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Telecommunication Systems
Published in: Telecommunication Systems 3/2024

23-01-2024

Secure and trustworthiness IoT systems: investigations and literature review

Authors: Wiem Bekri, Rihab Jmal, Lamia Chaari Fourati

Published in: Telecommunication Systems | Issue 3/2024

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Abstract

Internet of Things (IoT) is creating a new automated environment where human interaction is limited, in which smart-physical objects obtain the power to produce, acquire, and exchange data seamlessly. Hence, diverse IoT systems concentrate on automating various tasks. These automated applications and systems are highly promising to increase user satisfaction while also increasing security-related challenges. Accordingly, Security and Trust are critical elements for users' well-being. In this paper, we investigate the security and trust properties along with the focus on various existing novel technologies (Software-defined networking, Blockchain, and Artificial Intelligence) and provide a survey on the current literature advances towards secure and trustworthy IoT. Furthermore, we present a detailed study on various security and trust issues in various IoT environments. Moreover, we discuss real-life IoT-security projects, specify research challenges, and indicate future research trends.
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Literature
1.
Atzori, L., Iera, A., & Morabito, G. (2010). The internet of things: A survey. Computer networks, 54(15), 2787–2805.CrossRef
2.
Bekri, W., Jmal, R., & Fourati, L. C. Internet of Things Management Based on Software Defined Networking: A Survey.
3.
Scarpato, N., Pieroni, A., Di Nunzio, L., & Fallucchi, F. (2017). E-health-IoT universe: A review. Management, 21(44), 46.
4.
Gerla, M., Lee, E. K., Pau, G., & Lee, U. (2014). Internet of vehicles: From intelligent grid to autonomous cars and vehicular clouds. In: 2014 IEEE world forum on internet of things (WF-IoT) (pp. 241–246). IEEE.
5.
Gungor, V. C., Sahin, D., Kocak, T., Ergut, S., Buccella, C., Cecati, C., & Hancke, G. P. (2011). Smart grid technologies: Communication technologies and standards. IEEE transactions on Industrial informatics, 7(4), 529–539.CrossRef
6.
7.
Su, K., Li, J., & Fu, H. (2011). Smart city and the applications. In: 2011 international conference on electronics, communications and control (ICECC) (pp. 1028–1031). IEEE.
8.
Zhao, J. C., Zhang, J. F., Feng, Y., & Guo, J. X. (2010). The study and application of the IOT technology in agriculture. In: 2010 3rd International Conference on Computer Science and Information Technology (Vol. 2, pp. 462–465). IEEE.
9.
Bhatt, S., & Ragiri, P. R. (2021). Security trends in Internet of Things: A survey. SN Applied Sciences, 3(1), 1–14.
10.
Khan, M. A., & Salah, K. (2018). IoT security: Review, blockchain solutions, and open challenges. Future Generation Computer Systems, 82, 395–411.CrossRef
11.
Dorri, A., Kanhere, S. S., Jurdak, R., & Gauravaram, P. (2017, March). Blockchain for IoT security and privacy: The case study of a smart home. In: 2017 IEEE international conference on pervasive computing and communications workshops (PerCom workshops) (pp. 618–623). IEEE.
12.
Kreutz, D., Ramos, F. M., Verissimo, P. E., Rothenberg, C. E., Azodolmolky, S., & Uhlig, S. (2014). Software-defined networking: A comprehensive survey. Proceedings of the IEEE, 103(1), 14–76.CrossRef
13.
Farhady, H., Lee, H., & Nakao, A. (2015). Software-defined networking: A survey. Computer Networks, 81, 79–95.CrossRef
14.
Kalkan, K., & Zeadally, S. (2017). Securing internet of things with software defined networking. IEEE Communications Magazine, 56(9), 186–192.
15.
Mohammed, A. H., KHALEEFAH, R. M., & Abdulateef, I. A. (2020, June). A Review Software Defined Networking for Internet of Things. In 2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA) (pp. 1–8). IEEE.
16.
Yan, Z., Zhang, P., & Vasilakos, A. V. (2016). A security and trust frameyanwork for virtualized networks and software-defined networking. Security and communication networks, 9(16), 3059–3069.CrossRef
17.
Nofer, M., Gomber, P., Hinz, O., & Schiereck, D. (2017). Blockchain. Business and Information Systems Engineering, 59(3), 183–187.CrossRef
18.
