![]() Msadek, Mohamed Nizar ![]() ![]() ![]() in The IEEE Wireless Communications and Networking Conference (WCNC) (2019, April 19) Even in the face of strong encryption, the spectacular Internet of Things (IoT) penetration across sectors such as e-health, energy, transportation, and entertainment is expanding the attack surface ... [more ▼] Even in the face of strong encryption, the spectacular Internet of Things (IoT) penetration across sectors such as e-health, energy, transportation, and entertainment is expanding the attack surface, which can seriously harm users’ privacy. We demonstrate in this paper that an attacker is able to disclose sensitive information about the IoT device, such as its type,by identifying specific patterns in IoT traffic. To perform the fingerprint attack, we train machine-learning algorithms based on selected features extracted from the encrypted IoT traffic.Extensive simulations involving the baseline approach show that we achieve not only a significant mean accuracy improvement of 18.5% and but also a speedup of 18.39 times for finding the best estimators. Obtained results should spur the attention of policymakers and IoT vendors to secure the IoT devices they bring to market. [less ▲] Detailed reference viewed: 638 (14 UL)![]() Msadek, Mohamed Nizar ![]() ![]() ![]() in International Conference on Smart Applications, Communications and Networking (SmartNets) (2018, November) The Internet of Things (IoT) encompasses many aspects of our daily life, from connected homes and cities through connected vehicles and roads to devices that collaborate independently to achieve a ... [more ▼] The Internet of Things (IoT) encompasses many aspects of our daily life, from connected homes and cities through connected vehicles and roads to devices that collaborate independently to achieve a specific purpose. Being an example of a largescale self-organizing systems, the IoT should present imperative properties such as autonomy and trustworthiness. However, compared to classical self-organizing systems, IoT has intrinsic characteristics (wide deployment, resource constraints, uncertain environment, etc.) that open up several security challenges. These challenges cannot be solved by existing Autonomic and Organic Computing techniques and therefore new techniques adapted to self-organizing IoT, (that we call Self-IoT) peculiarities are needed. To this end, this paper studies related work in the area of self-organizing IoT, identifies and describes the key research challenges for trustworthy secure Self-IoT and proposes new and tailored existing solutions. [less ▲] Detailed reference viewed: 319 (21 UL) |
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