Towards exact and inexact approximate matching of executable binaries

Digital Investigation - Tập 28 - Trang S12-S21 - 2019
Lorenz Liebler1, Harald Baier1
1da/sec - Biometrics and Internet Security Research Group, University of Applied Sciences Darmstadt, Germany

Tài liệu tham khảo

Azab, 2014, Mining malware to detect variants, 44 Bloom, 1970, Space/time trade-offs in hash coding with allowable errors, Commun. ACM, 13, 422, 10.1145/362686.362692 Breitinger, 2012, Similarity preserving hashing: eligible properties and a new algorithm mrsh-v2, 167 Breitinger, 2014, vol. 800, 168 French, 2012, 2 fuzzy hashing techniques in applied malware analysis, 2 Kornblum, 2006, Identifying almost identical files using context triggered piecewise hashing, Digit. Invest., 3S, S91, 10.1016/j.diin.2006.06.015 Li, 2015, Experimental study of fuzzy hashing in malware clustering analysis, 52 Liebler, 2017, Approxis: a fast, robust, lightweight and approximate disassembler considered in the field of memory forensics Liebler, 2018, mrsh-mem: approximate matching on raw memory dumps, 47 Oliver, 2013, Tlsh–a locality sensitive hash, 7 Oliver, 2014, Using randomization to attack similarity digests, 199 Pagani, 2018, Beyond precision and recall: understanding uses (and misuses) of similarity hashes in binary analysis, 354 Ren Roussev, 2010, Data fingerprinting with similarity digests, 207 Upchurch, 2015, Variant: a malware similarity testing framework, 31