{"title":"Language-based opacity in modular discrete event systems: Compositional secret-based verification using labeled petri nets","authors":"Salwa Habbachi , Imen Ben Hafaiedh , Zhiwu Li","doi":"10.1016/j.ins.2025.122701","DOIUrl":null,"url":null,"abstract":"<div><div>This work focuses on verifying language-based opacity within modular discrete-event systems. We consider a distributed system that is modeled as a composition of multiple interacting modules, each modeled by a labeled Petri net. Ensuring confidentiality in such systems is critical for cyber-physical systems and industrial networks, where unauthorized inference of sensitive data can lead to security breaches. We introduce a new definition of language-based opacity for modular systems and propose three secret-based verification methods that avoid the construction of the monolithic system through parallel composition. Our approach includes three methods: (1) global secret verification via observer synchronization; (2) local, module-level secret verification; and (3) an iterative composition optimization that avoids building the entire modular system, yielding significant computational savings. Experimental results on a benchmark smart manufacturing system demonstrate the practical efficiency of our approach, showing orders-of-magnitude improvement in verification time and memory usage over traditional monolithic approaches.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"724 ","pages":"Article 122701"},"PeriodicalIF":6.8000,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Sciences","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0020025525008345","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
This work focuses on verifying language-based opacity within modular discrete-event systems. We consider a distributed system that is modeled as a composition of multiple interacting modules, each modeled by a labeled Petri net. Ensuring confidentiality in such systems is critical for cyber-physical systems and industrial networks, where unauthorized inference of sensitive data can lead to security breaches. We introduce a new definition of language-based opacity for modular systems and propose three secret-based verification methods that avoid the construction of the monolithic system through parallel composition. Our approach includes three methods: (1) global secret verification via observer synchronization; (2) local, module-level secret verification; and (3) an iterative composition optimization that avoids building the entire modular system, yielding significant computational savings. Experimental results on a benchmark smart manufacturing system demonstrate the practical efficiency of our approach, showing orders-of-magnitude improvement in verification time and memory usage over traditional monolithic approaches.
期刊介绍:
Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions.
Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.