in different industries, highlighting the challenges of quantum technology, and presenting various techniques used by researchers to overcome different problems”. Quantum cryptography is identified as a key strategy for improving the security of IoT systems and ensuring the security and consistency of information.
... Error correction: Quantum systems are susceptible to errors as a result of quantum decoherence (El-Latif et al., 2018) and various sources of noise. The inclusion of effective mistake correcting techniques is necessary in order to uphold the integrity of the protocols. ...
... This not only enabled users to inquire about historical data and bills, but also ensured secure data sharing with third-party entities. El-Latif et al. (2018) introduced a fresh framework designed for safeguarding information within the context of fog cloud IoT. Within this framework, a user at one location concealed their valuable data using the proposed quantum steganography protocol, and then uploaded the concealed data to the fog. ...
With the development of technology and its integration with scientific realities, computer systems continue to evolve as infrastructure. One of the most important obstacles in front of quantum computers with high‐speed processing is that its existing systems cause security vulnerabilities. Therefore, in order to take advantage of quantum systems, existing systems that are already secure must also be secure in the post‐quantum scenario. One of these systems is edge computing. There are challenges in terms of computational power for the implementation of pre‐ and post‐quantum methods in structures with resource‐constrained devices. This article reviews the post‐quantum security threats of edge devices and systems and the secure methods developed for them. Although there is relatively little research in this field, it remains relevant. In the studies reviewed, lattice‐based approaches are often highlighted for making edge systems quantum‐resistant. Additionally, these studies indicate that there has been an increasing trend in this field in recent years.
This article is categorized under: Applications of Computational Statistics > Defense and National Security
Algorithms and Computational Methods > Networks and Security
... Any quantum communication protocol must pass a security analysis as a critical component of its evaluation to be secure from eavesdropping attacks. Researchers frequently utilize security analysis to assess the security needs of their protocols and determine whether an eavesdropper is likely to be around [22,35,44]. The proposed authentication protocol's security relies on the quantum uncertainty principle and the quantum no-cloning theorem of the secret message to protect against unconditional attack, but it also applies the introduced authentication key to the quantum state to double-secure the messages. ...
Authentication is a security function that ensures the system's proper security by identifying and verifying users. Despite the advantages of quantum computers, it is still difficult to enforce authentication on behalf of multiple quantum channel users without the involvement of a third party because present protocols only consider two parties involved in communication. Scalability becomes an issue as the number of parties engaged in the quantum network increases. In addition, an eavesdropper may disguise herself among numerous participants and take advantage of the circumstances to gather information. The authentication method should be used throughout the quantum data exchange process to ensure that the parties participating in the protocol are who they claim to be. The suggested protocol's implementation has been tested using a simulation written in Python. This research aims to propose a protocol for multiparty authentication procedures without the assistance of a third party. The result of the proposed protocol is expected to be a simple and reliable quantum experiment. Importantly, this protocol can establish an environment that is more secure in terms of authentication and allows numerous parties to communicate freely and openly.
... El-Latif et al. [394] The authors proposed a security technique based on a quantum steganography architecture to secure the flow of communications in fog cloud IoT. ...
In recent times, the machine learning (ML) community has recognized the deep learning (DL) computing model as the Gold Standard. DL has gradually become the most widely used computational approach in the field of machine learning, achieving remarkable results in various complex cognitive tasks that are comparable to, or even surpassing human performance. One of the key benefits of DL is its ability to learn from vast amounts of data. In recent years, the DL field has witnessed rapid expansion and has found successful applications in various conventional areas. Significantly, DL has outperformed established ML techniques in multiple domains, such as cloud computing, robotics, cybersecurity, and several others. Nowadays, cloud computing has become crucial owing to the constant growth of the IoT network. It remains the finest approach for putting sophisticated computational applications into use, stressing the huge data processing. Nevertheless, the cloud falls short because of the crucial limitations of cutting-edge IoT applications that produce enormous amounts of data and necessitate a quick reaction time with increased privacy. The latest trend is to adopt a decentralized distributed architecture and transfer processing and storage resources to the network edge. This eliminates the bottleneck of cloud computing as it places data processing and analytics closer to the consumer. Machine learning (ML) is being increasingly utilized at the network edge to strengthen computer programs, specifically by reducing latency and energy consumption while enhancing resource management and security. To achieve optimal outcomes in terms of efficiency, space, reliability, and safety with minimal power usage, intensive research is needed to develop and apply machine learning algorithms. This comprehensive examination of prevalent computing paradigms underscores recent advancements resulting from the integration of machine learning and emerging computing models, while also addressing the underlying open research issues along with potential future directions. Because it is thought to open up new opportunities for both interdisciplinary research and commercial applications, we present a thorough assessment of the most recent works involving the convergence of deep learning with various computing paradigms, including cloud, fog, edge, and IoT, in this contribution. We also draw attention to the main issues and possible future lines of research. We hope this survey will spur additional study and contributions in this exciting area.
