Real number signal processing can detect denial-of-service attacks
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
Wireless communication systems are inherently vulnerable to adversarial attacks since malevolent jammers might jam and disrupt the legitimate transmission intentionally. Of particular interest are so-called denial-of-service (DoS) attacks in which the jammer is able to completely disrupt the communication. Accordingly, it is of crucial interest for the legitimate users to detect such DoS attacks. Turing machines provide the fundamental limits of today's digital computers and therewith of the traditional signal processing. It has been shown that these are incapable of detecting DoS attacks. This stimulates the question of how powerful the signal processing must be to enable the detection of DoS attacks. This paper investigates the general computation framework of Blum-Shub-Smale machines which allows the processing and storage of arbitrary reals. It is shown that such real number signal processing then enables the detection of DoS attacks.
Details
Original language | English |
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Title of host publication | ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
Pages | 4765-4769 |
Number of pages | 5 |
ISBN (electronic) | 978-1-7281-7605-5 |
Publication status | Published - 2021 |
Peer-reviewed | Yes |
Externally published | Yes |
Publication series
Series | International Conference on Acoustics, Speech, and Signal Processing (ICASSP) |
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ISSN | 1520-6149 |
Conference
Title | 2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 |
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Duration | 6 - 11 June 2021 |
City | Virtual, Toronto |
Country | Canada |
External IDs
ORCID | /0000-0002-1702-9075/work/165878306 |
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Keywords
ASJC Scopus subject areas
Keywords
- Algorithmic detection, Blum-Shub-Smale machine, Denial-of-service attack, Real number signal processing