Per Packet Flow Anonymization in 6LoWPAN IoT Networks

Kouachi, Asma Iman; Sahraoui, Somia; Bachir, Abdelmalik

doi:10.1109/wincom.2018.8629719

Cited by 6 publications

(1 citation statement)

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“…This work limited the time available to an attacker performing reconnaissance attacks and provided power consumption analysis to prove the efficacy of their micro MTD mechanism. [13] proposed an MTD technique to provide anonymization of packet flow for IoT devices. They looked into privacy issues caused by tracking and communicationflow identification in current low power solutions.…”

Section: Mtd and Defensive Deception Techniques For Iotmentioning

confidence: 99%

Proactive Defense for Internet-of-Things: Integrating Moving Target Defense with Cyberdeception

Ge,

Cho,

Kim

et al. 2020

Preprint

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Resource constrained Internet-of-Things (IoT) devices are highly likely to be compromised by attackers because strong security protections may not be suitable to be deployed. This requires an alternative approach to protect vulnerable components in IoT networks. In this paper, we propose an integrated defense technique to achieve intrusion prevention by leveraging cyberdeception (i.e., a decoy system) and moving target defense (i.e., network topology shuffling). We verify the effectiveness and efficiency of our proposed technique analytically based on a graphical security model in a software defined networking (SDN)based IoT network. We develop four strategies (i.e., fixed/random and adaptive/hybrid) to address "when" to perform network topology shuffling and three strategies (i.e., genetic algorithm/decoy attack pathbased optimization/random) to address "how" to perform network topology shuffling on a decoy-populated IoT network, and analyze which strategy can best achieve a system goal such as prolonging the system lifetime, maximizing deception effectiveness, maximizing service availability, or minimizing defense cost. Our results demonstrate that a software defined IoT network running our intrusion prevention technique at the optimal parameter setting prolongs system lifetime, increases attack complexity of compromising critical nodes, and maintains superior service availability compared with a counterpart IoT network without running our intrusion prevention technique. Further, when given a single goal or a multi-objective goal (e.g., maximizing the system lifetime and service availability while minimizing the defense cost) as input, the best combination of "when" and "how" strategies is identified for executing our proposed technique under which the specified goal can be best achieved.

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Section: Mtd and Defensive Deception Techniques For Iotmentioning

confidence: 99%