Identifying Authorship Style in Malicious Binaries: Techniques,
Challenges & Datasets

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Identifying Authorship Style in Malicious Binaries: Techniques, Challenges & Datasets

15 January 2021

Lorenzo Cavallaro

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Papers citing "Identifying Authorship Style in Malicious Binaries: Techniques, Challenges & Datasets"

14 / 14 papers shown

Title
Automatic Yara Rule Generation Using Biclustering Edward Raff Richard Zak Gary Lopez Munoz William Fleming Hyrum S. Anderson Bobby Filar Charles K. Nicholas James Holt AAML 15 31 0 06 Sep 2020
End-to-End Deep Neural Networks and Transfer Learning for Automatic Analysis of Nation-State Malware Ishai Rosenberg Guillaume Sicard E. David AAML 24 28 0 30 Nov 2019
A Survey of Binary Code Similarity I. Haq Juan Caballero 33 137 0 25 Sep 2019
Misleading Authorship Attribution of Source Code using Adversarial Learning Erwin Quiring Alwin Maier Konrad Rieck 46 106 0 29 May 2019
The MalSource Dataset: Quantifying Complexity and Code Reuse in Malware Development Alejandro Calleja Juan Tapiador Juan Caballero 46 38 0 16 Nov 2018
Malware triage for early identification of Advanced Persistent Threat activities Giuseppe Laurenza Riccardo Lazzeretti Lucas Mazzotti 21 28 0 16 Oct 2018
Adversarial Binaries for Authorship Identification Xiaozhu Meng B. Miller S. Jha AAML 36 11 0 21 Sep 2018
Adversarial Malware Binaries: Evading Deep Learning for Malware Detection in Executables Bojan Kolosnjaji Ambra Demontis Battista Biggio Davide Maiorca Giorgio Giacinto Claudia Eckert Fabio Roli AAML 55 317 0 12 Mar 2018
Microsoft Malware Classification Challenge Royi Ronen Marian Radu Corina Feuerstein E. Yom-Tov Mansour Ahmadi 63 380 0 22 Feb 2018
DeepAPT: Nation-State APT Attribution Using End-to-End Deep Neural Networks Ishai Rosenberg Guillaume Sicard E. David 28 43 0 27 Nov 2017
Git Blame Who?: Stylistic Authorship Attribution of Small, Incomplete Source Code Fragments Edwin Dauber Aylin Caliskan Richard E. Harang Gregory Shearer Michael Weisman Frederica Nelson Rachel Greenstadt 30 45 0 20 Jan 2017
On the Feasibility of Malware Authorship Attribution S. Alrabaee Paria Shirani M. Debbabi Lingyu Wang DeLMO 60 48 0 10 Jan 2017
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 266 8,555 0 16 Aug 2016
When Coding Style Survives Compilation: De-anonymizing Programmers from Executable Binaries Aylin Caliskan Fabian Yamaguchi Edwin Dauber Richard E. Harang Konrad Rieck Rachel Greenstadt Arvind Narayanan 28 115 0 28 Dec 2015

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