Karame, G. O., & Androulaki, E. (2016). Bitcoin and blockchain security. Artech House.
19.
Mitchell, R. S., Michalski, J. G., & Carbonell, T. M. (2013). An artificial intelligence approach. Springer.
20.
Bao, F., & Chen, I. R. (2012). Dynamic trust management for internet of things applications. In Proceedings of the 2012 international workshop on Self-aware internet of things (pp. 1–6).
21.
Bao, F., & Chen, R. (2012). Trust management for the internet of things and its application to service composition. In: 2012 IEEE international symposium on a world of wireless, mobile and multimedia networks (WoWMoM) (pp. 1–6). IEEE.
22.
Abassi, R., Douss, A. B. C., & Sauveron, D. (2020). TSME: A trust-based security scheme for message exchange in vehicular Ad hoc networks. Human-centric Computing and Information Sciences, 10(1), 1–19.CrossRef
23.
Zhao, Y. L. (2013). Research on data security technology in internet of things. In: Applied Mechanics and Materials (Vol. 433, pp. 1752–1755). Trans Tech Publications Ltd.
24.
Hasan, T., Adnan, A., Giannetsos, T., & Malik, J. (2020). Orchestrating SDN Control Plane towards Enhanced IoT Security. In: 2020 6TH IEEE CONFERENCE ON NETWORK SOFTWARIZATION (NETSOFT) (pp. 457–464). IEEE.
25.
Zhang, Y., Xu, X., Liu, A., Lu, Q., Xu, L., & Tao, F. (2019). Blockchain-based trust mechanism for IoT-based smart manufacturing system. IEEE Transactions on Computational Social Systems, 6(6), 1386–1394.CrossRef
26.
Zennaro, M. (2017). Introduction to the Internet of Things. Telecommunication and ICT4D Lab, The Abdus Salam International Centre for Theoretical Physics Trieste, Italy, pp. 1–48.
27.
Zarca, A. M., Bernabe, J. B., Trapero, R., Rivera, D., Villalobos, J., Skarmeta, A., & Gouvas, P. (2019). Security management architecture for NFV/SDN-aware IoT systems. IEEE Internet of Things Journal, 6(5), 8005–8020.
28.
Hammi, M. T., Bellot, P., & Serhrouchni, A. (2018, April). BCTrust: A decentralized authentication blockchain-based mechanism. In: 2018 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1–6). IEEE.
29.
Hammi, M. T., Hammi, B., Bellot, P., & Serhrouchni, A. (2018). Bubbles of Trust: A decentralized blockchain-based authentication system for IoT. Computers and Security, 78, 126–142.CrossRef
30.
Amangele, P., Reed, M. J., Al-Naday, M., Thomos, N., & Nowak, M. (2019). Hierarchical Machine Learning for IoT Anomaly Detection in SDN. In: 2019 International Conference on Information Technologies (InfoTech) (pp. 1–4). IEEE.
31.
Sharafaldin, I., Lashkari, A. H., & Ghorbani, A. A. (2018). Toward generating a new intrusion detection dataset and intrusion traffic characterization. In ICISSP (pp. 108–116).
32.
Farris, I., Taleb, T., Khettab, Y., & Song, J. (2018). A survey on emerging SDN and NFV security mechanisms for IoT systems. IEEE Communications Surveys and Tutorials, 21(1), 812–837.CrossRef
33.
Mohanta, B. K., Jena, D., Satapathy, U., & Patnaik, S. (2020). Survey on IoT security: challenges and solution using machine learning, artificial intelligence and blockchain technology. Internet of Things, p. 100227.
34.
Alfandi, O., Khanji, S., Ahmad, L., & Khattak, A. (2020). A survey on boosting IoT security and privacy through blockchain. Cluster Computing, pp. 1–19.
35.
Xie, L., Ding, Y., Yang, H., & Wang, X. (2019). Blockchain-based secure and trustworthy Internet of Things in SDN-enabled 5G-VANETs. IEEE Access, 7, 56656–56666.CrossRef
36.
Shu, J., Zhou, L., Zhang, W., Du, X., & Guizani, M. (2020). Collaborative Intrusion Detection for VANETs: A Deep Learning-Based Distributed SDN Approach. IEEE Transactions on Intelligent Transportation Systems.
37.
