Cyber-Attack Detection in Socio-Technical Transportation Systems Exploiting Redundancies Between Physical and Social Data

Tanushree Roy, Sara Sattarzadeh, Satadru Dey

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Cyber-physical-social connectivity is a key element in intelligent transportation systems (ITSs) due to the ever-increasing interaction between human users and technological systems. Such connectivity translates the ITSs into dynamical systems of socio-technical nature. Exploiting this socio-technical feature to our advantage, we propose a cyber-attack detection scheme for ITSs that focuses on cyber-attacks on freeway traffic infrastructure. The proposed scheme combines two parallel macroscopic traffic model-based partial differential equation (PDE) filters whose output residuals are compared to make decision on attack occurrences. One of the filters utilizes physical (vehicle/infrastructure) sensor data as feedback whereas the other utilizes social data from human users' mobile devices as feedback. The Social Data-based Filter is aided by a fake data isolator and a social signal processor that translates the social information into usable feedback signals. Mathematical convergence properties are analyzed for the filters using Lyapunov's stability theory. Finally, we validate our proposed scheme by presenting simulation results.

Original languageEnglish (US)
Pages (from-to)1477-1488
Number of pages12
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume54
Issue number3
DOIs
StatePublished - Mar 1 2024

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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