Accepted Papers

Improving Malware Detection: Bridging the Static/Dynamic Gap
Blake Anderson, Curtis Storlie and Terran Lane.
On the Effectiveness of using State-of-the-art Machine Learning Techniques to Launch Cryptographic Distinguishing Attacks
Jung-Wei Chou, Shou-De Lin and Chen-Mou Cheng.
Robust Detection of Comment Spam Using Entropy Rate
Alex Kantchelian, Justin Ma, Ling Huang, Sadia Afroz, Anthony Joseph and J. D. Tygar.
Learning Stateful Models for Network Honeypots
Tammo Krueger, Hugo Gascon, Nicole Krämer and Konrad Rieck.
An information theoretic framework for web inference detection
Hoi Le and Rei Safavi-Naini.
Understanding the Time-series Behavioral Characteristics of Evolutionally Advanced Email Spammers
Yukiko Sawaya, Ayumu Kubota and Akira Yamada.
Early Detection of Malicious Behavior in JavaScript Code
Kristof Schütt, Marius Kloft, Alexander Bikadorov and Konrad Rieck.
Autonomous Learning for Detection of JavaScript Attacks: Vision or Reality?
Guido Schwenk, Alexander Bikadorov, Tammo Krueger and Konrad Rieck.
Tracking concept drift in malware families
Anshuman Singh, Andrew Walenstein and Arun Lakhotia.
Nonparametric Semi-Supervised Learning for Network Intrusion Detection: Combining Performance Improvements with Realistic In-Situ Training
Christopher Symons and Justin Beaver.

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