Systems

September 29, 2015 at 1:30 p.m. Dr. Wei Shi, Assistant professor at the faculty of Business and I.T. in the University of Ontario Institute of Technology and an adjunct professor in the School of Computer Science at Carleton University, will be presenting “Geographic Partitioning Techniques for the Anonymization of Health Care Data (Big data and advanced analytics methods to ensure privacy)”. Speaker: Dr. Wei Shi Assistant professor at the faculty of Business and I.T. in the University of Ontario Institute of Technology and an adjunct professor in the School of Computer Science at Carleton University. Day & Time: Tuesday, September 29, 2015 1:30 p.m. – 2:30 p.m. Location: Eric Palin Hall Ryerson University Room: EPH207 87 Gerrard Street East, Toronto, Ontario Click here to see the Map – Look for EPH Organizer: IEEE Toronto Systems Chapter Contact: E-mail: Alexei Botchkarev Registration: Registration is free, but space is limited. Please register via this link: http://tinyurl.com/systemsEvent Abstract: Hospitals and health care organizations collect large amounts of detailed health care data that is in high demand by researchers. Thus, the possessors of such data are in need of methods that allow for this data to be released without compromising the confidentiality of the individuals to whom it pertains. As the geographic aspect of this data is becoming increasingly relevant for research being conducted, it is important for an anonymization process to pay due attention to the geographic attributes of such data. In this talk, a novel system for health care data anonymization is presented. At the core of the system is the aggregation of an initial regionalization guided by the use of a Voronoi diagram. We conduct a comparison with another geographic-based system of anonymization, GeoLeader. We show that our system is capable of producing results of a comparable quality with a much faster running time. Biography: Dr. Wei Shi is an assistant professor at the faculty of Business and I.T. in the University of Ontario Institute of Technology and an adjunct professor in the School of Computer Science at Carleton University. Dr. Shi received her BEng. in Computer Engineering from Harbin Institute of Technology in China and MSC and Ph.D. in Computer Science from Carleton University in Ottawa, Canada. Her research interests include big data analytics, algorithm design and analysis for distributed environments such as the cloud, wireless sensor network, mobile network as well as vehicular network. She has published over 40 technical papers in top conferences and journals. Her research work is supported by IBM and Natural Sciences and Engineering Research Council (NSERC) of Canada.

October 22, 2015 at 12:00 p.m. Dr. Ebrahim Bagheri, Associate Professor and the Director for the Laboratory for Systems, Software and Semantics (LS3) at Ryerson University, will be presenting “Modeling Semantics of Content on Twitter (What did you mean when you said Yoyo!)”. Speaker: Dr. Ebrahim Bagheri Associate Professor and the Director for the Laboratory for Systems, Software and Semantics (LS3) at Ryerson University. Day & Time: Thursday, October 22, 2015 12:00 p.m. – 1:00 p.m. Location: Kerr Hall West 379 Victoria Street, Toronto, Ontario Ryerson University Room: KHW057 Map – http://www.ryerson.ca/maps – Look for KHW Organizer: IEEE Systems Chapter – Toronto Section Contact: E-mail: Alexei Botchkarev Registration: Registration is free, but space is limited. Please register via this link: http://tinyurl.com/systems-Oct-22 Abstract: The microblogging service, Twitter, has gained wide popularity with over 300M active users and over 500M tweets per day. The unique characteristic of Twitter, only allowing short length messages to be communicated, has brought about interesting changes to how information is expressed and communicated by the users, i.e., the semantics of information when expressed on Twitter differ from when expressed on other medium. For instance, the word ‘metal’ when observed on Twitter carries a different semantic meaning, most likely referring to heavy metal music, as opposed to when used in other contexts where its predominant sense is the metal material. In this talk, I will discuss how the meaning and senses of words can be captured and modeled on Twitter to enable better and more efficient search, retrieval and recommendation of content. Biography: Ebrahim Bagheri is an Associate Professor and the Director for the Laboratory for Systems, Software and Semantics (LS3) at Ryerson University, and has been active in the areas of the Semantic Web and Software Engineering. He was one of the research theme leaders of the national project on Radiation Emission Monitoring at the National Research Council Canada and was responsible for leading the development of the Semantic Web and Knowledge Engineering components of that project. In 2011, he co-chaired the Canadian Semantic Web Conference in Vancouver, BC (http://ceur-ws.org/Vol-774/). His work on Semantic-Driven Information Extraction has resulted in two provisionally patented technologies namely Denote and Derive. Denote is a semantic annotation platform based on Linked Open Data and Derive is an extensible architecture for unsupervised knowledge extraction and object (concept and property-value pair) population from the Web. He has been involved in projects that encompass the use of Semantic Web technologies in the areas of e-commerce and business process modeling funded by NSERC, AIF and IBM. Over the past 5 years, he has led projects worth over $5M CAD including various NSERC research and development projects with over 12 industrial partners. He is a senior member of IEEE, an IBM Faculty Fellow and a member of PEO.

