메뉴 건너뛰기




Volumn , Issue , 2013, Pages 1338-1341

Android malware detection technology based on improved Bayesian classification

Author keywords

Android malware; Machine learning; Na ve Bayes Model

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMMUNICATION; COMPUTER CRIME; LEARNING SYSTEMS; LINUX; MALWARE; MEASUREMENTS; MOBILE DEVICES; STATISTICAL TESTS;

EID: 84904558925     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IMCCC.2013.297     Document Type: Conference Paper
Times cited : (26)

References (8)
  • 5
    • 84856225193 scopus 로고    scopus 로고
    • Andromaly': A behavioral malware detection framework for android devices[J]
    • Asaf Shabtai, Uri Kanonov, Yuval Elovici et al.'Andromaly': a behavioral malware detection framework for android devices[J]. Journal of intelligent information systems, 2012, 38(1): 161-190.
    • (2012) Journal of Intelligent Information Systems , vol.38 , Issue.1 , pp. 161-190
    • Shabtai, A.1    Kanonov, U.2    Elovici, Y.3
  • 7
    • 84878368035 scopus 로고    scopus 로고
    • Dissecting android malware: Characterization and evolution[C]
    • Zhou, Yajin, Jiang, Xuxian. Dissecting Android Malware: Characterization and Evolution[C].//2012 IEEE Symposium on Security and Privacy. 2012: 95-109
    • (2012) 2012 IEEE Symposium on Security and Privacy , pp. 95-109
    • Zhou, Y.1    Jiang, X.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.