6 citations · 6 across the 6 of their papers we have counts for
6 papers
iResolveX: Multi-Layered Indirect Call Resolution via Static Reasoning and Learning-Augmented Refinement
Monika Santra, Bokai Zhang, Mark Lim +3
Indirect call resolution remains a key challenge in reverse engineering and control-flow graph recovery, especially for stripped or optimized binaries. Static analysis is sound but…
Disa: Accurate Learning-based Static Disassembly with Attentions
Peicheng Wang, Monika Santra, Mingyu Liu +3
For reverse engineering related security domains, such as vulnerability detection, malware analysis, and binary hardening, disassembly is crucial yet challenging. The fundamental c…
DeepCatra: Learning Flow- and Graph-based Behaviors for Android Malware Detection
Yafei Wu, Jian Shi, Peicheng Wang +2
As Android malware is growing and evolving, deep learning has been introduced into malware detection, resulting in great effectiveness. Recent work is considering hybrid models and…
Dep: Mutation-based Dependency Generation for Precise Taint Analysis on Android Native Code
Cong Sun, Yuwan Ma, Dongrui Zeng +3
The existence of native code in Android apps plays an important role in triggering inconspicuous propagation of secrets and circumventing malware detection. However, the state-of-t…
CryptoEval: Evaluating the Risk of Cryptographic Misuses in Android Apps with Data-Flow Analysis
Cong Sun, Xinpeng Xu, Yafei Wu +4
The misunderstanding and incorrect configurations of cryptographic primitives have exposed severe security vulnerabilities to attackers. Due to the pervasiveness and diversity of c…
ReCFA: Resilient Control-Flow Attestation
Yumei Zhang, Xinzhi Liu, Cong Sun +4
Recent IoT applications gradually adapt more complicated end systems with commodity software. Ensuring the runtime integrity of these software is a challenging task for the remote…