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pro vyhledávání: '"Zak, Richard A."'
Autor:
Raff, Edward, Fleshman, William, Zak, Richard, Anderson, Hyrum S., Filar, Bobby, McLean, Mark
Recent works within machine learning have been tackling inputs of ever-increasing size, with cybersecurity presenting sequence classification problems of particularly extreme lengths. In the case of Windows executable malware detection, inputs may ex
Externí odkaz:
http://arxiv.org/abs/2012.09390
Autor:
Raff, Edward, Zak, Richard, Munoz, Gary Lopez, Fleming, William, Anderson, Hyrum S., Filar, Bobby, Nicholas, Charles, Holt, James
Yara rules are a ubiquitous tool among cybersecurity practitioners and analysts. Developing high-quality Yara rules to detect a malware family of interest can be labor- and time-intensive, even for expert users. Few tools exist and relatively little
Externí odkaz:
http://arxiv.org/abs/2009.03779
Autor:
Raff, Edward, Fleming, William, Zak, Richard, Anderson, Hyrum, Finlayson, Bill, Nicholas, Charles, McLean, Mark
N-grams have been a common tool for information retrieval and machine learning applications for decades. In nearly all previous works, only a few values of $n$ are tested, with $n > 6$ being exceedingly rare. Larger values of $n$ are not tested due t
Externí odkaz:
http://arxiv.org/abs/1908.00200
Security Analysts that work in a `Security Operations Center' (SoC) play a major role in ensuring the security of the organization. The amount of background knowledge they have about the evolving and new attacks makes a significant difference in thei
Externí odkaz:
http://arxiv.org/abs/1905.02497
As machine-learning (ML) based systems for malware detection become more prevalent, it becomes necessary to quantify the benefits compared to the more traditional anti-virus (AV) systems widely used today. It is not practical to build an agreed upon
Externí odkaz:
http://arxiv.org/abs/1806.04773
Autor:
Raff, Edward, Fleshman, William, Zak, Richard, Anderson, Hyrum S., Filar, Bobby, McLean, Mark
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 35:9386-9394
Recent works within machine learning have been tackling inputs of ever-increasing size, with cybersecurity presenting sequence classification problems of particularly extreme lengths. In the case of Windows executable malware detection, inputs may ex
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Autor:
Raff, Edward, Zak, Richard, Cox, Russell, Sylvester, Jared, Yacci, Paul, Ward, Rebecca, Tracy, Anna, McLean, Mark, Nicholas, Charles
Publikováno v:
Journal of Computer Virology and Hacking Techniques; February 2018, Vol. 14 Issue: 1 p1-20, 20p
Publikováno v:
Point of Care; Jun2017, Vol. 16 Issue 2, p102-104, 3p, 3 Charts, 1 Graph
Publikováno v:
Seminars in Liver Disease; 1983, Vol. 3 Issue 2, p132-145, 14p