Title

Cyber Attacks on Estimation Sensor Networks and Iots: Impact, Mitigation and Implications to Unattacked Systems

Abstract

Estimation of an unknown deterministic vector from quantized sensor data is considered in the presence of spoofing and man-in-the-middle attacks. First, asymptotically optimum processing, which identifies and categorizes the attacked sensors into different groups according to distinct types of attacks, is outlined in the face of man-in-the-middle attacks. Necessary and sufficient conditions are provided under which utilizing the attacked sensor data will lead to better estimation performance when compared to approaches where the attacked sensors are ignored. Next, necessary and sufficient conditions are provided under which spoofing attacks provide a guaranteed attack performance in terms of the Cramer-Rao Bound regardless of the processing the estimation system employs. It is shown that it is always possible to construct such a highly desirable attack by properly employing an attack vector parameter having a sufficiently large dimension relative to the number of quantization levels employed, which was not observed previously. For unattacked quantized estimation systems, a general limitation on the dimension of a vector parameter which can be accurately estimated is uncovered.

Meeting Name

2017 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP (2017: Mar. 5-9, New Orleans, LA)

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

Cramer-Rao Bound; Distributed Parameter Estimation; Man-In-The-Middle Attack; Sensor Network; Spoofing Attack

International Standard Book Number (ISBN)

978-150904117-6

International Standard Serial Number (ISSN)

1520-6149

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2017 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Share

 
COinS