A Taxonomy of Obfuscating Transformations

By Christian S. Collberg, Clark D. Thomborson, Douglas Low. 1997

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Citations in the corpus

Yes, Machine Learning Can Be More Secure! A Case Study on Android Malware Detection (2017, background): “that is downloaded or decrypted at runtime, or code that is thoroughly obfuscated [17], [23], [24], [31], [35], [36], [47].”
Oracle-guided component-based program synthesis (2010, background): “tion strategies from literature on obfuscation techniques [5] (P23) and Internet worms - Conficker [22] (P24) and MyDoom [21] (P25).”
Watermarking, Tamper-Proofing, and Obfuscation-Tools for Software Protection (2002, methodology): “Recently, software watermarking [22], [28], [35], [60], tamper-proofing [5], [6], [38], [77], and obfuscation [20], [ 23 ], [24], [25], [38], [49], [65], [92] have emerged as feasible technical means for the intellectual property protection of software.”
Evaluating Analysis Tools for Android Apps: Status Quo and Robustness Against Obfuscation (2016, methodology): “We did not address the injection of opaque predicates [12], which can be used to amplify the path explosion problem in multipath execution [29] and dynamic symbolic execution [46].”
Towards Better Program Obfuscation: Optimization via Language Models (2016, unknown): “Program obfuscation has been intensively studied [7, 8, 21, 20].”
Detection of Intrusions and Malware, and Vulnerability Assessment (2012, methodology): “Furthermore, malware classification research has produced a number of independent algorithmic improvements to increase malware classification accuracies [18,17,15,2,11,16,6].”
Static Analysis of Executables to Detect Malicious Patterns (2003, methodology): “While there are other generic obfuscation techniques [11, 12], those described here seem to be preferred by malicious code writers, possibly because implementing them is easy and they add little to the memory footprint.”
Secure outsourcing of scientific computations (2001, methodology): “A review and taxonomy of these techniques are given in [7].”
DroidChameleon: evaluating Android anti-malware against transformation attacks (2013, background): “[12] review and propose different types of obfuscations.”
The Evolution of Android Malware and Android Analysis Techniques (2017, result): “Similar forms of obfuscation have roots in traditional PC practices [Collberg et al. 1997].”
Static Disassembly of Obfuscated Binaries (2004, background): “A number of approaches have been proposed to make the reverse-engineering process harder [8] [9] [17].”
The New C Standard (Excerpted material) An Economic and Cultural Commentary (2008, unknown): “Studying those cases where the requirement is to minimize readability[ 6 ] can also be useful.”
SoK: Automated Software Diversity (2014, background): “b) Opaque Predicate Insertion: A single-predecessor block b can be substituted with a conditional branch to b and its clone b′ using an arbitrary predicate [14], [16].”
Context2Name: A Deep Learning-Based Approach to Infer Natural Variable Names from Usage Contexts (2017, background): “Nonetheless a large body of work has been published on new techniques for obfuscation [12, 23], as it has proved to be practically useful.”