Khoa, T. V., Saputra, Y. M., Hoang, D. T., Trung, N. L., Nguyen, D., Ha, N. V., & Dutkiewicz, E. (2020, May). Collaborative learning model for cyberattack detection systems in iot industry 4.0. In 2020 IEEE Wireless Communications and Networking Conference (WCNC) (pp. 1–6). IEEE.
38.
Meidan, Y., Bohadana, M., Mathov, Y., Mirsky, Y., Shabtai, A., Breitenbacher, D., & Elovici, Y. (2018). N-baiot—Network-based detection of iot botnet attacks using deep autoencoders. IEEE Pervasive Computing, 17(3), 12–22.CrossRef
39.
Haseeb, K., Ud Din, I., Almogren, A., & Islam, N. (2020). An energy efficient and secure IoT-based WSN framework: An application to smart agriculture. Sensors, 20(7), 2081.ADSCrossRefPubMedPubMedCentral
40.
Awan, K. A., Ud Din, I., Almogren, A., & Almajed, H. (2020). AgriTrust—a trust management approach for smart agriculture in cloud-based internet of agriculture things. Sensors, 20(21), 6174.ADSCrossRefPubMedPubMedCentral
41.
Sengupta, J., Ruj, S., & Bit, S. D. (2020). A secure fog-based architecture for industrial Internet of Things and industry 4.0. IEEE Transactions on Industrial Informatics, 17(4), 2316–2324.
42.
Al-Hamadi, H., & Chen, R. (2017). Trust-based decision making for health IoT systems. IEEE Internet of Things Journal, 4(5), 1408–1419.CrossRef
43.
Abou-Nassar, E. M., Iliyasu, A. M., El-Kafrawy, P. M., Song, O. Y., Bashir, A. K., & Abd El-Latif, A. A. (2020). DITrust chain: Towards blockchain-based trust models for sustainable healthcare IoT systems. IEEE Access, 8, 111223–111238.CrossRef
44.
Han, B., Wong, S., Mannweiler, C., Dohler, M., & Schotten, H. D. (2017, May). Security trust zone in 5G networks. In 2017 24th International Conference on Telecommunications (ICT) (pp. 1–5). IEEE.
45.
Hakiri, A., & Dezfouli, B. (2021, April). Towards a blockchain-sdn architecture for secure and trustworthy 5G massive IoT networks. In: Proceedings of the 2021 ACM International Workshop on Software Defined Networks and Network Function Virtualization Security (pp. 11–18).
46.
Herrera, J. D. J. G., & Vega, J. F. B. (2016). Network functions virtualization: A survey. IEEE Latin America Transactions, 14(2), 983–997.CrossRef
47.
Abbas, N., Zhang, Y., Taherkordi, A., & Skeie, T. (2017). Mobile edge computing: A survey. IEEE Internet of Things Journal, 5(1), 450–465.CrossRef
48.
49.
Wang, L., Von Laszewski, G., Younge, A., He, X., Kunze, M., Tao, J., & Fu, C. (2010). Cloud computing: A perspective study. New generation computing, 28(2), 137–146.CrossRef
50.
Bonomi, F., Milito, R., Zhu, J., & Addepalli, S. (2012, August). Fog computing and its role in the internet of things. In: Proceedings of the first edition of the MCC workshop on Mobile cloud computing (pp. 13–16).
51.
Vaquero, L. M., & Rodero-Merino, L. (2014). Finding your way in the fog: Towards a comprehensive definition of fog computing. ACM SIGCOMM Computer Communication Review, 44(5), 27–32.CrossRef
52.
Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks, 38(4), 393–422.CrossRef
53.
Minh, D., Wang, H. X., Li, Y. F., & Nguyen, T. N. (2022). Explainable artificial intelligence: a comprehensive review. Artificial Intelligence Review, pp. 1–66.
54.
Jovanov, E., Milenkovic, A., Otto, C., & De Groen, P. C. (2005). A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation. Journal of NeuroEngineering and Rehabilitation, 2(1), 1–10.CrossRef
55.
Kumar, M., & Chand, S. (2020). A lightweight cloud-assisted identity-based anonymous authentication and key agreement protocol for secure wireless body area network. IEEE Systems Journal, 15(2), 2779–2786.ADSCrossRef
56.
Fang, W., Cui, N., Chen, W., Zhang, W., & Chen, Y. (2020). A trust-based security system for data collection in smart city. IEEE Transactions on Industrial Informatics, 17(6), 4131–4140.CrossRef
57.
