It is our great pleasure to welcome you to the 4th ACM Workshop on Artificial Intelligence & Security — AISec’2011. This year’s workshop continues on its original mission of stimulating collaboration and cross-pollination between the Security & Privacy and Artificial Intelligence research communities. We are delighted to once again be co-located with the premier ACM Computer and Communication Security (CCS 2011) conference.
The call for papers attracted 18 high quality submissions spanning North & South America, Europe, the Middle East & Asia, and representing both academia and industry. Of these submissions, the Program Committee accepted 7 research papers and 3 position papers, making for a wonderful program that will bring together leading researchers with backgrounds in both Security & Privacy and AI.
This year’s ACM AISec will cover such topics as identifying workers hired online for web service abuse, malware and malicious webpage detection, probabilistic attack planning, and intrusion analysis. In addition the program includes an exciting keynote by Prof. Dawn Song of UC Berkeley who is an internationally recognized leader in Security & Privacy research with extensive experience applying state-of-the-art techniques from Machine Learning to exposing vulnerabilities in real-world systems and to developing robust defenses.
These proceedings feature an invited paper, Adversarial Machine Learning, following from the AISec’2010 keynote delivered by Prof. J. D. Tygar (UC Berkeley), whose work investigates Machine Learning through the lens of Security & Privacy, an important topic also covered by one of this year’s position papers.