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Malware 2018 Best Paper Award

Malware 2018
Best Paper Award - Research Track

Presented to

William Fleshman, Richard Zak and Mark McLean

Laboratory for Physical Sciences, USA

and

Edward Raff and Charles Nicholas

Booz Allen Hamilton and

University of Maryland, Baltimore County, USA

 

In recognition to their contributions to the Field of Information and Systems Security

and the quality and timeliness of their work as embodied in the manuscript:

 

“Static Malware Detection & Subterfuge: Quantifying the Robustness of Machine Learning and Current Anti-Viruscalable Encryption Fingerprinting in Dynamic Malware Trace" 

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 7:00 - 9:00 AM

Registration & Breakfast

 9:00 - 9:15 AM

Welcome Remarks - Dr. Fernando Colon Osorio, General Program Chair

 9:15 - 10:15 AM

 

Keynote - "An Overview of Adversarial Learning with Recent Results on Test-Time Evasion Attacks and Defense"

by

Prof. George Kesidis, CSE and EE Departments, The Pennsylvania State University, University Park, PA, USA

Abstract:  For many years, cyber security has faced a complex "big data" problem. Moreover,  many enterprises are very sensitive to false negatives and demand timely detection of new threats. As a result, machine learning systems have been applied, e.g., to keep pace with polymorphic/metamorphic malware. Machine learning systems are also ubiquitously used in cyber physical systems for safe and efficient operations. In the past decade, researchers have studied how machine learning systems themselves can be attacked. In this talk, we will first review different types of adversarial learning attacks: data poisoning, test-time evasion, and reverse engineering. Focusing on test-time evasion, we review recent work involving deep neural network classifier of image datasets (several researchers have proposed using image-like representations of malware for purposes of detection). We propose both a state-of-the-art defense and white-box attack. The talk concludes with a discussion of current and future research directions on adversarial learning.

10:15 - 10:30 AM

Break

10:30 - 12:30 PM:

Session # 1:  Measurement - the effectiveness of Anti-Malware techniques

Session Chair: Richard R. Brooks

1570474608 - "Static Malware Detection & Subterfuge: Quantifying the Robustness of Machine Learning and Current Anti-Virus" by William Fleshman, Richard Zak and Mark McLean, Laboratory for Physical Sciences, USA; Edward Raff, Booz Allen Hamilton & University of Maryland, Baltimore County, USA; Charles Nicholas, University of Maryland, Baltimore County, USA).


1570487993 - "Is Eval () Evil: A Study of JavaScript in PDF Malware?" by Sylvain P. Leblanc, Royal Military College of Canada, Canada; Antoine Lemay, École Polytechnique de Montréal, Canada.


1570487949
- "An In-Depth Study of Open-Source Command and Control Frameworks" by Julien Piet ,Ecole Polytechnique, France; Blake Anderson and David McGrew Cisco Systems, Inc., USA

12:30 - 01:30 PM

Lunch

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