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Communication Dans Un Congrès Année : 2019

Passive Inference of User Actions through IoT Gateway Encrypted Traffic Analysis

Résumé

Internet of Things (IoT) devices become widely used and their control is often provided through a cloud-based web service that interacts with an IoT gateway, in particular for individual users and home automation. In this paper, we propose a technique to infer private user information, i.e., actions performed, by considering a vantage point outside the end-user local IoT network. By learning the relationships between the user actions and the traffic sent by the web service to the gateway, we have been able to establish elementary signatures, one for each possible action, which can be then composed to discover compound actions in encrypted traffic. We evaluated the efficiency of our approach on one IoT gateway interacting with up to 16 IoT devices and showed that a passive attacker can infer user activities with an accuracy above 90%.
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Dates et versions

hal-02331783 , version 1 (24-10-2019)

Identifiants

  • HAL Id : hal-02331783 , version 1

Citer

Pierre-Marie Junges, Jerome Francois, Olivier Festor. Passive Inference of User Actions through IoT Gateway Encrypted Traffic Analysis. IM 2019 - The 16th IFIP/IEEE Symposium on Integrated Network and Service Management, Apr 2019, Washington DC, United States. ⟨hal-02331783⟩
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