Semantics-aware android malware classification using weighted contextual api dependency graphs
The drastic increase of Android malware has led to a strong interest in developing methods
to automate the malware analysis process. Existing automated Android malware detection …
to automate the malware analysis process. Existing automated Android malware detection …
Analyzing and detecting emerging Internet of Things malware: A graph-based approach
The steady growth in the number of deployed Internet of Things (IoT) devices has been
paralleled with an equal growth in the number of malicious software (malware) targeting …
paralleled with an equal growth in the number of malicious software (malware) targeting …
Adversarial learning attacks on graph-based IoT malware detection systems
IoT malware detection using control flow graph (CFG)-based features and deep learning
networks are widely explored. The main goal of this study is to investigate the robustness of …
networks are widely explored. The main goal of this study is to investigate the robustness of …
Automated synthesis of semantic malware signatures using maximum satisfiability
This paper proposes a technique for automatically learning semantic malware signatures for
Android from very few samples of a malware family. The key idea underlying our technique …
Android from very few samples of a malware family. The key idea underlying our technique …
Dl-fhmc: Deep learning-based fine-grained hierarchical learning approach for robust malware classification
The acceptance of the Internet of Things (IoT) for both household and industrial applications
is accompanied by the rapid growth of IoT malware. With the increase of their attack surface …
is accompanied by the rapid growth of IoT malware. With the increase of their attack surface …
Graph-based comparison of IoT and android malware
The growth in the number of android and Internet of Things (IoT) devices has witnessed a
parallel increase in the number of malicious software (malware) that can run on both …
parallel increase in the number of malicious software (malware) that can run on both …
An android malware detection approach using community structures of weighted function call graphs
Y Du, J Wang, Q Li - IEEE Access, 2017 - ieeexplore.ieee.org
With the development of code obfuscation and application repackaging technologies, an
increasing number of structural information-based methods have been proposed for …
increasing number of structural information-based methods have been proposed for …
Recurrent semantic learning-driven fast binary vulnerability detection in healthcare cyber physical systems
X Yi, J Wu, G Li, AK Bashir, J Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Healthcare cyber physical systems (HCPS) always pursuing high availability allow software
providers to adopt multiple kinds of development languages to reuse third-party program …
providers to adopt multiple kinds of development languages to reuse third-party program …
Hercules: Reproducing crashes in real-world application binaries
VT Pham, WB Ng, K Rubinov… - 2015 IEEE/ACM 37th …, 2015 - ieeexplore.ieee.org
Binary analysis is a well-investigated area in software engineering and security. Given real-
world program binaries, generating test inputs which cause the binaries to crash is crucial …
world program binaries, generating test inputs which cause the binaries to crash is crucial …
Automating information flow analysis of low level code
Low level code is challenging: It lacks structure, it uses jumps and symbolic addresses, the
control flow is often highly optimized, and registers and memory locations may be reused in …
control flow is often highly optimized, and registers and memory locations may be reused in …