The Internet of Things (IoT) is expected to connect billions of devices, that will interact with their physical environment through sensors or actuators. The measurements created from these sensors have varying levels of precision, leading to measurements that follow a distribution, whose variance presents an additional challenge for the employed security schemes. In this work we assume a smart attacker would attempt to mask his attack in the inherent uncertainty of the measurements, and attempt to manipulate the distribution of measurements as covertly as possible to affect the final meaningful value that the system would result in. We employ Game Theory to examine the best strategies to slowly corrupt the integrity of an IoT network, similar to ETSI's Low Throughput Networks (LTN). We examine the extent of the changes that can be made to the distribution without assuming a priori knowledge of it by the attacker, for different scenarios and compromisation patterns. To the best of our knowledge this is the first attempt to examine the limits of the compromise that could be applied by a smart attacker on an IoT/LTN-type network without triggering outlier-alarms, and can be applied in the design of better targeted defensive measures.
|Title of host publication||2016 IEEE Global Communications Conference (GLOBECOM 2016)|
|Subtitle of host publication||Proceedings of a meeting held 4-8 December 2016, Washington, DC, USA|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Number of pages||6|
|Publication status||Published - May 2017|
- Game Theory
- hellinger distance