IEEE DSC 2017 - IEEE International Conference on Data Science in Cyberspace

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TUTORIAL

Data Science in Online Digital Advertising

9:00-11:40, Monday, June 26, 2017

Tutorial Speaker: Xingquan Zhu

Abstract: Recent advancement in networking and communication technologies have witnessed a rapid growth of digital advertising, which uses the Internet to promote and deliver advertisements (Ad) to consumers. Compared to traditional media, such as Radio, TV, the Internet offers tremendous advantages such as real-time interaction, consumer information availability, transparent user engagement, and effective assessment of the campaign results etc. As a result, on-line digital advertising is quickly dominating the advertising market. One of the prominent and most sought characteristics of the Internet is that it allows the Ad industry to obtain fine-grained information from specific geographic locations, regions, households, or even individual users, and is able to serve highly customized advertisement to users in real-time. Yet the huge data volumes with billions of programmatic transactions on a daily basis, and millisecond real-time response requirement provides significant challenges for data science research to design effective methods for model learning, bidding optimization, fraud identification, etc.
In this tutorial, we will review data science research in online digital advertising, including (1) online digital advertising platforms, tools, and domain knowledge, for both display advertising and search advertising; and will also introduce (2) computational approaches to solve online digital advertising challenges, such as click through rate estimation, bid optimization, and fraud detection. The tutorial will also discuss research questions for future work in the field.

Biography: He is an Associate Professor in the Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, and a Distinguished Visiting Professor (Eastern Scholar) at Shanghai Institutions of Higher Learning. His research interests mainly include data mining, machine learning, bioinformatics, and computational advertising. He was the recipient of an ARC Future Fellowship in 2010, and has received two Best Paper Awards and one Best Student Paper Award.
Dr. Zhu is an associate editor of the IEEE Transactions on Knowledge and Data Engineering (2008-2012, 2014-date), and is currently serving on the Editor Board of International Journal of Social Network Analysis and Mining SNAM (2010-date), Journal of Big Data (2013-date), and Network Modeling Analysis in Health Informatics and Bioinformatics Journal (2014-date). He was a program committee co-chair for the 14th IEEE International Conference on Bioinformatics and BioEngineering (BIBE-2014), IEEE International Conference on Granular Computing (GRC-2013), 23rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI-2011), and the 9th International Conference on Machine Learning and Applications (ICMLA-2010). He also served as a conference co-chair for ICMLA-2012.

The Emergence of Hardware Security

14:00-16:40, Monday, June 26, 2017

Tutorial Speaker: Yier Jin

Abstract: Hardware has long been touted as dependable and trustable entity than the software running on it. The illusion that attackers cannot easily access the isolated integrated circuit (IC) supply chain has once and again been invalidated by remotely activated hardware Trojan and untraceable break-ins of networking systems running on fake and subverted chips reported by businesses and military strategists, and confirmed by forensic security experts analysing recent incidents. The situation was aggravated by the geographical dispersion of chip design activities and the heavy reliance on third-party hardware intellectual properties (IPs). Counterfeit chips (such as unauthorized copies, remarked/recycled dice, overproduced and subverted chips or cloned designs) pose a major threat to all stakeholders in the IC supply chain, from designers, manufacturers, system integrators to end users, in view of the severe consequence of potentially degraded quality, reliability and performance that they caused to the electronic equipment and critical infrastructure. Unfortunately, tools that can analyse the circuit netlist for malicious logic detection and full functionality recovery are lacking to prevent such design backdoors, counterfeit and malicious chips from infiltrated into the integrated circuit (IC) design and fabrication flow. This tutorial addresses and reviews recent development in preventive countermeasures, post-manufacturing diagnosis techniques and emerging security-enhanced primitives to avert these hardware security threats. This tutorial will also cover the emerging topics where hardware platforms are playing an active role in system protection and intrusion detection. It aims to create an awareness of the ultimate challenges and solutions in addressing hardware security issues in the new age of Internet of Things (IoT), where the intense interactions between devices and devices, and devices and humans have introduced new vulnerabilities of embedded devices and integrated electronic systems.

Biography: Yier Jin is the Endowed IoT Term Professor in the Warren B. Nelms Institute for the Connected World and also an Associate Professor in the Department of Electrical and Computer Engineering (ECE) in the University of Florida (UF). Prior to joining UF, he was an assistant professor in the ECE Department at the University of Central Florida (UCF). He received his PhD degree in Electrical Engineering in 2012 from Yale University after he got the B.S. and M.S. degrees in Electrical Engineering from Zhejiang University, China, in 2005 and 2007, respectively. His research focuses on the areas of embedded systems design and security, trusted hardware intellectual property (IP) cores and hardware-software co-design for modern computing systems. His is currently focusing on the design and security analysis on Internet of Things (IoT) and wearable devices with particular emphasis on information integrity and privacy protection in the IoT era. Dr. Jin received the Best Paper Award in the 52nd Design Automation Conference in 2015, the 21st Asia and South Pacific Design Automation Conference in 2016, and the 10th IEEE Symposium on Hardware-Oriented Security and Trust in 2017.