SIS PhD student Steven Ding wins prize for data mining search engine for computer security

Published: 30 September 2015

Congratulations to McGill School of Information Studies PhD student, Steven H. H. Ding, who has won 2nd prize in the Hex-Rays Plug-in Contest 2015 for "Kam1n0," a scalable data mining system for a range of computer security-related uses.

Understanding the functionalities, the characteristics and the composition of a given software is critical for malicious software analysis, software plagiarism justification, patent infringement investigation, and other computer security related tasks. It requires the analyst to disassemble the given software from machine-readable binary code to human-readable assembly code and understand the purpose of every step. This process is very time-consuming even for an experienced analyst due to the large amount of assembly codes to be reviewed. An effective and efficient assembly code clone search engine can greatly reduce the effort of this process because it enables the analysts to efficiently identify the cloned parts that have been previously analyzed from a repository.

Steven developed such a search engine called Kam1n0, which is a scalable data mining system that allows users to first index a large collection of binary files, and then search for the code clones of the given assembly functions or binary file. Kam1n0 showcases how big data research can benefit and make significant contribution to the cybersecurity and software engineering communities. Kam1n0 is an ongoing collaborative research project with the Defence Research & Development Canada (DRDC).

For more information about the project and the contest, see

Steven's supervisor is Dr. Benjamin Fung.

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