Singh, S. K., Jeong, Y. S., & Park, J. H. (2020). A deep learning-based IoT-oriented infrastructure for secure smart city. Sustainable Cities and Society, 60, 102252.CrossRef
58.
Cao, B., Wang, X., Zhang, W., Song, H., & Lv, Z. (2020). A many-objective optimization model of industrial internet of things based on private blockchain. IEEE Network, 34(5), 78–83.CrossRef
59.
Crosby, M., Pattanayak, P., Verma, S., & Kalyanaraman, V. (2016). Blockchain technology: Beyond bitcoin. Applied Innovation, 2(6–10), 71.
60.
Neshenko, N., Bou-Harb, E., Crichigno, J., Kaddoum, G., & Ghani, N. (2019). Demystifying IoT security: An exhaustive survey on IoT vulnerabilities and a first empirical look on Internet-scale IoT exploitations. IEEE Communications Surveys and Tutorials, 21(3), 2702–2733.CrossRef
61.
Zaman, S., Kaiser, M. S., Khan, R. T., & Mahmud, M. (2020, December). Towards SDN and Blockchain based IoT Countermeasures: A Survey. In: 2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI) (pp. 1–6). IEEE
62.
Li, W., Meng, W., Liu, Z., & Au, M. H. (2020). Towards blockchain-based software-defined networking: Security challenges and solutions. IEICE Transactions on Information and Systems, 103(2), 196–203.ADSCrossRef
63.
Iqbal, W., Abbas, H., Daneshmand, M., Rauf, B., & Bangash, Y. A. (2020). An in-depth analysis of IoT security requirements, challenges, and their countermeasures via software-defined security. IEEE Internet of Things Journal, 7(10), 10250–10276.CrossRef
64.
Zhang, C., & Lu, Y. (2021). Study on artificial intelligence: The state of the art and future prospects. Journal of Industrial Information Integration, 23, 100224.CrossRef
65.
Thiebes, S., Lins, S., & Sunyaev, A. (2021). Trustworthy artificial intelligence. Electronic Markets, 31, 447–464.CrossRef
66.
Janiesch, C., Zschech, P., & Heinrich, K. (2021). Machine learning and deep learning. Electronic Markets, 31(3), 685–695.CrossRef
67.
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT press.
68.
Borisov, V., Leemann, T., Seßler, K., Haug, J., Pawelczyk, M., & Kasneci, G. (2022). Deep neural networks and tabular data: A survey. IEEE Transactions on Neural Networks and Learning Systems.
69.
Behera, R. K., Bala, P. K., & Dhir, A. (2019). The emerging role of cognitive computing in healthcare: A systematic literature review. International journal of medical informatics, 129, 154–166.CrossRefPubMed
70.
Qiu, X., Sun, T., Xu, Y., Shao, Y., Dai, N., & Huang, X. (2020). Pre-trained models for natural language processing: A survey. Science China Technological Sciences, 63(10), 1872–1897.ADSCrossRef
71.
Rafique, W., Qi, L., Yaqoob, I., Imran, M., Rasool, R. U., & Dou, W. (2020). Complementing IoT services through software defined networking and edge computing: A comprehensive survey. IEEE Communications Surveys and Tutorials, 22(3), 1761–1804.CrossRef
72.
Bekri, W., Jmal, R., & Chaari Fourati, L. (2020). Internet of things management based on software defined networking: A survey. International Journal of Wireless Information Networks, 27, 385–410.CrossRef
73.
Sheikh, M. N. A., Halder, M., Kabir, S. S., Miah, M. W., & Khatun, S. (2019). SDN-Based approach to evaluate the best controller: Internal controller NOX and external controllers POX, ONOS, RYU. Global Journal of Computer Science and Technology, 19(1), 21–32.CrossRef
74.
Mishra, A., Gupta, N., & Gupta, B. B. (2021). Defense mechanisms against DDoS attack based on entropy in SDN-cloud using POX controller. Telecommunication systems, 77, 47–62.CrossRef
75.
Bholebawa, I. Z., & Dalal, U. D. (2018). Performance analysis of SDN/ OpenFlow controllers: POX versus foodlight. Wireless Personal Communications, 98(2), 1679–1699.CrossRef
76.
Eljack, A. H., Hassan, A. H. M., & Elamin, H. H. (2019, September). Performance Analysis of ONOS and Floodlight SDN Controllers based on TCP and UDP Traffic. In: 2019 International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE) (pp. 1–6). IEEE.
