ENEE 459D | ENEE 759D | CMSC 858Z :: Fall 2013 :: Security Data Science

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12/11: Group project reviews
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Targeted cyber attacks are increasingly sophisticated, while traditional security technologies (e.g. firewalls, password-protection systems, or other passive measures) have limited utility against skilled and persistent targeted hackers. Today, many organizations are seeking data scientists, who are able to use Big Data techniques for identifying threats and attacks. This specialized field demands skills and knowledge in multiple areas, including (a) systems, to develop the technologies needed to store and process massive data sets; (b) data analytics, to extract information from these data sets; and (c) security, to ask the right questions about cyber attacks.

ENEE 759D provides an introduction to security data science from the perspective of the security expert. The goals of the course are:

This course assumes a basic familiarity with security concepts. The course will consist of a reading/lecture/discussion component and a project component. The students will read papers on selected topics in security, summarize their strengths and weaknesses using a defined written template, and present this critique in front of the class. Specific topics that will be covered include: vulnerabilities and exploits, failures of cryptosystems, worms, denial of service, botnets, spam infrastructures, pay per install, attacks against physical infrastructure, targeted attacks, economic implications of cybercrime. The students will also form teams and work on a semester-long project to investigate a security problem of their choosing using data analysis techniques. Basic knowledge of data analysis systems and techniques will be delivered through lectures.

Course Staff

NameEmailOfficeOffice Hours
Tudor DumitraČ™ (instructor) AVW 3425 Mon 2-3 pm

Prof. Tudor DumitraČ™ is an Assistant Professor in the Electrical and Computer Engineering Department at the University of Maryland, College Park. His research focuses on applied security and distributed systems. He has real-world experience in analyzing large data sets to identify cyber attacks; for example, at Symantec Research Labs, he created the WINE platform for conducting Big Data experiments in security.

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