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Conferences, Lectures, & Seminars
Events for April
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CS Colloquium: Chang Liu (University of Maryland, College Park) - Secure Cloud Computing - A Programming Language Approach
Tue, Apr 05, 2016 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Chang Liu, University of Maryland, College Park
Talk Title: Secure Cloud Computing - A Programming Language Approach
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium
The big data era has dramatically transformed our lives; however, security incidents such as data breaches put sensitive data (e.g. photos, identities, genomes) at risk. To protect users' data privacy, there is a growing trend to build secure cloud computing systems, which enables computation over two or more parties' sensitive data, while revealing nothing more than the results to the participating parties. Conceptually, privacy-preserving computing systems leverage cryptographic techniques (e.g. secure multiparty computation) and trusted hardware (e.g. secure processors) to instantiate a "secure" abstract machine consisting of a CPU and encrypted memory, so that an adversary cannot learn information through either the computation within the CPU or the data in the memory. Unfortunately, evidence has shown that, side channels (e.g. memory accesses, timing, and termination) in such a "secure" abstract machine may potentially leak highly sensitive information including cryptographic keys that form the root of trust for the secure systems.
I conduct synergistic research to bridge cryptography and programming language techniques to address
this problem. My research broadly expanded the investigation of a research direction called trace oblivious computation, where I employ programming language techniques to prevent side channel information leakage. In this talk, I will discuss my work on two promising approaches, i.e. secure-processor and secure multiparty computation, toward building a secure cloud computing system. I will focus on both theoretical development to enforce formal security, as well as practical system building to yield the state-of-the-art results.
Biography: Chang Liu is a PhD candidate in the Department of Computer Science at University of Maryland, College Park, where he works in the Maryland Cybersecurity Lab with his advisors Michael Hicks and Elaine Shi. His work broadly expanded the investigation of the research direction of trace oblivious computation, which made significant impact on trusted hardware-based secure computation and cryptography-based secure multiparty computation. He is the recipient of John Vlissides Award (2015) and University of Maryland's Outstanding Early Graduate Student Award (2014). His papers has received a NSA Best Scientific Cybersecurity Paper Award (2013), the Best Paper Award of ASPLOS (2015), and 1st Best Paper Award in Applied Cyber Security Paper at CSAW (1st Place, 2015). His ObliVM system won the HLI Award for Secure Multiparty Computation in the iDash Secure Genomics Analysis Competition (2015).
Host: CS Department
Location: Olin Hall of Engineering (OHE) - 136
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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CS Colloquium: Tien Nguyen (Iowa State University) -Program Analysis and Large-scale Code Mining for Software Quality
Tue, Apr 05, 2016 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Tien Nguyen, Iowa State University
Talk Title: Program Analysis and Large-scale Code Mining for Software Quality
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium
Detecting and fixing software defects are important in developing reliable and high-quality software systems. Software defects are so prevalent and detrimental that they cost the US economy an estimated $59 billion annually. In this talk, I will present my research that develops advanced program analysis methods in combination with large-scale code mining and software analytics to support developers in the process of software maintenance, detecting and fixing software defects. I will present our cross-stage, variability-aware program analysis infrastructure for dynamic Web applications to support the detection and debugging of software defects in web development. The advanced techniques include output-oriented symbolic execution, variability-aware web code analysis, and multi-language, embedded code analysis. I will also present an integrated approach between program analysis and statistical learning to mine from a large-scale code repository infrastructure to support important software engineering tasks including inferring and checking the specifications of software libraries, migrating code from one platform in a programming language to another, and detecting software vulnerabilities in API usages with pattern mining and anomaly detection.
