Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Jee, Kangkook"'
Autor:
Mukherjee, Kunal, Wiedemeier, Joshua, Wang, Tianhao, Kim, Muhyun, Chen, Feng, Kantarcioglu, Murat, Jee, Kangkook
The opaqueness of ML-based security models hinders their broad adoption and consequently restricts transparent security operations due to their limited verifiability and explainability. To enhance the explainability of ML-based security models, we in
Externí odkaz:
http://arxiv.org/abs/2306.00934
Autor:
Gao, Peng, Xiao, Xusheng, Li, Ding, Jee, Kangkook, Chen, Haifeng, Kulkarni, Sanjeev R., Mittal, Prateek
The need for countering Advanced Persistent Threat (APT) attacks has led to the solutions that ubiquitously monitor system activities in each enterprise host, and perform timely abnormal system behavior detection over the stream of monitoring data. H
Externí odkaz:
http://arxiv.org/abs/1903.08159
Autor:
Gao, Peng, Xiao, Xusheng, Li, Zhichun, Jee, Kangkook, Xu, Fengyuan, Kulkarni, Sanjeev R., Mittal, Prateek
The need for countering Advanced Persistent Threat (APT) attacks has led to the solutions that ubiquitously monitor system activities in each enterprise host, and perform timely attack investigation over the monitoring data for uncovering the attack
Externí odkaz:
http://arxiv.org/abs/1810.03464
Autor:
Gao, Peng, Xiao, Xusheng, Li, Ding, Li, Zhichun, Jee, Kangkook, Wu, Zhenyu, Kim, Chung Hwan, Kulkarni, Sanjeev R., Mittal, Prateek
Recently, advanced cyber attacks, which consist of a sequence of steps that involve many vulnerabilities and hosts, compromise the security of many well-protected businesses. This has led to the solutions that ubiquitously monitor system activities i
Externí odkaz:
http://arxiv.org/abs/1806.09339
Autor:
Gao, Peng, Xiao, Xusheng, Li, Zhichun, Jee, Kangkook, Xu, Fengyuan, Kulkarni, Sanjeev R., Mittal, Prateek
The need for countering Advanced Persistent Threat (APT) attacks has led to the solutions that ubiquitously monitor system activities in each host, and perform timely attack investigation over the monitoring data for analyzing attack provenance. Howe
Externí odkaz:
http://arxiv.org/abs/1806.02290
Autor:
Jee, Kangkook
Data Flow Tracking (DFT) is a technique broadly used in a variety of security applications such as attack detection, privacy leak detection, and policy enforcement. Although effective, DFT inherits the high overhead common to in-line monitors which s
Akademický článek
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Autor:
Mukherjee, Kunal, Wiedemeier, Joshua, Wang, Tianhao, Kim, Muhyun, Chen, Feng, Kantarcioglu, Murat, Jee, Kangkook
The black-box nature of complex Neural Network (NN)-based models has hindered their widespread adoption in security domains due to the lack of logical explanations and actionable follow-ups for their predictions. To enhance the transparency and accou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5e8390269eeaffec9e78e772ea4e75d4
http://arxiv.org/abs/2306.00934
http://arxiv.org/abs/2306.00934
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
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K zobrazení výsledku je třeba se přihlásit.
Autor:
Pomonis, Marios, Petsios, Theofilos, Jee, Kangkook, Polychronakis, Michalis, Keromytis, Angelos D.
Publikováno v:
ACM International Conference Proceeding Series; 12/8/2014, p416-425, 10p
