N-gram Opcode Analysis for Android Malware Detection
作者： Suleiman Y. Yerima , Kieran McLaughlin , BooJoong Kang , Sakir Sezer
DOI:
关键词: n-gram 、 Android malware 、 Computer science 、 Opcode 、 Machine learning 、 Artificial intelligence 、 Android (operating system)
摘要: … -gram opcodes from Android applications and how to select n-gram opcodes that will enable optimal malware … The following two subsections describe the process of the n-gram opcode …
arxiv.org参考文章(27)
Borja Sanz, Igor Santos, Carlos Laorden, Xabier Ugarte-Pedrero, Pablo Garcia Bringas, Gonzalo Álvarez, PUMA: Permission Usage to Detect Malware in Android CISIS/ICEUTE/SOCO Special Sessions. pp. 289- 298 ,(2013) , 10.1007/978-3-642-33018-6_30
Min Zhao, Fangbin Ge, Tao Zhang, Zhijian Yuan, AntiMalDroid: An Efficient SVM-Based Malware Detection Framework for Android international conference on information computing and applications. pp. 158- 166 ,(2011) , 10.1007/978-3-642-27503-6_22
Suleiman Y. Yerima, Sakir Sezer, Igor Muttik, Android malware detection: An eigenspace analysis approach science and information conference. pp. 1236- 1242 ,(2015) , 10.1109/SAI.2015.7237302
Martina Lindorfer, Matthias Neugschwandtner, Christian Platzer, None, MARVIN: Efficient and Comprehensive Mobile App Classification through Static and Dynamic Analysis computer software and applications conference. ,vol. 2, pp. 422- 433 ,(2015) , 10.1109/COMPSAC.2015.103
Gerardo Canfora, Andrea De Lorenzo, Eric Medvet, Francesco Mercaldo, Corrado Aaron Visaggio, Effectiveness of Opcode ngrams for Detection of Multi Family Android Malware availability, reliability and security. pp. 333- 340 ,(2015) , 10.1109/ARES.2015.57
Asaf Shabtai, Uri Kanonov, Yuval Elovici, Chanan Glezer, Yael Weiss, Andromaly: a behavioral malware detection framework for android devices intelligent information systems. ,vol. 38, pp. 161- 190 ,(2012) , 10.1007/S10844-010-0148-X
Byeongho Kang, BooJoong Kang, Jungtae Kim, Eul Gyu Im, Android malware classification method: Dalvik bytecode frequency analysis research in adaptive and convergent systems. pp. 349- 350 ,(2013) , 10.1145/2513228.2513295
Ugur Pehlivan, Nuray Baltaci, Cengiz Acarturk, Nazife Baykal, The analysis of feature selection methods and classification algorithms in permission based Android malware detection 2014 IEEE Symposium on Computational Intelligence in Cyber Security (CICS). pp. 1- 8 ,(2014) , 10.1109/CICYBS.2014.7013371
Iker Burguera, Urko Zurutuza, Simin Nadjm-Tehrani, Crowdroid Proceedings of the 1st ACM workshop on Security and privacy in smartphones and mobile devices - SPSM '11. pp. 15- 26 ,(2011) , 10.1145/2046614.2046619
Suleiman Y. Yerima, Igor Muttik, Sakir Sezer, High Accuracy Android Malware Detection Using Ensemble Learning Iet Information Security. ,vol. 9, pp. 313- 320 ,(2015) , 10.1049/IET-IFS.2014.0099