The Experts below are selected from a list of 399 Experts worldwide ranked by ideXlab platform
Eddy Willems - One of the best experts on this subject based on the ideXlab platform.
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Malware Author Profiles
Cyberdanger, 2019Co-Authors: Eddy WillemsAbstract:Hackers and people who write Malware are by no means always criminal geniuses. In fact, not all Malware Authors have, historically, intentionally set out to break the law, though nowadays most are quite happy to do so where there are high profits and low risks. Here we take a closer look at the psychology of the Malware developer.
Anil Somayaji - One of the best experts on this subject based on the ideXlab platform.
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The Malware Author testing challenge
2014 Second Workshop on Anti-malware Testing Research (WATeR), 2014Co-Authors: Tarun Moni, Sameer Salahudeen, Anil SomayajiAbstract:Attackers regularly evaluate anti-Malware software to see whether or not their Malware will be detected. This attacker-driven anti-Malware testing is something defenders would ideally want to limit. Given that anti-Malware products must be widely distributed to be commercially viable, it is not feasible to prevent attackers from running them. Here we examine whether it may be possible to instead limit the effectiveness of attacker tests. Specifically, we present a game-theoretic model of anti-Malware testing where detection timeliness and coverage are parameters that can be adjusted by anti-Malware providers. The less coverage and the slower the response, the harder it is for attackers to determine whether their Malware will be detected-and the less protection the software provides to hosts running the anti-Malware software. While our results are preliminary, they suggest that it is clearly non-optimal for anti-Malware vendors to simply maximize coverage and detection time. As we explain, this result has significant implications for product design and (non-malicious) anti-Malware testing methodologies.
Tarun Moni - One of the best experts on this subject based on the ideXlab platform.
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The Malware Author testing challenge
2014 Second Workshop on Anti-malware Testing Research (WATeR), 2014Co-Authors: Tarun Moni, Sameer Salahudeen, Anil SomayajiAbstract:Attackers regularly evaluate anti-Malware software to see whether or not their Malware will be detected. This attacker-driven anti-Malware testing is something defenders would ideally want to limit. Given that anti-Malware products must be widely distributed to be commercially viable, it is not feasible to prevent attackers from running them. Here we examine whether it may be possible to instead limit the effectiveness of attacker tests. Specifically, we present a game-theoretic model of anti-Malware testing where detection timeliness and coverage are parameters that can be adjusted by anti-Malware providers. The less coverage and the slower the response, the harder it is for attackers to determine whether their Malware will be detected-and the less protection the software provides to hosts running the anti-Malware software. While our results are preliminary, they suggest that it is clearly non-optimal for anti-Malware vendors to simply maximize coverage and detection time. As we explain, this result has significant implications for product design and (non-malicious) anti-Malware testing methodologies.
Sangwook Kim - One of the best experts on this subject based on the ideXlab platform.
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a human in the loop approach to Malware Author classification
Conference on Information and Knowledge Management, 2020Co-Authors: Eujeanne Kim, Sungjun Park, Dongkyu Chae, Seokwoo Choi, Sangwook KimAbstract:For these few decades Malwares have been posing a major concern in the cyber security. Recently, a number of "Author groups" have been generating lots of newMalwares by sharing source code within a group and exploiting evasive schemes such as polymorphism and metamorphism. This motivates us to study the problem of identifying the Author group of a given Malware, which would be able to work for not only blocking Malwares but also legally punishing suspected Malware Authors. In this paper, we propose a human-machine collaborative approach for classifying Author groups of Malwares accurately. We also propose a visualization method for helping human experts to make the decision easily. We verify the superiority of our framework through extensive experiments using real-world Malware data.
Sameer Salahudeen - One of the best experts on this subject based on the ideXlab platform.
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The Malware Author testing challenge
2014 Second Workshop on Anti-malware Testing Research (WATeR), 2014Co-Authors: Tarun Moni, Sameer Salahudeen, Anil SomayajiAbstract:Attackers regularly evaluate anti-Malware software to see whether or not their Malware will be detected. This attacker-driven anti-Malware testing is something defenders would ideally want to limit. Given that anti-Malware products must be widely distributed to be commercially viable, it is not feasible to prevent attackers from running them. Here we examine whether it may be possible to instead limit the effectiveness of attacker tests. Specifically, we present a game-theoretic model of anti-Malware testing where detection timeliness and coverage are parameters that can be adjusted by anti-Malware providers. The less coverage and the slower the response, the harder it is for attackers to determine whether their Malware will be detected-and the less protection the software provides to hosts running the anti-Malware software. While our results are preliminary, they suggest that it is clearly non-optimal for anti-Malware vendors to simply maximize coverage and detection time. As we explain, this result has significant implications for product design and (non-malicious) anti-Malware testing methodologies.