Parameter identification of FIR systems with binary-valued observations: when the event-driven communication mechanism encounters DoS attacks

Jiahua Fan, Ruizhe Jia, Kun Zhang and Jin Guo

International Journal of Systems Science, 2025, vol. 56, issue 13, 3156-3176

Abstract: With the development of technology, finite impulse response(FIR) is widely used in signal processing, communication and other fields, so it is of great significance to study its parameter identification problem. In the communication process of FIR systems, denial-of-service(DoS) attacks cause data packet loss, and the introduction of event-driven communication mechanism can reduce the sensitivity of the system to DoS attacks, however, the coupling of the two increases the difficulty of parameter identification. In this paper, we explore the problem of FIR parameter identification in the presence of DoS attacks and event-driven communication from the perspective of the defense side. Initially, the inadequacy of the original identification algorithm in estimating parameters during attacks is acknowledged. Compared to the original algorithm, the improved algorithm incorporates parameters of a model based on DoS attacks and analyzes its convergence performance. Subsequently, the trace of the asymptotic normal variance matrix of the improved identification algorithm is utilised as a metric to gauge the attack's effectiveness, leading to the design of an optimal attack strategy. Building upon the enhanced identification algorithm, adjustments are made to the event-driven mechanism, and an adaptive identification algorithm is formulated. The convergence performance of this algorithm is analysed, followed by the calculation of a communication rate aimed at optimisation based on selected indicators. Lastly, the paper concludes with an examination of the correctness and validity of the findings through numerical simulation.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2025.2469814 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tsysxx:v:56:y:2025:i:13:p:3156-3176

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20

DOI: 10.1080/00207721.2025.2469814

Access Statistics for this article

International Journal of Systems Science is currently edited by Visakan Kadirkamanathan

More articles in International Journal of Systems Science from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().