ACM CODASPY 2017
3rd ACM International Workshop on Security and Privacy Analytics (IWSPA 2017)
Friday, March 24, 2017
Co-located with ACM CODASPY 2017 at Scottsdale, Arizona, USA
Increasingly, sophisticated techniques from machine learning, data mining, statistics and natural language processing are being applied to challenges in security and privacy fields. However, experts from these areas have no medium where they can meet and exchange ideas so that strong collaborations can emerge, and cross-fertilization of these areas can occur. Moreover, current courses and curricula in security do not sufficiently emphasize background in these areas and students in security and privacy are not emerging with deep knowledge of these topics. Hence, we propose a workshop that will address the research and development efforts in which analytical techniques from machine learning, data mining, natural language processing and statistics are applied to solve security and privacy challenges (“security analytics”). Submissions of papers related to methodology, design, techniques and new directions for security and privacy that make significant use of machine learning, data mining, statistics or natural language processing are welcome. Furthermore, submissions on educational topics and systems in the field of security analytics are also highly encouraged.
Short Submission Guidelines:
Papers must be at most 8 pages in length total and use the ACM CODASPY template. All submissions must describe original research, not published nor currently under review for another workshop, conference, or journal.Submission implies the willingness of at least one author to attend the workshop and present the paper. A limited number of high-quality submissions may be selected for publication in a special issue of a journal. All papers must be submitted electronically via the Easychair system.
ALL PAPERS MUST BE SUBMITTED USING EASYCHAIR SUBMISSION SITE
Paper Submission Deadline:
December 16, December 19, 2016, 11.59pm anywhere on earth
Acceptance Notification: January 9, 2017
Camera Ready Submission Deadline: January 24, 2017
The proceedings of IWSPA 2017 will be available in the ACM Digital Library.
Find the agenda to the 3rd International Workshop for Security and Privacy Analytics HERE!
Invited Keynote Speakers
Invited Keynote 1:
Speaker: Shambhu Upadhyaya, SUNY Buffalo
Invited Keynote 2:
Speaker: Patrick McDaniel, Pennsylvania State University
Feature Cultivation in Privileged Information-augmented Detection - Z. Berkay Celik (Pennsylvania State University); Patrick McDaniel (Pennsylvania State University); Rauf Izmailov (Vencore Labs)
Accepted Papers (Full and Short)
The following are the accepted full and short papers for the 3rd IWSPA 2017.
Accepted Full Papers:
(a) Predicting Exploitation of Disclosed Software Vulnerabilities Using Open-source Data - Benjamin Bullough (MIT); Anna Yanchenko (MIT); Christopher Smith (MIT); Joseph Zipkin (MIT)
(b) Fast Feature Extraction and Malicious URL Detection - Rakesh Verma (University of Houston); Avisha Das (University of Houston)
(c) Non-interactive (t, n)-Incidence Counting from Differentially Private Indicator Vectors - Mohammad Alaggan (INRIA); Mathieu Cunche (INRIA); Marine Minier (INSA Lyon)
(d) EMULATOR vs REAL PHONE: Android Malware Detection Using Machine Learning - Mohammed Alzaylaee (Queen's University Belfast); Suleiman Yerima (Queen's University Belfast); Sakir Sezer (Queen's University Belfast)
Accepted Short Papers:
(a) Model-based cluster analysis for identifying suspicious activity sequences in software - Hemank Lamba (CMU); Thomas Glazier (CMU); Bradley Schmerl (CMU); Javier Camar Moreno (CMU); David Garlan (CMU); Juergen Pfeffer (TU Munich)
(b) An Internal/Insider Threat Score for Data Loss Prevention And Detection - Kyrre Wahl Kongsgård (Norwegian Defense Research Establishment); Nils Agne Nordbotten (Norwegian Defense Research Establishment); Federico Mancini (Norwegian Defense Research Establishment); Paal E. Engelstad (Norwegian Defense Research Establishment)
(c) Analysis of Causative attacks against SVMs Learning from Data Streams -
Cody Burkard (University of Washington, Bothell); Brent Lagesse (University of Washington, Bothell)
(d) Identifying Key Cyber-Physical Terrain - Brian Thompson (MITRE Corporation); Richard Harang (Invincea Inc.)
(e) MCDefender: Toward Effective Cyberbullying Defense in Mobile Online Social Networks - Nishant Vishwamitra (Clemson University); Xiang Zhang (Clemson University); Hongxin Hu (Clemson University); Feng Luo (Clemson University)