Browsing Institute for Information Security & Privacy (IISP) by Subject "Machine learning"
Now showing items 1-3 of 3
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Automated In-memory Malware/rootkit Detection via Binary Analysis and Machine Learning
(Georgia Institute of Technology, 2018-02-16)A prominent technique for detecting sophisticated malware consists of monitoring the execution behavior of each binary to identify anomalies and/or malicious intent. Hooking and emulation are two primary mechanisms that ... -
Automatic Feature Engineering: Learning to Detect Malware by Mining the Scientific Literature
(Georgia Institute of Technology, 2017-09-29)The detection of malware and network attacks increasingly relies on machine learning techniques, which utilize multiple features to separate the malicious and benign behaviors. The effectiveness of these techniques primarily ... -
Automating the Discovery of Censorship Evasion Strategies
(Georgia Institute of Technology, 2020-09-11)Researchers and censoring regimes have long engaged in a cat-and-mouse game, leading to increasingly sophisticated censorship techniques and methods to evade them. Unfortunately, censors have long had an inherent advantage ...