03274nam a22005175i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001400153072001600167072002300183072001500206100007300221245013400294250001800428264007200446300004300518336002600561337002600587338003600613347002400649520134500673650004202018650002102060650004202081650002202123650002902145650003302174650003502207650002302242650001302265650002202278650001602300700007802316700007102394700007702465710003402542773002602576776003602602776003602638776003602674856004602710978-981-97-1459-9DE-He21320251030112057.0cr nn 008mamaa240523s2024    si |    s    |||| 0|eng d  a97898197145997 a10.1007/978-981-97-1459-92doi 4aTK5105.59 7aUTN2bicssc 7aCOM0430502bisacsh 7aUTN2thema1 aNiu, Weina.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut10aAndroid Malware Detection and Adversarial Methodsh[electronic resource] /cby Weina Niu, Xiaosong Zhang, Ran Yan, Jiacheng Gong.  a1st ed. 2024. 1aSingapore :bSpringer Nature Singapore :bImprint: Springer,c2024.  aXIV, 190 p. 5 illus.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda  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. 0aComputer networksxSecurity measures. 0aData protection. 0aData protectionxLaw and legislation. 0aMachine learning. 0aBlockchains (Databases).14aMobile and Network Security.24aData and Information Security.24aSecurity Services.24aPrivacy.24aMachine Learning.24aBlockchain.1 aZhang, Xiaosong.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut1 aYan, Ran.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut1 aGong, Jiacheng.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978981971458208iPrinted edition:z978981971460508iPrinted edition:z978981971461240uhttps://doi.org/10.1007/978-981-97-1459-9