| Information security: principles and practice M Stamp John Wiley & Sons, 2011 | 902 | 2011 |
| A comparison of static, dynamic, and hybrid analysis for malware detection A Damodaran, FD Troia, CA Visaggio, TH Austin, M Stamp Journal of Computer Virology and Hacking Techniques 13, 1-12, 2017 | 546 | 2017 |
| Hunting for metamorphic engines W Wong, M Stamp Journal in Computer Virology 2, 211-229, 2006 | 382 | 2006 |
| A revealing introduction to hidden Markov models M Stamp Department of Computer Science San Jose State University, 26-56, 2004 | 356 | 2004 |
| An algorithm for the k-error linear complexity of binary sequences with period 2/sup n M Stamp, CF Martin IEEE Transactions on Information Theory 39 (4), 1398-1401, 1993 | 310 | 1993 |
| Handbook of information and communication security P Stavroulakis, M Stamp Springer Science & Business Media, 2010 | 268 | 2010 |
| Opcode graph similarity and metamorphic detection N Runwal, RM Low, M Stamp Journal in computer virology 8, 37-52, 2012 | 217 | 2012 |
| Introduction to machine learning with applications in information security M Stamp Chapman and Hall/CRC, 2022 | 208 | 2022 |
| Structural entropy and metamorphic malware D Baysa, RM Low, M Stamp Journal of computer virology and hacking techniques 9, 179-192, 2013 | 189 | 2013 |
| Applied cryptanalysis: breaking ciphers in the real world M Stamp, RM Low John Wiley & Sons, 2007 | 185 | 2007 |
| Hidden Markov models for malware classification C Annachhatre, TH Austin, M Stamp Journal of Computer Virology and Hacking Techniques 11, 59-73, 2015 | 175 | 2015 |
| Deriving common malware behavior through graph clustering Y Park, D Reeves Proceedings of the 6th ACM Symposium on Information, Computer and …, 2011 | 160 | 2011 |
| Profile hidden Markov models and metamorphic virus detection S Attaluri, S McGhee, M Stamp Journal in computer virology 5, 151-169, 2009 | 158 | 2009 |
| Hunting for undetectable metamorphic viruses D Lin, M Stamp Journal in computer virology 7, 201-214, 2011 | 155 | 2011 |
| Transfer learning for image-based malware classification N Bhodia, P Prajapati, F Di Troia, M Stamp arXiv preprint arXiv:1903.11551, 2019 | 136 | 2019 |
| Chi-squared distance and metamorphic virus detection AH Toderici, M Stamp Journal of Computer Virology and Hacking Techniques 9, 1-14, 2013 | 127 | 2013 |
| Exploring hidden Markov models for virus analysis: A semantic approach TH Austin, E Filiol, S Josse, M Stamp 2013 46th Hawaii International Conference on System Sciences, 5039-5048, 2013 | 111 | 2013 |
| Detecting malware evolution using support vector machines M Wadkar, F Di Troia, M Stamp Expert Systems with Applications 143, 113022, 2020 | 109 | 2020 |
| Deep Learning versus Gist Descriptors for Image-based Malware Classification. S Yajamanam, VRS Selvin, F Di Troia, M Stamp Icissp, 553-561, 2018 | 106 | 2018 |
| Risks of monoculture M Stamp Communications of the ACM 47 (3), 120, 2004 | 97 | 2004 |
Thomas H. AustinAssociate Professor of Computer Science, San Jose State Universitybias2build.com üzerinde doğrulanmış e-posta adresine sahip
