Protecting IoT-environments against Traffic Analysis Attacks with Traffic Morphing

Ibbad Hafeez, Markku Antikainen, Sasu Tarkoma

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

Traffic analysis attacks allow an attacker to infer sensitive information about users by analyzing network traffic of user devices. These attacks are passive in nature and are difficult to detect. In this paper, we demonstrate that an adversary, with access to upstream traffic from a smart home network, can identify the device types and user interactions with IoT devices, with significant confidence. These attacks are practical even when device traffic is encrypted because they only utilize statistical properties, such as traffic rates, for analysis. In order to mitigate the privacy implications of traffic analysis attacks, we propose a traffic morphing technique, which shapes network traffic thus making it more difficult to identify IoT devices and their activities. Our evaluation shows that the proposed technique provides protection against traffic analysis attacks and prevent privacy leakages for smart home users.
Original languageEnglish
Title of host publication2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)
Number of pages6
PublisherIEEE
Publication date6 Jun 2019
Pages196-201
ISBN (Print)978-1-5386-9152-6
ISBN (Electronic)978-1-5386-9151-9, 978-1-5386-9150-2
DOIs
Publication statusPublished - 6 Jun 2019
MoE publication typeA4 Article in conference proceedings
Event2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops): 2nd International Workshop on Context-Awareness for ​Multi-Device Pervasive and Mobile Computing - Kyoto, Kyoto, Japan
Duration: 11 Mar 201915 Mar 2019
Conference number: 2
http://pds.cs.helsinki.fi/percrowd/

Fields of Science

  • 113 Computer and information sciences

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