Monday November 13, 2017 at 3:00 p.m. Dr. Shahryar Rahnamayan will be presenting “Fingerprints of Black-Box Optimization in Science and Engineering”. Day & Time: Monday November 13, 2017 3:00 p.m. – 5:00 p.m. Speaker: Dr. Shahryar Rahnamayan Location: Room ENG 210 George Vari Engineering and Computing Centre 245 Church Street, Toronto, ON M5B 1Z4 Contact: Mehrdad Tirandazian Organizers: IEEE Toronto Systems Chapter Abstract: In this research seminar, the speaker will discuss his recent optimization research works and accomplishments, categorized in the following two main groups of contributions: theoretical/developmental and practical. The first group will cover his contributions in large-scale optimization, opposition-based computation, many-objective optimization, image-based large-scale visualization and interaction, incremental cooperative coevolution, micro-differential evolution, 3D visualization of many-objective Pareto-front, innovation, preserving constraint handling, decision making in high-dimensional objective space, and multi-modal optimization. In the practical category, the speaker will explain several real-world applications to demonstrate contributions of optimization in medical image processing, renewable energy systems, forensic science, vibration, scheduling, and wireless sensors network. In this talk, the essential role of complex black-box optimization in since and engineering will be highlighted. This seminar would be beneficial for faculty members and students who conduct “research in optimization” or “optimization in research”. Biography: Dr. Shahryar Rahnamayan received his B.Sc. and M.Sc. degrees both with honors in software engineering. In 2007, he received his Ph.D. degree in the field of evolutionary computation from the University of Waterloo (UW), Canada. Since 2008, he is an associate professor in the Department of Electrical, Computer, and Software Engineering, University of Ontario Institute of Technology. He is a faculty member of the BEACON Center (an NSF center for study of evolution in action) since 2014; and also adjunct professor at the Systems Design Engineering, University of Waterloo, since 2009. Dr. Rahnamayan was a postdoctoral fellow at the School of Engineering, Simon Fraser University, in 2008. His research is mainly focused on evolutionary computation and its real-world applications. Dr. Rahnamayan has 139 peer-reviewed publications mostly in evolutionary optimization areas, which received 3700 citations (h-index: 24); one of his high-impact journal papers in optimization ranked 23rd out of 194,000 in term of number of citations, 2008-2017. Dr. Rahnamayan co-founded Segasist Technologies Inc., which develops segmentation solutions for medical image analysis and radiation planning; the company raised over $2M and secured the FDA approval. Dr. Rahnamayan has been awarded several prestigious research grants, including, NSERC Discovery Grant and Applied Research and Commercialization Initiative Fund. He recently conducted research as a visiting associate professor at Michigan State University (MI, USA) for two years (2014-2016). Dr. Rahnamayan is an active reviewer for more than thirty international conference and journal papers. He has been awarded the UOIT Research Excellence Award in 2017.

