Network topology construction is one of the basic means to study the target network. Whether it is the discovery of vital nodes, IP location or network characteristics mining, a complete and accurate network topology ...
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Taint analysis is a common technology for software analysis, which is widely used in the region of information security. Aiming at the problem that the existing binary program dynamic taint analysis framework does not...
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Industrial Control Systems (ICSs) are widely deployed in critical infrastructures, such as electric power, water filtration and distribution. Programmable Logic Controllers (PLCs) work as the core components of an ICS...
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Security of online software upgrade has become one of the most important evaluation criteria of cyber security. It is too inefficient to evaluate the security of software upgrade by manual reverse analysis method, whi...
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Fuzzing [1] is a well-known technique which was employed to provide unexpected or random data as input to JavaScript engines in hopes of finding a security vulnerability. For effective fuzzing, the input must be both ...
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With the continuous development of trusted computing, the integrity measurement has gradually been practical;but the popularization and application of the existing measurement tools are still restricted by their own m...
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The security of the IoT has become a hot research area in cyberspace security, among which the malware is a major threat. Based on the ATT&CK model, this paper studies the composition and behavior of IoT malware, ...
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Malware clustering analysis plays an important role in large-scale malware homology analysis. However, the generation approach of the ground truth data is usually ignored. The Labels from Anti-virus(AV) engines are mo...
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Current white-box attack to deep neural networks have achieved considerable success, but not for black-box attack. The main reason is poor transferability, as the adversarial examples are crafted with single deep neur...
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Neural networks are vulnerable when input data is applied with human-imperceptible perturbations, which is called adversarial examples. When used in image classification models, adversarial examples mislead neural net...
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