IEEE Miami Section

IEEE

Extending Detection with Forensic Information

 

 

Extending Detection with Forensic Information

Invited Lecture by

Berkay Celik

Date: Dec 7, 2016
Time: 03:00 PM
Address: Department of Electrical and Computer Engineering Department, Florida International University, 10555 W. Flagler Street, Miami, Florida 33174
Room: EC-3350

Abstract:For over a quarter century, security-relevant detection has been driven by models learned from input features collected from real or simulated environments. An artifact (e.g., network event, potential malware sample, suspicious email) is deemed malicious or non-malicious based on its similarity to the learned model at run-time. However, the training of the models has been historically limited to only those features available at run time. This talk covers an alternate model construction approach that trains models using forensic “privileged” information–features available at training time, but not at runtime–to improve the accuracy and resilience of detection systems. In particular, we adapt and extend recent advances in knowledge transfer, model influence, and distillation to enable the use of forensic data in a range of security domains. Such techniques open the door to systems that can integrate forensic data directly into detection models, and therein provide a means to fully exploit the information available about past security-relevant events.

Bio: Berkay Celik is a PhD student in Department of Electrical Engineering and Computer Science at the Pennsylvania State University working with Prof. Patrick McDaniel and a member of the Systems and Internet Infrastructure Security Laboratory (SIIS). His research focuses on solving privacy and security problems using system techniques, machine learning, and probability/statistics. He obtained his MS degree in Computer Science at the Pennsylvania State University. During his MS. studies, he worked with Prof. George Kesidis and Prof. David J. Miller on NSF NeTSE Unsupervised Flow-Based Clustering project. His research focused on network security and design of learning algorithms. Moreover, he worked under the direction of Prof. Sema Oktug at Istanbul Technical University focusing on practical security problems.

 

 

For seat reservation and more information please contact IEEE Miami Section staff at kmoha023@fiu.edu

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