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Found 16 papers, 4 papers with code
How to Train your Antivirus: RL-based Hardening through the Problem-Space
It also makes possible to provide theoretical guarantees on the robustness of the model against a particular set of adversarial capabilities.
Unraveling the Key of Machine Learning Solutions for Android Malware Detection
Android malware detection serves as the front line against malicious apps.
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time (Extended Version)
Machine learning (ML) plays a pivotal role in detecting malicious software.
Adversarial Markov Games: On Adaptive Decision-Based Attacks and Defenses
To reliably measure robustness, it is important to evaluate against realistic and worst-case attacks.
Locate and Verify: A Two-Stream Network for Improved Deepfake Detection
Deepfake has taken the world by storm, triggering a trust crisis.
DFIL: Deepfake Incremental Learning by Exploiting Domain-invariant Forgery Clues
However, the accuracy of detection models degrades significantly on images generated by new deepfake methods due to the difference in data distribution.
Exploiting Code Symmetries for Learning Program Semantics
This paper tackles the challenge of teaching code semantics to Large Language Models (LLMs) for program analysis by incorporating code symmetries into the model architecture.
Jigsaw Puzzle: Selective Backdoor Attack to Subvert Malware Classifiers
Empirically, we show that existing backdoor attacks in malware classifiers are still detectable by recent defenses such as MNTD.
Realizable Universal Adversarial Perturbations for Malware
Universal Adversarial Perturbations (UAPs), which identify noisy patterns that generalize across the input space, allow the attacker to greatly scale up the generation of such examples.
Identifying Authorship Style in Malicious Binaries: Techniques, Challenges & Datasets
Attributing a piece of malware to its creator typically requires threat intelligence.
Cryptography and Security
ROPfuscator: Robust Obfuscation with ROP
Software obfuscation plays a crucial role in protecting intellectual property in software from reverse engineering attempts.
Cryptography and Security Software Engineering
Dos and Don'ts of Machine Learning in Computer Security
With the growing processing power of computing systems and the increasing availability of massive datasets, machine learning algorithms have led to major breakthroughs in many different areas.
Catch Me (On Time) If You Can: Understanding the Effectiveness of Twitter URL Blacklists
In addition, an equally large number of URLs contained within public tweets remain in GSB for at least 150 days, raising questions about potential false positives in the blacklist.
Cryptography and Security
Intriguing Properties of Adversarial ML Attacks in the Problem Space
Second, building on our formalization, we propose a novel problem-space attack on Android malware that overcomes past limitations.
TESSERACT: Eliminating Experimental Bias in Malware Classification across Space and Time
Is Android malware classification a solved problem?
BabelView: Evaluating the Impact of Code Injection Attacks in Mobile Webviews
A Webview embeds a full-fledged browser in a mobile application and allows the application to expose a custom interface to JavaScript code.
Cryptography and Security Software Engineering
