7th ACM Workshop on Artificial Intelligence and Security
with the 21st ACM Conference on Computer and Communications (CCS)
November 7, 2014, The Scottsdale Plaza Resort, Scottsdale, Arizona, USA.


  • About


The Proceedings of AISec 2014 are available here.

Workshop Program

Welcome Remarks (08:45 - 09:00)

Keynote Address (09:00 - 10:00) (chair Benjamin Rubinstein)

  • Battista Biggio (Univ. of Cagliari, Italy), On Learning and Recognition of Secure Patterns
  • [slides]

Session 1: Privacy, Learning and Security - Part I (10:00 - 10:30) (chair Benjamin Rubinstein)

  • Andrew Newell, Rahul Potharaju, Luojie Xiang and Cristina Nita-Rotaru, On the Practicality of Integrity Attacks on Document-Level Sentiment Analysis

Coffee Break (10:30 - 11:00)

Session 2: Privacy, Learning and Security - Part II (11:00 - 12:30) (chair Rachel Greenstadt)

  • Sadia Afroz, Rekha Bachwani, Edwin Dauber, Ling Huang, Anthony Joseph, Alex Kantchelian, Brad Miller, Michael Carl Tschantz and J. D. Tygar, Adversarial Active Learning
  • Francesco Alda and Hans Simon, Randomized Response Schemes, Privacy and Usefulness
  • Battista Biggio, Konrad Rieck, Davide Ariu, Christian Wressnegger, Igino Corona, Giorgio Giacinto and Fabio Roli, Poisoning Behavioral Malware Clustering
  • Sebastian Abt and Harald Baier, A Plea for Utilising Synthetic Data when Performing Machine Learning Based Cyber-Security Experiments

Lunch (12:30 - 14:00)

Session 3: Intrusion and Anomaly Detection (14:00 - 15:30) (chair Battista Biggio)

  • Igino Corona, Davide Maiorca, Davide Ariu and Giorgio Giacinto, Lux0R: Detection of Malicious PDF-embedded JavaScript code through Discriminant Analysis of API References
  • Pratyusa K Manadhata, Sandeep Yadav, Prasad Rao and William Horne, Detecting Malicious Domains via Graph Inference
  • Sean Whalen, Nathaniel Boggs and Sal Stolfo, Model Aggregation for Distributed Content Anomaly Detection
  • Xiang Junlong, Magnus Westerlund, Dušan Sovilj and Göran Pulkkis, Using Extreme Learning Machine for Intrusion Detection in a Big Data Environment

Coffee Break (15:30 - 16:00)

Session 4: Novel Applications (16:00 - 17:00) (chair Rachel Greenstadt)

  • Sruti Bhagavatula, Christopher Dunn, Chris Kanich, Minaxi Gupta and Brian Ziebart, Leveraging Machine Learning to Improve Unwanted Resource Filtering
  • Blake Anderson, Curtis Storlie, Micah Yates and Aaron McPhall, Automating Reverse Engineering with Machine Learning Techniques
  • Xiao Wang and Patrick Tague, Non-Invasive User Tracking via Passive Sensing: Privacy Risks of Time-Series Occupancy Measurement