Results 91 to 100 of about 46,394 (182)
An Android Malicious Code Detection Method Based on Improved DCA Algorithm
Recently, Android malicious code has increased dramatically and the technology of reinforcement is increasingly powerful. Due to the development of code obfuscation and polymorphic deformation technology, the current Android malicious code static ...
Chundong Wang +5 more
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A study of the relationship of malware detection mechanisms using Artificial Intelligence
Implementation of malware detection using Artificial Intelligence (AI) has emerged as a significant research theme to combat evolving various types of malwares.
Jihyeon Song +6 more
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We propose a detection system incorporating a weighted voting mechanism that reflects the vote’s reliability based on the accuracy of each detector’s examination, which overcomes the problem of cooperative detection. Collaborative malware detection is an
Naonobu Okazaki +6 more
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Stateless Malware Packet Detection by Incorporating Naive Bayes with Known Malware Signatures
Malware detection done at the network infrastructure level is still an open research problem ,considering the evolution of malwares and high detection accuracy needed to detect these threats.
Ismahani Ismail +2 more
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Hybrid Input Model Using Multiple Features From Surface Analysis for Malware Detection
Many malware detection models have been proposed to protect computers from the ever- increasing number of malware attacks. The features that are obtained from surface analysis and machine learning are often used for malware detection.
Mamoru Mimura, Satoki Kanno
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MIDALF—multimodal image and audio late fusion for malware detection
Malware detection remains a critical challenge in cybersecurity due to the rapid evolution of sophisticated malware and adversarial threats. Traditional detection systems struggle to adapt to dynamic malware behavior and are particularly vulnerable to ...
Setia Juli Irzal Ismail +4 more
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The sophistication of Android malware poses significant threats to user security and privacy. Traditional detection methods struggle with rapid malware evolution and benign application diversity, leading to high false positive rates and limited ...
Yogesh Kumar Sharma +3 more
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Detection of unseen malware threats using generative adversarial networks and deep learning models
The fast advancement of malware makes it an urgent problem for cybersecurity, as perpetrators consistently devise obfuscation methods to avoid detection.
Chirag Joshi +2 more
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Incremental clustering method based on Gaussian mixture model to identify malware family
Aiming at the logical similarity of the behavioral characteristics of malware belonging to the same family,the characteristics of malware were extracted by tracking the logic rules of API function call from the perspective of behavior detection,and the ...
Jianwei HU +3 more
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Reassessing feature-based Android malware detection in a contemporary context. [PDF]
Muzaffar A +3 more
europepmc +1 more source

