Latest Past Events

Cybersecurity and Machine Learning Applications

Virtual: https://events.vtools.ieee.org/m/337646

The Internet is the baseline for cyberspace, where technology infrastructure can be autonomous. It is a virtual space that can be accessed via different interconnected network devices. These devices can come from trusted or untrusted sources; therefore, the communication among these devices might be safe and/or unsafe which leads to insecure vulnerable communication in cyberspace. Security in cyberspace, namely Cyber-security can be described as a set of measures that makes cyberspace safe. Identifying threats and predicting vulnerabilities in this environment are the key components of the security mechanism. The main cause of security violations is the intrusion of an attacker into the network or the devices. Machine learning is one of the branches of artificial intelligence which can be used to increase the accuracy level for detecting threats in cyberspace to improve the system's efficiency and performance. In this talk, how machine learning can help detect and mitigate cyber threats is presented. Speaker(s): Dr. Mizanur Rahman, Virtual: https://events.vtools.ieee.org/m/337646

Protect the Privacy, Security, and Integrity of APIs

Virtual - Zoom

TeejLab’s mission: Protect the privacy, security, and integrity of APIs at a global scale by building Data Science and Artificial Intelligence driven API management solutions to help enterprises with API Governance.  Learn more about TeejLab: https://apidiscovery.teejlab.com. Contact: Mehrdad Tirandazian Abstract: Software development is becoming increasingly reliant on using third-party services accessed through APIs. These APIs connect various IT systems and processes with people to offer useful services that help us run our businesses and personal lives.  API integration may be simple, but APIs may directly or indirectly expose your IT assets and Databases to unofficial or illegitimate use. This talk aims to help students understand the overall implications of API, including information security, data management, legal risk management, and licensing costs. Speaker(s): Dr. Baljeet Baljeet of TeejLab Biography: Dr. Malhotra is an award-winning researcher known for his work in Open Source and API data management. He conceptualized the world's first "API Composition Analysis" based on source code static analysis. He founded TeejLab in 2017 and steered the team to build, API Discovery™, world's first comprehensive end-to-end API Management platform. He also established R&D unit of Black Duck Software in 2016 (acquired for US $565M by Synopsys). Previously, he was Research Director at SAP (2011-2016), Computational Scientist at the EOS Lab (2009) and Software Engineer at Satyam Computers (1999). He received a PhD in Computing Science from the University of Alberta. He was awarded NSERC (Canada) scholar in 2005, and Global Young Scientist (Singapore) in 2011. He concurrently holds Adjunct Professor positions at the University of British Columbia, University of Victoria and University of Northern BC.

Software Security and White-box Cryptography

Centennial College 941 Progress Avenue Toronto, Ontario Canada M1G 3T8 Room Number: PR A3-15

Saturday November 30th, 2019 at 2:30 p.m. Dr. Sk Md Mizanur Rahman, professor in the department of Information and Communication Engineering Technology, School of Engineering Technology and Applied Science, Centennial College, will be presenting “Software Security and White-box Cryptography”. Day & Time: Saturday November 30th, 2019 2:30 p.m. ‐ 3:30 p.m. Speaker: Dr. Sk Md Mizanur Rahman Professor, Department of Information and Communication Engineering Technology, School of Engineering Technology and Applied Science, Centennial College Organizers: IEEE Toronto Systems Chapter Location: Centennial College 941 Progress Avenue Toronto, Ontario Canada M1G 3T8 Room Number: PR A3-15 Contact: Dr. Mehrdad Tirandazian Abstract: Traditionally, cryptographic implementations are mainly designed to resist black-box attack without considering grey-box or white-box attacks. In a black-box attack model, an adversary tries to deduce the cryptographic key by knowing the algorithm and analyzing only inputs and outputs without the execution being visible. It is assumed that the adversaries know what family of cryptographic algorithm they are targeting (e.g., AES, DES, RSA, etc.), but all other details (e.g. execution time, power consumption, memory accesses) are unavailable to them. In fact, a black-box attacker treats a cryptographic implementation as a mathematical function. On the other hand, a white-box attacker is a much more powerful type of adversary and is able to analyze all parts of the implementation. Rather than just study inputs and outputs, a white-box attacker can see everything that goes on inside the implementation. For example, if the attackers are targeting cryptographic software running on, say, a PC or mobile phone, then they can execute that software inside a debugger and examine memory and register values during the execution. In a grey-box attack scenario, it is assumed that an attacker has limited knowledge of the security assets and methods (more that a black-box attacker) but does not have access to source code or detail design information. Therefore, based on the severity of an attack, the above attack models can be categorized as white-box > grey-box > black-box. In this presentation, a brief discussion will be given on white-box implementations of the existing cryptographic algorithms. Biography: Dr. Sk Md Mizanur Rahman is a fulltime professor in the department of Information and Communication Engineering Technology, School of Engineering Technology and Applied Science, Centennial College. Prior to his current appointment, he worked as an Assistant Professor for five years in the Information Systems Department at the College of Computer and Information Sciences, King Saud University. He also worked for several years in cryptography and security engineering in the high-tech industry in Ottawa, Canada. In addition, he worked as a postdoctoral researcher for several years at the University of Ottawa, University of Ontario Institute of Technology (UOIT), and University of Guelph, Canada. He completed a Ph.D. in Engineering (Major: Cybersecurity Risk Engineering) in the Laboratory of Cryptography and Information Security, Department of Risk Engineering, University of Tsukuba, Japan, in 2007. The Information Processing Society Japan (IPSJ) awarded Dr. Rahman its Digital Courier Funai Young researcher Encouragement Award for his excellent contributions to IT security research. He is awarded a Gold Medal for distinction in his undergraduate and graduate programs. He has published approximately one-hundred peer reviewed journal and conference research articles. Also, he has a granted industrial patent (US Patent) on cryptographic key generation and protection. Dr. Rahman’s primary research interests are cryptographic protocol design, white-box cryptography, software and network security, reverse engineering and ethical hacking, privacy enhancing technology, sensor and mobile ad-hoc network security, cloud and the Internet of Things (IoT) security, machine learning in information security.