Integrating PHY Security Into NDN-IoT Networks By Exploiting MEC: Authentication Efficiency, Robustness, and Accuracy Enhancement

Peng, Hao; Wang, Xianbin

doi:10.1109/tsipn.2019.2932678

Cited by 14 publications

(6 citation statements)

References 36 publications

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“…This feature enables resource constrained IoT nodes for utilizing integrity verification mechanisms available under 5G RAN. For IoT devices, hash-based and session-key based encryption schemes could be employed for ensuring integrity at the PHY level [57].…”

Section: ) Possible Integrity Violationsmentioning

confidence: 99%

Survey on Multi-Access Edge Computing Security and Privacy

Ranaweera

Jurcut

Liyanage

2021

IEEE Commun. Surv. Tutorials

182

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The European Telecommunications Standards Institute (ETSI) has introduced the paradigm of Multi-Access Edge Computing (MEC) to enable efficient and fast data processing in mobile networks. Among other technological requirements, security and privacy are significant factors in the realization of MEC deployments. In this paper, we analyse the security and privacy of the MEC system. We introduce a thorough investigation of the identification and the analysis of threat vectors in the ETSI standardized MEC architecture. Furthermore, we analyse the vulnerabilities leading to the identified threat vectors and propose potential security solutions to overcome these vulnerabilities. The privacy issues of MEC are also highlighted, and clear objectives for preserving privacy are defined. Finally, we present future directives to enhance the security and privacy of MEC services.

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Section: ) Possible Integrity Violationsmentioning

confidence: 99%

Survey on Multi-Access Edge Computing Security and Privacy

Ranaweera

Jurcut

Liyanage

2021

IEEE Commun. Surv. Tutorials

182

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“…For fairness, we define efficient energy density as the energy density that is used only to transmit the data of authenticated users. The efficient energy density can be transformed from (10)…”

Section: Benefit Of the Authentication In Reducing Energy Densitymentioning

confidence: 99%

Reliable resource allocation with RF fingerprinting authentication in secure IoT networks

Lin

et al. 2022

Sci. China Inf. Sci.

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The unprecedented growth of the Internet of Things (IoT) has led to a huge amount of wireless resource consumption in a network. Due to limited wireless resources, a network can only guarantee the quality of service (QoS) of authenticated users rather than that of all users. By acknowledging this limitation, we realise that user authentication would be a big issue in IoT networks. Although traditional authentication methods can enhance network security to a certain extent, their vulnerability to malicious attacks and the relevant complicated computations restrict IoT deployments. In this paper, a radio frequency (RF) fingerprinting based authentication scheme is proposed under the architecture of convolutional neural network (CNN). It can effectively prevent unauthenticated users from consuming valuable wireless resources and significantly improve QoS performance for legitimate users. By solving an NP-hard optimization problem with the objective of minimizing efficient energy density, we demonstrate an approximate optimal resource allocation scheme in consideration of an RF-fingerprinting based authentication process. The analytic results show that our proposed scheme can dramatically reduce the efficient energy density compared with traditional cryptography based authentication schemes.

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“…The developer should always try for the improvement of accuracy and correctness of the system. Hence, some research work should be carried out to improve the accuracy of the frameworks [61,62].…”

Section: Future Research Directionsmentioning

confidence: 99%

Blockchain-Envisioned Secure Authentication Approach in AIoT: Applications, Challenges, and Future Research

Wazid

Das

2021

Wireless Communications and Mobile Computing

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The Artificial Intelligence of Things (AIoT) is the amalgamation of Artificial Intelligence (AI) methods and the Internet of Things (IoT) infrastructure, which are deployed there to improve the overall performance of the system. AIoT can be deployed to achieve more efficient IoT operations; thereby can improve human-machine interactions and provide better data analysis. AI methods can be used to transform IoT data into useful information for the better decision-making processes, and it further increases the overall usability of the system. AIoT frameworks are very useful and applicable in a variety of applications, like security and surveillance system, smart home, intelligent transportation system, smart farming, secure and safe healthcare monitoring, industrial automation and control, eCommerce, logistics operations and control, and many more. However, AIoT frameworks may have issues related to data security and privacy as they are vulnerable to various types of information security-related attacks. These issues further cause the serious consequences, like the unauthorized data leakage and data update. Blockchain is a specific type of database. It is a digital ledger of transactions, which is duplicated and distributed across the entire network of computer systems. It stores data in the form of some blocks, which are then chained together. Blockchain is tamper proof and provides more security as compared to the traditional security mechanisms. Hence, blockchain can be integrated in various AIoT applications to provide more security. A generalized blockchain-envisioned secure authentication framework for AIoT has been proposed. The adversary model of blockchain-envisioned secure authentication framework for AIoT is also highlighted that covers most of the potential threats of a kind of communication environment. Various applications of the proposed framework are also discussed. Furthermore, different issues and challenges of the proposed framework are highlighted. In the end, we also provide some future research directions relevant to the proposed framework.

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Integrating PHY Security Into NDN-IoT Networks By Exploiting MEC: Authentication Efficiency, Robustness, and Accuracy Enhancement

Cited by 14 publications

References 36 publications

Survey on Multi-Access Edge Computing Security and Privacy

Survey on Multi-Access Edge Computing Security and Privacy

Reliable resource allocation with RF fingerprinting authentication in secure IoT networks

Blockchain-Envisioned Secure Authentication Approach in AIoT: Applications, Challenges, and Future Research

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