77.
Zhang, Y., He, Q., Chen, G., Zhang, X., & Xiang, Y. (2019). A low-overhead, confidentiality-assured, and authenticated data acquisition framework for IoT. IEEE Transactions on Industrial Informatics, 16(12), 7566–7578.CrossRef
78.
Valea, E., Da Silva, M., Flottes, M. L., Di Natale, G., Dupuis, S., & Rouzeyre, B. (2019, April). Providing confidentiality and integrity in ultra low power iot devices. In: 2019 14th International Conference on Design and Technology of Integrated Systems In Nanoscale Era (DTIS) (pp. 1–6). IEEE.
79.
Fadi, A. T., & Deebak, B. D. (2020). Seamless authentication: For IoT-big data technologies in smart industrial application systems. IEEE Transactions on Industrial Informatics, 17(4), 2919–2927.
80.
Zhao, Q., Chen, S., Liu, Z., Baker, T., & Zhang, Y. (2020). Blockchain-based privacy-preserving remote data integrity checking scheme for IoT information systems. Information Processing and Management, 57(6), 102355.CrossRef
81.
López-Peña, M. A., Díaz, J., Pérez, J. E., & Humanes, H. (2020). DevOps for IoT systems: Fast and continuous monitoring feedback of system availability. IEEE Internet of Things Journal, 7(10), 10695–10707.CrossRef
82.
Amini, M. R., & Baidas, M. W. (2020). Availability-Reliability-Stability trade-offs in ultra-reliable energy-harvesting cognitive radio IoT networks. IEEE Access, 8, 82890–82916.CrossRef
83.
Song, K., Zhang, J., Ji, Z., Jiang, J., & Li, C. (2020). Energy-efficiency for IoT system with cache-enabled fixed-wing UAV relay. IEEE Access, 8, 117503–117512.CrossRef
84.
Metallidou, C. K., Psannis, K. E., & Egyptiadou, E. A. (2020). Energy efficiency in smart buildings: IoT approaches. IEEE Access, 8, 63679–63699.CrossRef
85.
Li, J., Cai, J., Khan, F., Rehman, A. U., Balasubramaniam, V., Sun, J., & Venu, P. (2020). A secured framework for sdn-based edge computing in IOT-enabled healthcare system. IEEE Access, 8, 135479–135490.CrossRef
86.
Prabavathy, S., & Supriya, V. (2021, August). SDN based Cognitive Security System for Large-Scale Internet of Things using Fog Computing. In: 2021 International Conference on Emerging Techniques in Computational Intelligence (ICETCI) (pp. 129–134). IEEE.
87.
88.
Grammatikis, P. R., Sarigiannidis, P., Dalamagkas, C., Spyridis, Y., Lagkas, T., Efstathopoulos, G., & Arce, A. (2021). SDN-Based Resilient Smart Grid: The SDN-microSENSE Architecture. Digital, 1(4), 173–187.
89.
Ortiz, J., Sanchez-Iborra, R., Bernabe, J. B., Skarmeta, A., Benzaid, C., Taleb, T., & Lopez, D. (2020). INSPIRE-5Gplus: intelligent security and pervasive trust for 5G and beyond networks. In: Proceedings of the 15th International Conference on Availability, Reliability and Security (pp. 1–10).
90.
91.
92.
93.
94.
95.
96.
97.
98.
Da Xu, L., Lu, Y., & Li, L. (2021). Embedding blockchain technology into IoT for security: a survey. IEEE Internet of Things Journal.
99.
Sharma, V., You, I., Andersson, K., Palmieri, F., Rehmani, M. H., & Lim, J. (2020). Security, privacy and trust for smart mobile-Internet of Things (M-IoT): A survey. IEEE Access, 8, 167123–167163.CrossRef
100.
Liao, Z., Pang, X., Zhang, J., Xiong, B., & Wang, J. (2021). Blockchain on Security and Forensics management in edge computing for IoT: a comprehensive survey. IEEE Transactions on Network and Service Management.
101.
Mbarek, B., Ge, M., & Pitner, T. (2021). Trust-based authentication for smart home systems. Wireless Personal Communications, 117(3), 2157–2172.CrossRef
102.
Naija, Y., Beroulle, V., & Machhout, M. (2018). Security enhancements of a mutual authentication protocol used in a HF full-fledged RFID tag. Journal of Electronic Testing, 34(3), 291–304.CrossRef
103.
