Internet of Things: Security vulnerabilities and challenges

By Ioannis Andrea, Chrysostomos Chrysostomou, George C. Hadjichristofi. International Symposium on Computers and Communications, 2015

435 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Signal Processing

View Paper: https://www.semanticscholar.org/paper/67e3aece58a89d257b9e924af951d8e36fd2b07f

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In Signal Processing

Citations in the corpus

Security attacks in IoT: A survey (2017, background): “The architecture of IoT is explained in detail in [4] [5] [6].”
A Survey on Security and Privacy Issues in Internet-of-Things (2017, background): “[13] come up with a new classification of IoT devices attacks presented in four distinct types: 1) physical;”
A Survey on Emerging SDN and NFV Security Mechanisms for IoT Systems (2019, background): “1) Malicious Virus/Worm: IoT applications can be severely damaged through malicious viruses and worms, which can allow data leakage and compromise the correct behaviour of cyber-physical systems [75].”
A Survey on Internet of Things: Architecture, Enabling Technologies, Security and Privacy, and Applications (2017, methodology): “Nonetheless, as a large number of RFID-based devices are integrated in IoT, and most of the RFID tags lack proper authentication mechanisms, RFID tags can be accessed and the information stored in tags can be obtained, modiﬁed, and deleted by the adversary [8], [60].”
Machine Learning in IoT Security: Current Solutions and Future Challenges (2019, background): “This attack is referred to as sleep deprivation attack [59].”
IoT Security Techniques Based on Machine Learning: How Do IoT Devices Use AI to Enhance Security? (2018, background): “■ DoS attackers: The attackers flood the target server with superfluous requests to prevent IoT devices from obtaining services [4].”
Classifying IoT Devices in Smart Environments Using Network Traffic Characteristics (2019, background): “It is widely known that IoT devices are by their nature and design easy to inﬁltrate [7], [8], [9], [10], [11], [12].”
A Supervised Intrusion Detection System for Smart Home IoT Devices (2019, background): “1) DoS: Aims to make IoT devices unavailable to its intended users by temporarily or indefinitely disrupting their services [43].”
Machine Learning Based Solutions for Security of Internet of Things (IoT): A Survey (2020, background): “This makes it hard to di ﬀ erentiate be-tween the normal tra ﬃ c and attack tra ﬃ c [43].”