... Despite the anticipated storage and network issues, the results reveal that the proposed solution meets the secure information management needs of 5% of patients. Another technique, suggested in [24], proposes a method of quantum steganography which uses a hashing algorithm to validate security. The approach proposed in [24] is only relevant for securing messages in foggy IoT platforms, according to the authors of [25]. ...
... Another technique, suggested in [24], proposes a method of quantum steganography which uses a hashing algorithm to validate security. The approach proposed in [24] is only relevant for securing messages in foggy IoT platforms, according to the authors of [25]. ...
Convolutional neural networks (CNNs) have gained popularity for Internet-of-Healthcare (IoH) applications such as medical diagnostics. However, new research shows that adversarial attacks with slight imperceptible changes can undermine deep neural network techniques in healthcare. This raises questions regarding the safety of deploying these IoH devices in clinical situations. In this paper, we review the techniques used in fighting against cyber-attacks. Then, we propose to study the robustness of some well-known CNN architectures’ belonging to sequential, parallel, and residual families, such as LeNet5, MobileNetV1, VGG16, ResNet50, and InceptionV3 against fast gradient sign method (FGSM) and projected gradient descent (PGD) attacks, in the context of classification of chest radiographs (X-rays) based on the IoH application. Finally, we propose to improve the security of these CNN structures by studying standard and adversarial training. The results show that, among these models, smaller models with lower computational complexity are more secure against hostile threats than larger models that are frequently used in IoH applications. In contrast, we reveal that when these networks are learned adversarially, they can outperform standard trained networks. The experimental results demonstrate that the model performance breakpoint is represented by γ = 0.3 with a maximum loss of accuracy tolerated at 2%.
... There are various use-cases for QSS in IoT domain. For example, a novel quantum steganography protocol is proposed in fog and mobile edge computing [34]. ...
Quantum Key Distribution (QKD) is a promising paradigm for Internet of Things (IoT) networks against eavesdropping attacks. However, classical quantum-based mechanisms are overweight and expensive for resource-constrained IoT devices. That is, the devices need to frequently exchange with the QKD controller via an out-band quantum channel. In this paper, we propose a novel Quantum-based Secure and Lightweight Transmission (QSLT) mechanism to ease the overweight pain for IoT devices against eavesdropping. Particularly, the mechanism predistributes quantum keys into IoT devices with SIM cards. Using one of the keys, QSLT encrypts or decrypts IoT sensitive data. It is noting that an in-band key-selection method is used to negotiate the session key between two different devices. For example, on one IoT device, the in-band method inserts a key-selection field at the end of the encrypted data to indicate the key’s sequence number. After another device receives the data, QSLT extracts the key-selection field and decrypts the data with the selected quantum key stored locally. We implement the proposed mechanism and evaluate its security and transmission performances. Experimental results show that QSLT can transmit IoT data with a lower delay while guaranteeing the security performance. Besides, QSLT also decreases power usage by approximately 58.77% compared with state of the art mechanisms.
... Many study disciplines have seen great possibilities and problems due to the introduction of the national form of huge online information, which has piqued scientists' curiosity. For instance, users tie their location to a posted text document on the Chinese territory via the blog site [9]. ...
... in the stable equilibrium of the probabilistic network with grouped vertex. Equation (9) determines if the probabilistic graph has reached a stable level. ...