Babiker Mohamed, M., Matthew Alofe, O., Ajmal Azad, M., Singh Lallie, H., Fatema, K., & Sharif, T. (10). A comprehensive survey on secure software‐defined network for the Internet of Things. Transactions on Emerging Telecommunications Technologies, e4391.
104.
Gopalan, S. S., Raza, A., & Almobaideen, W. (2021, March). IoT Security in Healthcare using AI: A Survey. In: 2020 International Conference on Communications, Signal Processing, and their Applications (ICCSPA) (pp. 1–6). IEEE.
105.
Ferreira, J. C., Teixeira, D., & Macedo, J. (2021). Systematic literature review of AI/ML in software-defined networks using the snowballing approach.
106.
Nawir, M., Amir, A., Yaakob, N., & Lynn, O. B. (2016). Internet of Things (IoT): Taxonomy of security attacks. In: 2016 3rd international conference on electronic design (ICED) (pp. 321–326). IEEE.
107.
Zhang, Z. K., Cho, M. C. Y., Wang, C. W., Hsu, C. W., Chen, C. K., & Shieh, S. (2014, November). IoT security: ongoing challenges and research opportunities. In: 2014 IEEE 7th international conference on service-oriented computing and applications (pp. 230–234). IEEE.
108.
Zhang, J., Chen, H., Gong, L., Cao, J., & Gu, Z. (2019). The current research of IoT security. In: 2019 IEEE Fourth International Conference on Data Science in Cyberspace (DSC) (pp. 346–353). IEEE.
109.
Attkan, A., & Ranga, V. (2022). Cyber-physical security for IoT networks: a comprehensive review on traditional, blockchain and artificial intelligence based key-security. Complex and Intelligent Systems, pp. 1–33.
110.
Zaman, S., Alhazmi, K., Aseeri, M. A., Ahmed, M. R., Khan, R. T., Kaiser, M. S., & Mahmud, M. (2021). Security threats and artificial intelligence based countermeasures for internet of things networks: A comprehensive survey. Ieee Access, 9, 94668–94690.CrossRef
111.
Gebremariam, A. A., Usman, M., & Qaraqe, M. (2019, March). Applications of artificial intelligence and machine learning in the area of SDN and NFV: A survey. In: 2019 16th International Multi-Conference on Systems, Signals and Devices (SSD) (pp. 545–549). IEEE.
112.
Flauzac, O., González, C., Hachani, A., & Nolot, F. (2015, March). SDN based architecture for IoT and improvement of the security. In: 2015 IEEE 29th international conference on advanced information networking and applications workshops (pp. 688–693). IEEE.
113.
Sambandam, N., Hussein, M., Siddiqi, N., & Lung, C. H. (2018). Network security for iot using sdn: Timely ddos detection. In: 2018 IEEE Conference on Dependable and Secure Computing (DSC) (pp. 1–2). IEEE.
114.
Ghazal, T. M. (2021). Internet of things with artificial intelligence for health care security. Arabian Journal for Science and Engineering, pp. 1–12.
115.
Fang, W., Chen, W., Zhang, W., Pei, J., Gao, W., & Wang, G. (2020). Digital signature scheme for information non-repudiation in blockchain: A state of the art review. EURASIP Journal on Wireless Communications and Networking, 2020(1), 1–15.CrossRef
116.
Bekri, W., Layeb, T., Rihab, J. M. A. L., & Fourati, L. C. (2022, May). Intelligent IoT Systems: Security issues, attacks, and countermeasures. In: 2022 International Wireless Communications and Mobile Computing (IWCMC) (pp. 231–236). IEEE.
117.
Rahouti, M., Xiong, K., Xin, Y., Jagatheesaperumal, S. K., Ayyash, M., & Shaheed, M. (2022). SDN security review: Threat taxonomy, implications, and open challenges. IEEE Access, 10, 45820–45854.CrossRef
Metadata
Title
Secure and trustworthiness IoT systems: investigations and literature review
Authors
Wiem Bekri
Rihab Jmal
Lamia Chaari Fourati
Publication date
23-01-2024
Publisher
Springer US
Published in
Telecommunication Systems / Issue 3/2024
Print ISSN: 1018-4864
Electronic ISSN: 1572-9451
DOI
https://doi.org/10.1007/s11235-023-01089-z

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