Abstract and Bio

    Jeremy Clark

    Concordia University, Canada

    The Bitcoin & Blockchain Technology Landscape

    Abstract

    Bitcoin has emerged as the most successful cryptographic currency in history. Within two years of its quiet launch in 2009, Bitcoin grew to comprise billions of dollars of economic value despite only cursory analysis of the system’s design. Since then, researchers have identified hidden-but-important properties of the system, developers and entrepreneurs have proposed promising alternatives and extensions, and major corporations have deployed technologies based on Bitcoin’s data-structure for distributed ledgers (the blockchain). In this talk, we trace Bitcoin’s origins and provide an overview of how it, and its components, are being applied to digital currency and other disintermediated services.


    Biography

    Jeremy Clark is an assistant professor at the Concordia Institute for Information Systems Engineering. He obtained his PhD from the University of Waterloo, where his dissertation, awarded Waterloo’s Gold Medal, was on designing and deploying secure voting systems that provide a provably correct tally, and included Scantegrity -- the first use of an end-to-end verifiable system in a public sector election. He recently became interested in Bitcoin and has contributed to one of the first academic papers in the area, several research projects, and a textbook. Beyond research, he has worked with several municipalities on voting technology and testified to the Canadian Senate on Bitcoin.

    Abstract and Bio

    François Laviolette

    Laval University, Canada

    Machine Learning, Big Data and Security

    Abstract

    (TBA)


    Biography

    François Laviolette is a full Professor at the department of Computer Science and Software Engineering of Laval University. He received his doctorate in graph theory at the University of Montreal in 1995. His thesis solved an old problem that had been studied among others by the mathematician Paul Erdos.

    For over 10 years, his main area of research has been Machine Learning. More specifically, he develops learning algorithms to solve new types of learning problems, including problems relating to genomics and proteomics. He is currently the director of the new Big Data Research Center at Laval University.

    Abstract and Bio

    Jean-Yves Marion

    LORIA, France

    A Morphological Approach to Binary Code Analysis

    Abstract

    Binary code analysis is a complex process which can be performed nowadays only by skilled cybersecurity experts whose workload just keeps increasing. Uses cases include vulnerabilities detection, testing, clustering and classification, malware analysis, etc... We develop a tool named Gorille, which is based on the reconstruction of an high level semantics for the binary code. Control flow graphs provide a fair level of abstraction to deal with the binary codes they represent. After applying some graph rewriting rules to normalize these graphs, our software tackles the subgraph search problem in a way which is both efficient and convenient for that kind of graphs. This technique is described as morphological analysis as it recognizes the whole shape of the malware.

    That being said, some pitfalls still need to be considered. First of all, the output can only get as good as the input data. And it is known that static disassembly cannot produce the perfect control flow graph since this problem is undecidable. As a matter of facts, malware heavily use obfuscation techniques such as opaque predicates to hide their payloads and confuse analyses. Dynamic analysis should then be used along with static disassembly to combine their strengths. Another dangerous pitfall feared by every expert is the so-called false positives rate : false alarms that make them waste indeed a precious time assessing the reality of the threat. Shared binary code is not always relevant as many software embed static standard libraries. Gorille's solution to this issue lies in graph rewriting. By rewriting classic subgraphs into configuration-based special nodes, we even obtain an higher abstraction of the control flow graph.


    Biography

    Jean-Yves Marion is professor at Université de Lorraine, France. He is the director of the computer science lab LORIA (www.loria.fr) which is affiliated to CNRS, Inria and Université de Lorraine. He got his habilitation in 2002 from Université Nancy 2 and his Phd Thesis from Université Paris 7. He spent two years at Indiana University. His research interests are in two main domains: (i) in proof theory and computation complexity, and (ii) in computer security and more specifically in malware. He is one of the co-founder of the High Security Lab (LHS) which was in 2010 a unique research platform to conduct computer security experiments. He published about 80 papers and supervised about 25 PhD thesis. Since 2015, he is a senior member of Institut Universitaire de France.