Today, artificial intelligence (AI) can be found in nearly every aspect of travel and tourism, from personalization and recommendation systems to robotics to conversational systems to intelligent travel agents to forecasting and prediction tools and systems for language translation. As a result, this study examines the connection between large-scale big data analysis and smart tourism, resulting in a massive data platform for forecasting and providing feedback on smart tourist developments.This article aims to shed light on the importance of AI in the travel and tourism sector. Many cybersecurity firms are stepping to raise their efforts using artificial intelligence to attain this goal because effective information security is necessary for better detection.An intelligent all-area-advanced tourism cloud platform is demonstrated in this paper, as well as how to design the overall system framework, system structure, and database systems needed to integrate all of the province's tourism resources into a single information resource sharing system.Furthermore, this paper presents an intelligent decision-support system based on big data to reimagine tourism public administration and service. It moreover examines the ramifications of this decision-making mode and implementation procedures. This study covers the framework operation's elements, environment features, and promotion mode by creating a tourism public management and service framework based on big data. Big data-driven decision-support and management can overhaul tourism public management and service models. Cyber threat intelligence and applications, including those that defend systems, networks, programs, devices, and data from cyber threats, could significantly impact this tourism industry.The present tourism industry's problem-solving efficiency, quality, and services have increased. The simulation evaluation can promote the public tourism service in sustainable tourism development with an improved decision accuracy of 97.21%.
... Preserving security using quantum steganography is a novel approach that adheres to the fog cloud IoT framework according to the research proposed by El-latif et al. [11]. Here, users embed their secrets using quantum steganography, and the recipient can extract them using the extraction method. ...
... This novel approach does not consume any other side-channel for the secure transfer of secrets. Different types of performance analysis ensure the proposed work of [11] is one of the remarkable ones. ...
... Henceforth no embedding or modification bits are required. So fundamentally, it resists any steganalysis detection and any attackers' suspicion [11]. We explain some of the security analyses hereunder. ...
Cloud storage is an essential and most demanding application for enterprise and private use in today’s communication. However, the data security over the distributed cloud resources is threatened due to numerous security challenges. Analyzing and reviewing the existing security policies are necessary to prevent unauthorized infringement of sensitive information in cloud storage. Therefore, a convenient and adaptable security framework should be designed. However, traditional steganographic systems use the embedding technique substantially by transforming carriers which unavoidably leaves the evidence. Therefore the transforming bits can be easily detected through steganalysis. This paper proposes a novel steganography approach to ensure the security of sensitive information in cloud storage. The approach uses the realization over embedding technique, which stores only the cover-secret mapping instead of original information in the cloud by taking significantly less storage space. Enhanced Longest Common Subsequence (Enhanced- LCS) is used here to generate the secure reversible mapping, and data hiding methodology is used to mask the secret in this framework. This mapping is fully realized only by the dedicated recipient with keys. The Cantor pairing function is used for constructing keys. We significantly reduce the time and space complexity by using the Enhanced-LCS algorithm. Space and time complexities are calculated as O(n) and \(O (n*\log (n))\) here. Divergent file types such as image, word, and PDF files with different dimensions have been used to perform experimental analysis. This approach also ensures protection against some of the well-known security attacks. Different types of performance analysis make this framework more efficient and robust.
... The proficiency of the traditional E-Health models is highly vulnerable to cyberattacks, such as ransomware, Denial-of-service (DoS) attack, and various other data breaches that replicates disruption in the medical services (Abdolkhani, Gray, Borda, & DeSouza, 2019;Veeramakali, Siva, Sivakumar, Senthil Mahesh, & Krishnaraj, 2021). The security of these data in the cloudenabled system is ensured by using cryptography techniques (El-Latif, Abd-El-Atty, Hossain, Elmougy, & Ghoneim, 2018;Li, Abd-El-Atty, El-Latif, & Ghoneim, 2017), and other data hiding techniques. One of the significant and widely used data hiding mechanisms is information hiding which can be categorized into steganography and watermarking. ...
Secure transmission of data is achieved through the steganography images, where the secret data are embedded and transmitted so that the prohibited users couldn’t able to access the data. In this research, the data are embedded in the optimal location of the network using the proposed FIEO Optimal Location Enabled Stegochain. The algorithm effectively determines the location for the embedding of secret data in the finest region of the image with faster convergence. The two different steps utilized in the research is the determination of the optimal location for embedding the image using the proposed algorithm and the embedded image transformation using the discrete wavelet transform while transferring the image is the first step. And the reconstruction of the original image at the receiver side with the help of the Inverse discrete wavelet transform is performed (IDWT). The performance of the proposed method is evaluated in terms of the performance metrics such as correlation coefficient, and PSNR with the salt and pepper noise is 0.777, and 52.588 respectively. Similarly, for the random noise the correlation coefficient and PSNR obtained by the proposed method are 0.796, and 52.397 respectively.
