Thursday 10/06 09:15-12:30 Tutorial-01: MALWARE ANALYSIS AND DETECTION
Often computer/mobile users call everything that disturbs/corrupts their system a VIRUS without being aware of what it means or accomplishes. This tutorial systematically introduces the different malware varieties, their distinctive properties, different methods of analyzing the malware, and their detection techniques.
Today computing devices like laptops, mobile phones, smart devices, etc., have penetrated very deep into our modern society and have become an integral part of our daily lives. Currently, more than half of the world’s population uses computers/mobile devices for their professional/personal needs. However, these computing devices are targeted by malware designers encouraged by profits/gains associated with the attack. According to a recent report, monetary losses due to cybercrime are expected to reach 10 trillion dollars annually by 2025. The primary role in providing defense against malware attacks is designed and developed by the anti-malware community (researchers and anti-virus industry). Traditionally anti-viruses are based on the signature, heuristic, and behavior based detection engines. However, these engines are unable to detect next-generation polymorphic and metamorphic malware. Thus researchers have started developing malware detection engines based on machine learning to complement the existing anti-virus engines. However, there are many open research challenges in these models like adversarial robustness, explainability, fairness, etc., which we are going to discuss in detail during the workshop.
This workshop will cover fundamental techniques, limitations, open research problems and future directions in the field of malware analysis and detection. Following are the three specific learning outcomes:
Biography of Presenters
Ashu Sharma is currently working as a senior malware analyst at WatchGuard, India. He has more than three years of industrial experience in malware analysis and more than two years of teaching experience. He has completed his Ph.D. in static malware analysis from BITS Pilani, India, and post-doctoral in malware identification via dynamic analysis under Prof. Sandeep Shukla (IIT Kanpur, India). He was the speaker at many reputed conferences/workshops and had many publications in reputed conferences/journals.
Hemant Rathore is currently working as Assistant Professor at the Department of CS and IS at BITS Pilani, Goa Campus, India. Before joining academics, he was working in the area of computer security for three years at Symantec, India. His Ph.D. is on the topic of Adversarial Robustness and Explainability in Malware Detection Models. His research interests are in the area of Malware Analysis, Network Security, Machine Learning, and Operating Systems. He has guided several undergraduate and postgraduate students in their independent research projects and published many research papers in reputed journals/conferences.
Thursday 10/06 14:00-17:40 Tutorial-02: Blockchain for Sustainable Energy Management Systems
xAnalytics Inc., Ottawa, Canada
The need for clean energy has become crucial with population growth, the abundant demand in traditional energy resources and the need for the decarbonization of economy to curb climate change. The solution ahead is to shift to and integrate more renewable and clean sources of energy with the existing conventional energy infrastructure as well as offer end-users a more active role in the integrated management of their energy resources (grid, loads, storage, microgeneration). Energy trading platforms are mechanisms used to attain increased energy demands while meeting participants’ satisfaction (i.e., consumers, prosumers, and utility grids). Participant satisfaction is driven by two main factors: stable coverage of energy demand and profit maximization, which can be fostered by demand response programs. Peer-to-Peer (P2P) energy trading platforms should find a win-win balance, where all participants are able to make some profit and meet their energy demand under any circumstances.
Biography of Presenter
Dr. Moayad Aloqaily (S’12, M’17) received the M.Sc. degree in electrical and computer engineering from Concordia University, Montreal, QC, Canada, in 2012, and the Ph.D. degree in electrical and computer engineering from the University of Ottawa, Ottawa, ON, in 2016. He was an instructor in the Systems and Computer Engineering Department at Carleton University, Ottawa, Canada, in 2017. He has been working with Gnowit Inc. as a Senior Researcher and Data Scientist since 2016. He is also the managing director of xAnalytics Inc., Ottawa, ON, Canada, 2019. Currently, he is with the Faculty of Engineering, Al Ain University, United Arab Emirates. His current research interests include the applications of AI and ML, Connected and Autonomous Vehicles, Blockchain Solutions, and Sustainable Energy and Data Management. He was the recipient of many honors and awards. He received the 2020 best paper award from Ad Hoc Networks Journal. He has chaired and co-chaired many IEEE conferences and workshops including BCCA2020, AdHocNets2020, PEDISWESA-ISCC2020, ITCVT-NOMS2020, E2NIoT-IWCMC2020, ICCN-INFOCOM19, AICSSA19, and BATFMEC19-20. He has served as a guest editor in many journals including IEEE Wireless Communications Magazine. He started his own Special Interest Group (SIG) on Blockchain and Application as well as Internet of Unmanned Aerial Networks. He is an IEEE member, ACM Member, and a Professional Engineer Ontario (P.Eng.).