Items where Author is "Brengel, Michael"

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Number of items: 6.

Conference or Workshop Item (A Paper)

Brengel, Michael and Rossow, Christian
(2021) YarIx: Scalable YARA-based Malware Intelligence.
In: USENIX Security Symposium.
Conference: USENIX-Security Usenix Security Symposium

Brengel, Michael and Rossow, Christian
(2020) xOSSig: Leveraging OS Diversity to Automatically Extract Malware Code Signatures.
In: Botconf, Dec 1-4, 2020, (online).
Conference: UNSPECIFIED

Brengel, Michael and Rossow, Christian
(2018) Identifying Key Leakage of Bitcoin Users.
In: Proceedings of the Symposium on Research in Attacks, Intrusions and Defenses (RAID).
Conference: RAID The International Symposium on Research in Attacks, Intrusions and Defenses (was International Symposium on Recent Advances in Intrusion Detection)
(In Press)

Brengel, Michael and Rossow, Christian
(2018) MemScrimper: Time- and Space-Efficient Storage of Malware Sandbox Memory Dumps.
In: Proceedings of the Conference on Detection of Intrusions and Malware, and Vulnerability Assessment (DIMVA).
Conference: DIMVA GI International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment

Brengel, Michael and Backes, Michael and Rossow, Christian
(2016) Detecting Hardware-Assisted Virtualization.
In: Detection of Intrusions and Malware, and Vulnerability Assessment: 13th International Conference, DIMVA 2016, San Sebastián, Spain, July 7-8, 2016, Proceedings.

Yokoyama, Akira and Ishii, Kou and Tanabe, Rui and Papa, Yinmin and Yoshioka, Katsunari and Matsumoto, Tsutomu and Kasama, Takahiro and Inoue, Daisuke and Brengel, Michael and Backes, Michael and Rossow, Christian
(2016) SandPrint: Fingerprinting Malware Sandboxes to Provide Intelligence for Sandbox Evasion.
In: Research in Attacks, Intrusions, and Defenses - 19th International Symposium, RAID 2016, Paris, France, September 19-21, 2016, Proceedings.
Conference: RAID The International Symposium on Research in Attacks, Intrusions and Defenses (was International Symposium on Recent Advances in Intrusion Detection)

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