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Volumn 12, Issue 6, 2014, Pages 40-47

Detecting industrial control malware using automated PLC code analytics

Author keywords

formal models; industrial control malware; model checking; PLC code analytics; process control systems; reverse engineering; safety critical code; security

Indexed keywords

ACCIDENT PREVENTION; CODES (SYMBOLS); COMPUTER CRIME; CONTROL THEORY; DYNAMICAL SYSTEMS; MALWARE; MODEL CHECKING; PROCESS CONTROL; REVERSE ENGINEERING;

EID: 84921416016     PISSN: 15407993     EISSN: None     Source Type: Journal    
DOI: 10.1109/MSP.2014.113     Document Type: Article
Times cited : (76)

References (11)
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  • 4
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    • Using symbolic execution for verifying safety-critical systems
    • A. Coen-Porisini et al., "Using Symbolic Execution for Verifying Safety-Critical Systems," ACM SIGSOFT Software Engineering Notes, vol. 26, no. 5, 2001, pp. 142-151.
    • (2001) ACM SIGSOFT Software Engineering Notes , vol.26 , Issue.5 , pp. 142-151
    • Coen-Porisini, A.1
  • 8
    • 84921332020 scopus 로고    scopus 로고
    • Breakage
    • J. Larsen, "Breakage," Black Hat Federal, 2008; www.blackhat.com/presentations/bh-dc-08/Larsen/Presentation/bh-dc-08-larsen.pdf.
    • (2008) Black Hat Federal
    • Larsen, J.1
  • 10
    • 84857186552 scopus 로고    scopus 로고
    • Anomaly detection via statistical learning in industrial communication networks
    • J. Rrushi, "Anomaly Detection via Statistical Learning in Industrial Communication Networks," Int'l J. Information and Computer Security, vol. 4, no. 4, 2011, pp. 295-315.
    • (2011) Int'l J. Information and Computer Security , vol.4 , Issue.4 , pp. 295-315
    • Rrushi, J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.