Learning Malware Using Generalized Graph Kernels
暂无分享,去创建一个
[1] Somesh Jha,et al. Synthesizing Near-Optimal Malware Specifications from Suspicious Behaviors , 2010, 2010 IEEE Symposium on Security and Privacy.
[2] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[3] Christopher Krügel,et al. On the Detection of Anomalous System Call Arguments , 2003, ESORICS.
[4] Carsten Willems,et al. Learning and Classification of Malware Behavior , 2008, DIMVA.
[5] Hugo Daniel Macedo,et al. Mining Malware Specifications through Static Reachability Analysis , 2013, ESORICS.
[6] Tayssir Touili,et al. Precise Extraction of Malicious Behaviors , 2018, 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC).
[7] Sulaiman Mohd Nor,et al. FEATURE SELECTION AND MACHINE LEARNING CLASSIFICATION FOR MALWARE DETECTION , 2015 .
[8] Lior Rokach,et al. Mal-ID: Automatic Malware Detection Using Common Segment Analysis and Meta-Features , 2012, J. Mach. Learn. Res..
[9] Salvatore J. Stolfo,et al. Data mining methods for detection of new malicious executables , 2001, Proceedings 2001 IEEE Symposium on Security and Privacy. S&P 2001.
[10] Chandrasekar Ravi,et al. Malware Detection using Windows Api Sequence and Machine Learning , 2012 .
[11] Radu State,et al. Malware analysis with graph kernels and support vector machines , 2009, 2009 4th International Conference on Malicious and Unwanted Software (MALWARE).
[12] Jian Xu,et al. A similarity metric method of obfuscated malware using function-call graph , 2012, Journal of Computer Virology and Hacking Techniques.
[13] Hichem Sahbi,et al. Bags-of-daglets for action recognition , 2014, 2014 IEEE International Conference on Image Processing (ICIP).
[14] Stavros D. Nikolopoulos,et al. A graph-based model for malware detection and classification using system-call groups , 2017, Journal of Computer Virology and Hacking Techniques.
[15] Guanhua Yan,et al. Discriminant malware distance learning on structural information for automated malware classification , 2013, SIGMETRICS.
[16] Hichem Sahbi,et al. Directed Acyclic Graph Kernels for Action Recognition , 2013, 2013 IEEE International Conference on Computer Vision.
[17] Bazara I. A. Barry,et al. Improving the Detection of Malware Behaviour Using Simplified Data Dependent API Call Graph , 2013 .
[18] Christopher Krügel,et al. Effective and Efficient Malware Detection at the End Host , 2009, USENIX Security Symposium.
[19] Joris Kinable,et al. Malware classification based on call graph clustering , 2010, Journal in Computer Virology.
[20] Hichem Sahbi,et al. Context-Based Support Vector Machines for Interconnected Image Annotation , 2010, ACCV.
[21] Tayssir Touili,et al. Malware Detection based on Graph Classification , 2017, ICISSP.
[22] Curtis B. Storlie,et al. Graph-based malware detection using dynamic analysis , 2011, Journal in Computer Virology.
[23] Javier Esparza,et al. Reachability Analysis of Pushdown Automata: Application to Model-Checking , 1997, CONCUR.
[24] Tayssir Touili,et al. Automatic extraction of malicious behaviors , 2016, 2016 11th International Conference on Malicious and Unwanted Software (MALWARE).
[25] Marcus A. Maloof,et al. Learning to detect malicious executables in the wild , 2004, KDD.
[26] Dragos Gavrilut,et al. Malware Detection Using Perceptrons and Support Vector Machines , 2009, 2009 Computation World: Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns.
[27] S. V. N. Vishwanathan,et al. Graph kernels , 2007 .