TY - GEN
T1 - Generic black-box end-to-end attack against state of the art API call based malware classifiers
AU - Rosenberg, Ishai
AU - Shabtai, Asaf
AU - Rokach, Lior
AU - Elovici, Yuval
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2018.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - In this paper, we present a black-box attack against API call based machine learning malware classifiers, focusing on generating adversarial sequences combining API calls and static features (e.g., printable strings) that will be misclassified by the classifier without affecting the malware functionality. We show that this attack is effective against many classifiers due to the transferability principle between RNN variants, feed forward DNNs, and traditional machine learning classifiers such as SVM. We also implement GADGET, a software framework to convert any malware binary to a binary undetected by malware classifiers, using the proposed attack, without access to the malware source code.
AB - In this paper, we present a black-box attack against API call based machine learning malware classifiers, focusing on generating adversarial sequences combining API calls and static features (e.g., printable strings) that will be misclassified by the classifier without affecting the malware functionality. We show that this attack is effective against many classifiers due to the transferability principle between RNN variants, feed forward DNNs, and traditional machine learning classifiers such as SVM. We also implement GADGET, a software framework to convert any malware binary to a binary undetected by malware classifiers, using the proposed attack, without access to the malware source code.
KW - Adversarial attacks
KW - Deep neural networks
KW - Dynamic analysis
KW - Malware classification
KW - Transferability
UR - http://www.scopus.com/inward/record.url?scp=85053870606&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-00470-5_23
DO - 10.1007/978-3-030-00470-5_23
M3 - Conference contribution
AN - SCOPUS:85053870606
SN - 9783030004699
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 490
EP - 510
BT - Research in Attacks, Intrusions, and Defenses - 21st International Symposium, RAID 2018, Proceedings
A2 - Bailey, Michael
A2 - Ioannidis, Sotiris
A2 - Stamatogiannakis, Manolis
A2 - Holz, Thorsten
PB - Springer Verlag
T2 - 21st International Symposium on Research in Attacks, Intrusions and Defenses, RAID 2018
Y2 - 10 September 2018 through 12 September 2018
ER -