MAC-Layer Traffic Shaping Defense Against WiFi Device Fingerprinting Attacks

Mnassar Alyami, Mohammed Alkhowaiter, Mansour Al Ghanim, Cliff Zou, Yan Solihin

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

7 Scopus citations

Abstract

WiFi networks are vulnerable to statistical traffic analysis attacks, even when a WiFi network is securely encrypted and the attacker is unable to join the network. Many defenses proposed in the literature are inefficient to deal with profiling attacks against WiFi-based Internet-of-Things (IoT) devices, because they burden the Internet traffic with high bandwidth overhead and pose deliberate delay on packet transmission. In this paper, we propose a new MAC-layer packet injection technique where injected dummy packets only exist within the WiFi link between IoT devices and their connected WiFi access point. This traffic shaping defense is effective against data-link device profiling attacks without adding any Internet-side overhead or time delay in legitimate traffic. We evaluated our approach on four WiFi-based IoT devices against a recent privacy attack, and showed the reduction of attack classification accuracy from the original 100% to 54%, close to random guessing..

Original languageEnglish
Title of host publication2022 IEEE Symposium on Computers and Communications, ISCC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665497923
DOIs
StatePublished - 2022
Externally publishedYes
Event27th IEEE Symposium on Computers and Communications, ISCC 2022 - Rhodes, Greece
Duration: 30 Jun 20223 Jul 2022

Publication series

NameProceedings - IEEE Symposium on Computers and Communications
Volume2022-June
ISSN (Print)1530-1346

Conference

Conference27th IEEE Symposium on Computers and Communications, ISCC 2022
Country/TerritoryGreece
CityRhodes
Period30/06/223/07/22

Keywords

  • Device Fingerprinting
  • IoT Privacy
  • Traffic Analysis Countermeasure

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