Annual Computer Security Applications Conference 2015

Full Program »

M3. Security and Privacy Analysis for Next Generation Malware

Monday, 7 December 2015
08:30 - 12:00

Salon 8

[This is a full day session.]

In the last couple of years, security and privacy experts in malware cyber attacks have identified a >2,000% increase of malware behavior over the Internet.  The main motivation of malware is to steal personal and proprietary data of individuals and enterprises.  In order to succeed, malware developers has started to make their programs evasive.  Evasive malware is capable of tricking most well known malware analyses.  Evasive malware is becoming increasingly more advanced and sophisticated, while spreading over the Internet very rapidly.  On the other hand, security and privacy experts are struggling to identify new malware in order to prevent cybercrimes.  The Security and Privacy Analysis for Next Generation Malware course prepares the audience by teaching the next generation of malware trends and the security and privacy impact that new malware can have on IT professionals and their organizations as well as individuals across the world.  The course will also introduce the current state of the art on how researchers in the industry and academia are evolving their analyses against this new generation of malware.

Prerequisites. None

Outline:

  1. Malware Evolution
    • Background of malware analysis
    • First generation based sandboxes and signature gateways
    • Security and privacy issues over the Internet
  2. New Malware Treats and Analyses
    • Top five malware trends on the horizon on the Internet
    • New analyses and strategies IT professionals should be on the lookout
    • Global impact of evasive malware on organizations and individuals
  3. Malware Analysis and Detection
    • Leveraging different techniques for malware analysis and detection
    • Static analysis, dynamic analysis and machine learning for automatic detection of malware
  4. Future of Malware Analysis
    • Toward automated detection of evasive malware
    • Current state of the art

About the Instructor:

Dr. Paolina Centonze, PhD, is a Professor in the Computer Science Department at Iona College in New Rochelle, NY.  Her areas of research include Language-based Security and Mobile Computing.  Dr. Centonze is also actively collaborating with researchers at IBM's Thomas J. Watson Research Center, Yorktown Heights, New York in the area of Program Analysis applied to Mobile Security.  She has published extensively at numerous conferences worldwide, such as ISSTA, ECOOP, ACSAC, MDM and MOBILESoft.  She is a co-author of many scientific publications and a co-inventor of 8 patents and 12 patent applications.  Dr. Centonze received her Ph.D. in Mathematics and M.S. degree in Computer Science from New York University, Polytechnic School of Engineering, Brooklyn, New York, in 2008 and her B.S. degree in Computer Science from St. John's University, Queens, New York in 2003.

Dr. Centonze's home page is:

http://www.iona.edu/Academics/School-of-Arts-Science/Departments/Computer-Science/Faculty-Staff/Paolina-Centonze.aspx

 

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