Biography: Dr. Tien N. Nguyen is currently an Associate Professor in both Electrical and Computer Engineering Department and Computer Science Department at Iowa State University (ISU). He is currently serving as the Chair of Software Systems Area. Since joining ISU in 2005, his research interests include program analysis, mining large-scale software repositories, and software maintenance and evolution. Since 2009, he has been awarded 3 ACM SIGSOFT Distinguished Paper Awards, one Best Paper Award, and one best ICSE Formal Research Demonstration Award at the top-tier, international software engineering conferences including ICSE, FSE, and ASE. His research has been supported by 14 external grants including 8 NSF grants from US National Science Foundation (PI on 5 of them), and several grants from industry including ABB Software Research Grant Program, Litton Industry, IBM research, and Agile Alliance Academic Program. He will be serving as the Program Co-Chair of the 32nd ACM/IEEE International Conference on Automated Software Engineering (ASE 2017) and the Co-Chair of the Formal Research Demo Track at the 40th International Conference on Software Engineering (ICSE 2018). He has served on Program Committees and Program Boards of top-tier software engineering conferences including ICSE, FSE, ASE, OOPSLA, ECOOP, and ICSME. He also served as the Chair of Formal Research Demo Track at ACM SIGSOFT Symposium on the Foundations of Software Engineering (FSE 2010). He was awarded the Litton Professorship Medallion Award from Iowa State University in 2008 for young faculty who exhibits excellent leadership in research and teaching. He is one of the key persons who have first contributed to the ABET-accredited B.Sc. degree program in Software Engineering at ISU.
Host: CS Department
More Info: https://bluejeans.com/514828239
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
Event Link: https://bluejeans.com/514828239
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CS Colloquium: Aaron Schulman (Stanford) - Why applications are still draining our batteries, and how we can help
Wed, Apr 06, 2016 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Aaron Schulman , Stanford
Talk Title: Why applications are still draining our batteries, and how we can help.
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium
Application developers lack tools to profile and compare the energy consumption of different software designs. This energy-optimization task is challenging because of unpredictable interactions between the application and increasingly complex power management logic. Yet, having accurate power information would allow application developers to both avoid inefficient designs and discover opportunities for new optimizations.
In this talk, I will show that it is possible to accurately measure system-level power and attribute it to application activities. I will present BattOr, a portable, easy-to-use power monitor that provides developers with a profile of the energy consumption of their designs-”without modifications to hardware or software. I will show how Google developers are using BattOr to improve Chrome's energy efficiency. I will also show how fine-grained understanding of cellular power at different signal strengths enables novel energy optimizations. Finally, I will describe my future plans to attribute system-level power to individual hardware components and to investigate opportunities presented by instrumenting every server in a data center with fine-grained power monitoring.
Biography: Aaron Schulman is a Postdoctoral Scholar at Stanford working with Sachin Katti; he earned his Ph.D. in Computer Science from the University of Maryland, where he was advised by Neil Spring. His research interests are in low-power embedded systems, wireless communication, and network measurement. Aaron's research on the BattOr power monitor has been funded by Google, is being commercialized by his startup Mellow Research, and is becoming Google's de facto standard tool for measuring the energy consumption of the Chrome web browser. For his dissertation, Aaron provided the first observations of fundamental factors that limit the reliability of the Internet's critical last-mile infrastructure. His dissertation was selected to receive the the 2013 ACM SIGCOMM Doctoral Dissertation Award. http://stanford.edu/~aschulm
Host: CS Department
Location: Olin Hall of Engineering (OHE) - 136
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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CS Colloquium: Kobbi Nissim (Harvard University) - Privacy: From Theory to Practice
Tue, Apr 12, 2016 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Kobbi Nissim, Dept. of Computer Science, Ben-Gurion University and Center for Research on Computation and Society, Harvard University
Talk Title: Privacy: From Theory to Practice
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium
The treatment of privacy in data analysis has taken a dramatic shift a little more than a decade ago - as failures of traditional privacy preserving techniques were beginning to accumulate, a theoretical, foundational approach to privacy emerged. A central concept in this theoretical treatment is "differential privacy", a definition of privacy in the context of data analysis that has concrete provable privacy consequences. