How malware works or operate or penetrate?
Best insight from top research papers
Malware is a term used to describe malicious software that is designed to harm or exploit devices, services, or networks. It can disrupt operations, compromise the integrity and confidentiality of information, and pose a serious threat to sensitive and critical operations. Traditional approaches to malware detection, such as antivirus software, are not always effective in detecting new or unseen malware. Attackers use automated tools to generate new or modified malware, making it difficult for signature-based detection methods to keep up. To address this, researchers have proposed using natural language processing techniques to analyze the strings present in the executable files of malware. By treating these strings as a language abstraction and extracting relevant topics, a classifier's detection performance can be improved. Experimental results have shown that this topic modeling-based approach outperforms traditional techniques in terms of precision and accuracy .
Answers from top 5 papers
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| Papers (5) | Insight |
|---|---|
| The paper does not provide specific information on how malware operates or penetrates computer systems. It focuses on the analysis of malware using reverse engineering techniques. | |
| The paper does not provide specific information on how malware works or operates. It mainly focuses on the challenges faced by investigators in malware detection and the need for a novel approach to malware detection. | |
22 Jul 2013 3 Citations | The provided paper does not provide information on how malware works or operates. The paper focuses on detecting and clustering variants of malware based on structural sequence comparison and probabilistic similarity measures. |
| The paper does not provide specific information on how malware works or operates. It mainly focuses on the classification and detection of malware. | |
30 May 2022 | The paper does not provide information on how malware works or operates. The paper focuses on proposing a topic modeling-based approach for executable file malware detection. |
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