[CSEE Talk] talk: Quantum Classification of Malware, 3pm Fri 7/17, UMBC

[Tim Finin]

	     Computer Science and Electrical Engineering
	       University of Maryland, Baltimore County

		 "Quantum" Classification of Malware

			  John Seymour, UMBC

		 3:00pm Friday, 17 July 2015, ITE 366

Quantum computation has recently become an important area for security
research, with its applications to factoring large numbers and secure
communication. In practice, only one company (D-Wave) has claimed to
create a quantum computer which can solve relatively hard problems,
and that claim has been met with much skepticism. Regardless of
whether it is using quantum effects for computation or not, the D-Wave
architecture cannot run the standard quantum algorithms, such as
Grover's and Shor's. The D-Wave architecture is instead purported to
be useful for machine learning and for heuristically solving
NP-Complete problems.

We will show why the D-Wave and the machine learning problem for
malware classification seem especially suited for each other. We also
explain how to translate the classification problem for malicious
executables into an optimization problem which a D-Wave machine can
solve. Specifically, using a 512-qubit D-Wave Two processor, we show
that a minimalist malware classifier, with cross-validation accuracy
comparable to standard machine learning algorithms, can be
created. However, even such a minimalist classifier incurs a
surprising level of overhead.

Note: This is a preview of one that will be presented at DEFCON 2015
(http://bit.ly/DefCon23) in Las Vegas, 6-9 August 2015.


John Seymour is a Ph.D. student at the University of Maryland,
Baltimore County, where he performs research at the intersection of
machine learning and information security. He is mostly interested in
avoiding and helping others avoid some of the major pitfalls in
machine learning, especially in dataset preparation (seriously, do
people still use malware datasets from 1998?). In 2014, he completed
his Master's thesis on the subject of quantum computation applied to
malware analysis. He currently works at CyberPoint International, a
company which performs network and host-based machine learning,
located in Baltimore, MD.