소장자료

>>
소장자료
>
000 nam5i
001 2210080934175
003 DE-He213
005 20250321105341
007 cr nn 008mamaa
008 240523s2024 si | s |||| 0|eng d
020 a97898197145999978-981-97-1459-9
024 a10.1007/978-981-97-1459-92doi
040 a221008
050 aTK5105.59
072 aUTN2bicssc
072 aCOM0430502bisacsh
072 aUTN2thema
082 a005.8223
100 aNiu, Weina.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut
245 00 aAndroid Malware Detection and Adversarial Methodsh[electronic resource] /cby Weina Niu, Xiaosong Zhang, Ran Yan, Jiacheng Gong.
250 a1st ed. 2024.
264 aSingapore :bSpringer Nature Singapore :bImprint: Springer,c2024.
300 aXIV, 190 p. 5 illus.bonline resource.
336 atextbtxt2rdacontent
337 acomputerbc2rdamedia
338 aonline resourcebcr2rdacarrier
347 atext filebPDF2rda
520 aThe rise of Android malware poses a significant threat to users’ information security and privacy. Malicious software can inflict severe harm on users by employing various tactics, including deception, personal information theft, and device control. To address this issue, both academia and industry are continually engaged in research and development efforts focused on detecting and countering Android malware. This book is a comprehensive academic monograph crafted against this backdrop. The publication meticulously explores the background, methods, adversarial approaches, and future trends related to Android malware. It is organized into four parts: the overview of Android malware detection, the general Android malware detection method, the adversarial method for Android malware detection, and the future trends of Android malware detection. Within these sections, the book elucidates associated issues, principles, and highlights notable research. By engaging with this book, readers will gain not only a global perspective on Android malware detection and adversarial methods but also a detailed understanding of the taxonomy and general methods outlined in each part. The publication illustrates both the overarching model and representative academic work, facilitating a profound comprehension of Android malware detection.
650 aComputer networksxSecurity measures.
650 aData protection.
650 aData protectionxLaw and legislation.
650 aMachine learning.
650 aBlockchains (Databases).
650 aMobile and Network Security.
650 aData and Information Security.
650 aSecurity Services.
650 aPrivacy.
650 aMachine Learning.
650 aBlockchain.
700 aZhang, Xiaosong.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut
700 aYan, Ran.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut
700 aGong, Jiacheng.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut
710 aSpringerLink (Online service)
773 tSpringer Nature eBook
776 iPrinted edition:z9789819714582
776 iPrinted edition:z9789819714605
776 iPrinted edition:z9789819714612
856 uhttps://doi.org/10.1007/978-981-97-1459-9
912 aZDB-2-SCS
912 aZDB-2-SXCS
950 aComputer Science (SpringerNature-11645)
950 aComputer Science (R0) (SpringerNature-43710)
Android Malware Detection and Adversarial Methods[electronic resource] /by Weina Niu, Xiaosong Zhang, Ran Yan, Jiacheng Gong
종류
전자책
서명
Android Malware Detection and Adversarial Methods[electronic resource] /by Weina Niu, Xiaosong Zhang, Ran Yan, Jiacheng Gong
저자명
판 사항
1st ed. 2024.
형태사항
XIV, 190 p 5 illus online resource.
주기사항
The rise of Android malware poses a significant threat to users’ information security and privacy. Malicious software can inflict severe harm on users by employing various tactics, including deception, personal information theft, and device control. To address this issue, both academia and industry are continually engaged in research and development efforts focused on detecting and countering Android malware. This book is a comprehensive academic monograph crafted against this backdrop. The publication meticulously explores the background, methods, adversarial approaches, and future trends related to Android malware. It is organized into four parts: the overview of Android malware detection, the general Android malware detection method, the adversarial method for Android malware detection, and the future trends of Android malware detection. Within these sections, the book elucidates associated issues, principles, and highlights notable research. By engaging with this book, readers will gain not only a global perspective on Android malware detection and adversarial methods but also a detailed understanding of the taxonomy and general methods outlined in each part. The publication illustrates both the overarching model and representative academic work, facilitating a profound comprehension of Android malware detection.
관련 URL

소장정보

도서예약
서가부재도서 신고
보존서고신청
캠퍼스대출
우선정리신청
검색지인쇄
등록번호 청구기호 별치기호 소장위치 대출상태 반납예정일 서비스
전자자료는 소장사항이 존재하지 않습니다

책소개

전체 메뉴 보기