R-D Seminar: Applications and potential of Machine Learning in Software Security

R-D Seminar: Applications and potential of Machine Learning in Software Security
March 25, 2019 11:00
CRIM (405, avenue Ogilvy, bureau 101, Montréal)

Applications and potential of Machine Learning in Software Security

SPEAKERYasir Malik, Ph.D., Assistant Professor at the College of Engineering and Computing Science at New York Institute of Technology.

ABSTRACT

Software plays an important role in the implementation and operation of critical infrastructure, industrial automation, network management and emerging IoT systems. The growing demand for system interconnectivity, interoperability and scalabilitymakes software development more complex and prone to security vulnerabilities (e.g. ransomware, malware, system exploits, etc.). Recent research has reported, that more than 90% of the cyber security attacks occur due to application vulnerabilities and lack of security controls.

The safe execution of a system depends on secure and reliable software. Recently, industry and academic researchers have shown keen interest in studying applications of machine learning and artificial intelligence to develop tools and techniques that can detect application vulnerabilities, run dynamic program analysis, automate test case generation, perform error mining and develop predictive security controls at runtime to adversaries and deliver accurate results.

In this talk, I will highlight the potential applications of Machine Learning and Deep Learning in software security, discuss current trends and future research prospects along with results from ongoing results project at CyberSecurity Intelligence Lab (CSIL) in New York Institute of Technology.

BIOGRAPHY

YASIR MALIK is an Assistant Professor at the College of Engineering and Computing Science at New York Institute of Technology. He holds a Ph.D. in Computer Science from Sherbrooke University, Canada. He has more than ten years of research and development experience. His research interests include secure software engineering, applied machine learning with applications in system security to optimize software and program analysis techniques, pattern discovery for software bug mining, and security vulnerability detection in complex systems. 

Free Conference. Registration required

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