Callback2Vec: Callback-aware hierarchical embedding for mobile application

作者: Chenkai Guo , Dengrong Huang , Naipeng Dong , Jianwen Zhang , Jing Xu

DOI: 10.1016/J.INS.2020.06.058

关键词: Downstream (software development)CallbackSemantics (computer science)Representation (mathematics)Theoretical computer scienceEmbeddingEvent (computing)Scale (chemistry)Code (cryptography)Computer science

摘要: … generated using the traditional context-free encoding, which loses … The Adjusted Rand Index (ARI) [20], a standard evaluation … of those strong context-aware embedding methods, and …

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
Debasis Ganguly, Dwaipayan Roy, Mandar Mitra, Gareth J.F. Jones, Word Embedding based Generalized Language Model for Information Retrieval international acm sigir conference on research and development in information retrieval. pp. 795- 798 ,(2015) , 10.1145/2766462.2767780
Justin Sahs, Latifur Khan, A Machine Learning Approach to Android Malware Detection european intelligence and security informatics conference. pp. 141- 147 ,(2012) , 10.1109/EISIC.2012.34
Siegfried Rasthofer, Steven Arzt, Eric Bodden, A Machine-learning Approach for Classifying and Categorizing Android Sources and Sinks network and distributed system security symposium. ,(2014) , 10.14722/NDSS.2014.23039
Hugo Gascon, Fabian Yamaguchi, Daniel Arp, Konrad Rieck, Structural detection of android malware using embedded call graphs Proceedings of the 2013 ACM workshop on Artificial intelligence and security. pp. 45- 54 ,(2013) , 10.1145/2517312.2517315
Daniel Arp, Michael Spreitzenbarth, Malte Hubner, Hugo Gascon, Konrad Rieck, CERT Siemens, DREBIN: Effective and Explainable Detection of Android Malware in Your Pocket. network and distributed system security symposium. ,(2014) , 10.14722/NDSS.2014.23247
Y. Bengio, A. Courville, P. Vincent, Representation Learning: A Review and New Perspectives IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. 35, pp. 1798- 1828 ,(2013) , 10.1109/TPAMI.2013.50
Omer Levy, Yoav Goldberg, Linguistic Regularities in Sparse and Explicit Word Representations Proceedings of the Eighteenth Conference on Computational Natural Language Learning. pp. 171- 180 ,(2014) , 10.3115/V1/W14-1618
Shifu Hou, Aaron Saas, Yanfang Ye, Lifei Chen, DroidDelver: An Android Malware Detection System Using Deep Belief Network Based on API Call Blocks Web-Age Information Management. pp. 54- 66 ,(2016) , 10.1007/978-3-319-47121-1_5
Zhenxiang Chen, Qiben Yan, Hongbo Han, Shanshan Wang, Lizhi Peng, Lin Wang, Bo Yang, Machine learning based mobile malware detection using highly imbalanced network traffic Information Sciences. pp. 346- 364 ,(2018) , 10.1016/J.INS.2017.04.044