NDLI: Using Channel State Information for Tamper Detection in the Internet of Things

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Using Channel State Information for Tamper Detection in the Internet of Things

Content Provider	ACM Digital Library
Author	Schulz, Matthias Roedig, Utz Hollick, Matthias Bagci, Ibrahim Ethem Martinovic, Ivan
Abstract	The Internet of Things (IoT) is increasingly used for critical applications and securing the IoT has become a major concern. Among other issues it is important to ensure that tampering with IoT devices is detected. Many IoT devices use WiFi for communication and Channel State Information (CSI) based tamper detection is a valid option. Each 802.11n WiFi frame contains a preamble which allows a receiver to estimate the impact of the wireless channel, the transmitter and the receiver on the signal. The estimation result - the CSI - is used by a receiver to extract the transmitted information. However, as the CSI depends on the communication environment and the transmitter hardware, it can be used as well for security purposes. If an attacker tampers with a transmitter it will have an effect on the CSI measured at a receiver. Unfortunately not only tamper events lead to CSI fluctuations; movement of people in the communication environment has an impact too. We propose to analyse CSI values of a transmission simultaneously at multiple receivers to improve distinction of tamper and movement events. A moving person is expected to have an impact on some but not all communication links between transmitter and the receivers. A tamper event impacts on all links between transmitter and the receivers. The paper describes the necessary algorithms for the proposed tamper detection method. In particular we analyse the tamper detection capability in practical deployments with varying intensity of people movement. In our experiments the proposed system deployed in a busy office environment was capable to detect 53% of tamper events (TPR = 53%) while creating zero false alarms (FPR = 0%).
Starting Page	131
Ending Page	140
Page Count	10
File Format	PDF
ISBN	9781450336826
DOI	10.1145/2818000.2818028
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-12-07
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Phy Wireless 802.11n Ofdm Tamper detection Security Channel state information
Content Type	Text
Resource Type	Article

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