Anomaly Detection for malware identification using Hardware Performance Counters.
作者： Alberto Garcia-Serrano
DOI:
关键词: Computer science 、 Computer hardware 、 Malware 、 Identification (information) 、 Software 、 Process (computing) 、 Cryptovirology 、 Anomaly detection 、 Computer security
摘要: … to amplify the small deviations produced by the malware. In this article we have used a … density-based clustering method. We found that, with low false positive rate, it’s possible to detect …
harvard.edu
arxiv.org
128.84.21.199参考文章(11)
Christine Deane, George Ho, Phil Mucci, Shirley Browne, PAPI: A Portable Interface to Hardware Performance Counters hpcmp users group conference. ,(1999)
Shailendra Singh, Sanjay Silakari, An ensemble approach for feature selection of Cyber Attack Dataset arXiv: Cryptography and Security. ,(2009)
E Eskin, Andrew Arnold, Michael Prerau, Leonid Portnoy, Sal Stolfo, A GEOMETRIC FRAMEWORK FOR UNSUPERVISED ANOMALY DETECTION: DETECTING INTRUSIONS IN UNLABELED DATA APPLICATIONS OF DATA MINING IN COMPUTER SECURITY. pp. 0- 0 ,(2002) , 10.7916/D8D50TQT
Konrad Rieck, Philipp Trinius, Carsten Willems, Thorsten Holz, Automatic analysis of malware behavior using machine learning Journal of Computer Security. ,vol. 19, pp. 639- 668 ,(2011) , 10.3233/JCS-2010-0410
Marco Prandini, Marco Ramilli, Return-Oriented Programming ieee symposium on security and privacy. ,vol. 10, pp. 84- 87 ,(2012) , 10.1109/MSP.2012.152
Alberto Avritzer, Rajanikanth Tanikella, Kiran James, Robert G. Cole, Elaine Weyuker, Monitoring for security intrusion using performance signatures workshop on software and performance. pp. 93- 104 ,(2010) , 10.1145/1712605.1712623
Christian Wressnegger, Guido Schwenk, Daniel Arp, Konrad Rieck, A close look on n-grams in intrusion detection: anomaly detection vs. classification Proceedings of the 2013 ACM workshop on Artificial intelligence and security. pp. 67- 76 ,(2013) , 10.1145/2517312.2517316
Mahbod Tavallaee, Ebrahim Bagheri, Wei Lu, Ali A. Ghorbani, A detailed analysis of the KDD CUP 99 data set computational intelligence and security. pp. 53- 58 ,(2009) , 10.1109/CISDA.2009.5356528
Markus M. Breunig, Hans-Peter Kriegel, Raymond T. Ng, Jörg Sander, LOF: identifying density-based local outliers international conference on management of data. ,vol. 29, pp. 93- 104 ,(2000) , 10.1145/335191.335388
Dmitrijs Zaparanuks, Milan Jovic, Matthias Hauswirth, Accuracy of performance counter measurements international symposium on performance analysis of systems and software. pp. 23- 32 ,(2009) , 10.1109/ISPASS.2009.4919635