Friday Nov 16, 2018 at 9:30 a.m. Dr. Ali Hooshyar, Editor of IEEE Transactions on Power Delivery & IEEE Transactions on Smart Grid, will be presenting “Next-Generation Protection Technologies for Power Systems: The Quest for Resilience”. Day & Time: Friday November 16th, 2018 9:30 a.m. ‐ 11:00 a.m. Speaker: Dr. Ali Hooshyar Editor of IEEE Transactions on Power Delivery, IEEE Transactions on Smart Grid Organizers: IEEE Toronto Systems Chapter Location: Ryerson University, Department of Computer Science, Room 288 George Vari Engineering and Computing Centre 245 Church Street, Toronto, ON – M5B 2K3 Contact: Mehrdad Tirandazian Abstract: The resilience of power systems is known as their ability to predict, adapt to and quickly recover from various disruptive events. Power grids have always been subject to such events, but in the last few years, the frequency and severity of large-scale disruptions have increased due to the growing number of major climate disasters. In addition, the increasing reliance on the cyber layer of smart grids has diversified the causes of major disruptions. Attackers can exploit the grid’s cyber vulnerabilities to manipulate protection and control commands, as was the case with the 2015 and 2016 blackouts in Ukraine. These recent developments have intensified the efforts to improve grid resilience. Large-scale disruptions usually involve abnormal currents and voltages—to which the protection system of the grid is expected to respond—, or involve trip commands to circuit breakers, which can originate from protective devices. Furthermore, some of the strategies to increase grid resilience alter the short-circuit behavior of the grid. As a result, substantial upgrades in the protection system are necessary to meet the demands for higher grid resilience. This talk will highlight some of the major changes required to prevent large-scale disruptive events or improve the grid operation during such events. Various protection system challenges that the speaker has unveiled are discussed, followed by the proposed solutions. Two of these challenges are elaborated in detail: first, this talk focuses on the relation between grid resilience and protection of microgrids, which can ensure the continuity of power supply during major disruptions in the transmission system. The performance of existing commercial relays for microgrid protection is demonstrated, and the requirements to eliminate the shortcomings of these relays are identified. Afterwards, this talk shows how cyber-attacks on communication-assisted protection schemes can lead to wide-area disruptions throughout the grid. The vulnerabilities of such schemes and a new approach to address them are discussed. Biography: Ali Hooshyar received the Ph.D. degree in electrical engineering from the University of Waterloo in 2014. He joined the Department of Electrical and Computer Engineering at the University of Toronto in 2018. He was with the Electrical Engineering and Computer Science Department, York University, Toronto, from 2015 to 2018. His research interests include protection and control of renewable energy systems and smart grids. Dr. Hooshyar is an Editor of the IEEE Transactions on Power Delivery and the IEEE Transactions on Smart Grid.

Monday April 1st, 2019 at 7:30 p.m. Aislin O’Hara of O’Hara & Associates Consulting, will be presenting “Diversity and Inclusion in Computing”. Day & Time: Monday April 1st, 2019 7:30 p.m. ‐ 9:00 p.m. Speaker: Aislin O’Hara of O’Hara & Associates Consulting Organizers: IEEE Toronto Systems Chapter Location: Room ENG 103, Ryerson University George Vari Engineering and Computing Centre 245 Church Street, Toronto, Ontario Canada M5B 2K3 Contact: Mehrdad Tirandazian Register: https://events.vtools.ieee.org/m/196718 Abstract: Josh Bersin, world class industry analyst & founder of Bersin by Deloitte cited Diversity & Inclusion as one of the hottest topics for 2019 technology companies. Through this presentation, we will uncover what diversity & inclusion really means, why it matters and what strategies can be used to foster inclusion. We will explore some case studies showing best practices and listen to a testimonial from a person living with a disability. Students will learn the ways diversity and inclusion is protected under the Ontario Human Rights Code, participate in a rich discussion on common misconceptions and leave with a deepened understanding on how the technology sector can leverage diversity to become a more successful industry as a whole. Biography: Aislin is a Certified Professional Consultant on Aging with 12 years of experience executing accessible & inclusive customer experience solutions within the public sector. Presently, Aislin is the Principal Consultant and founder of O’Hara & Associates Consulting, which helps businesses prepare for the demographic shift in our population by providing age-friendly strategies and advice on designing accessible & inclusive solutions. Most recently, Aislin was the Project Lead – Customer Experience for TTC Wheel-Trans, the 3rd largest specialized transit agency in North America, whose customer base is vastly comprised of seniors and persons with disabilities. Aislin was responsible for designing and implementing various accessible, diverse & inclusive customer facing initiatives for the Wheel-Trans Transformation Program. Aislin’s work on accessible customer service design was recently published in the Journal of the Transportation Research Board and was recently presented at the January 2019 Washington conference.

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.

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.

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