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20182026
most citedROPNN: Detection of ROP Payloads Using Deep Neural Networks

9 citations · 14 across the 8 of their papers we have counts for

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9 papers · 1 filter

cs.CR2026

Detecting Avalanche Effect in Adversarial Settings: Spotting the Encryption Loops in Ransomware

Nanqing Luo, Xusheng Li, Haizhou Wang +3

Spotting encryption loops in binary-only ransomware is a critical reverse engineering task. Since the existence of avalanche effect, an intrinsic characteristic of any secure encry…

cs.CR2026

Differentiation Between Faults and Cyberattacks through Combined Analysis of Cyberspace Logs and Physical Measurements

Mohammad Shamim Ahsan, Haizhou Wang, Venkateswara Reddy Motakatla +2

In recent years, cyberattacks - along with physical faults - have become an increasing factor causing system failures, especially in DER (Distributed Energy Resources) systems. In…

cs.CR2024

Unmasking the Shadows: Pinpoint the Implementations of Anti-Dynamic Analysis Techniques in Malware Using LLM

Haizhou Wang, Nanqing Luo, Xusheng Li +1

Sandboxes and other dynamic analysis processes are prevalent in malware detection systems nowadays to enhance the capability of detecting 0-day malware. Therefore, techniques of an…

cs.CR2024

Hide Your Malicious Goal Into Benign Narratives: Jailbreak Large Language Models through Carrier Articles

Zhilong Wang, Haizhou Wang, Nanqing Luo +4

Large Language Model (LLM) jailbreak refers to a type of attack aimed to bypass the safeguard of an LLM to generate contents that are inconsistent with the safe usage guidelines. B…

cs.CR2024

A hybrid LLM workflow can help identify user privilege related variables in programs of any size

Haizhou Wang, Zhilong Wang, Peng Liu

Many programs involves operations and logic manipulating user privileges, which is essential for the security of an organization. Therefore, one common malicious goal of attackers…

cs.CR2021★ 2 cited

Identifying Non-Control Security-Critical Data through Program Dependence Learning

Zhilong Wang, Haizhou Wang, Hong Hu +1

As control-flow protection gets widely deployed, it is difficult for attackers to corrupt control-data and achieve control-flow hijacking. Instead, data-oriented attacks, which man…

cs.CR2021★ 2 cited

Tackling Imbalanced Data in Cybersecurity with Transfer Learning: A Case with ROP Payload Detection

Haizhou Wang, Peng Liu

In recent years, deep learning gained proliferating popularity in the cybersecurity application domain, since when being compared to traditional machine learning, it usually involv…

cs.CR2019★ 1 cited

Using Deep Learning to Solve Computer Security Challenges: A Survey

Yoon-Ho Choi, Peng Liu, Zitong Shang +5

Although using machine learning techniques to solve computer security challenges is not a new idea, the rapidly emerging Deep Learning technology has recently triggered a substanti…

cs.CR2018★ 9 cited

ROPNN: Detection of ROP Payloads Using Deep Neural Networks

Xusheng Li, Zhisheng Hu, Haizhou Wang +4

Return-oriented programming (ROP) is a code reuse attack that chains short snippets of existing code to perform arbitrary operations on target machines. Existing detection methods…