The cyber world is plagued with ever-evolving malware that readily infiltrate all defense
mechanisms, operate viciously unbeknownst to the user, and surreptitiously exfiltrate …

Anti-virus vendors are confronted with a multitude of potentially malicious samples today.
Receiving thousands of new samples every day is not uncommon. The signatures that …

In this work we introduce malware detection from raw byte sequences as a fruitful research
area to the larger machine learning community. Building a neural network for such a …

Microarchitectural timing channels expose hidden hardware states though timing. We survey
recent attacks that exploit microarchitectural features in shared hardware, especially as they …

Machine learning techniques are widely used in addition to signatures and heuristics to
increase the detection rate of anti-malware software, as they automate the creation of …

The execution of malware in an instrumented sandbox is a widespread approach for the
analysis of malicious code, largely because it sidesteps the difficulties involved in the static …

Botnets are now recognized as one of the most serious security threats. In contrast to
previous malware, botnets have the characteristic of a command and control (C&C) channel …

Methods, systems, and media for detecting covert malware are provided. In accordance with
some embodiments, a method for detecting covert malware in a computing environ ment is …

The volume and the sophistication of malware are continuously increasing and evolving.
Automated dynamic malware analysis is a widely-adopted approach for detecting malicious …

2009-12-05 Assigned to THE TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF
NEW YORK reassignment THE TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF …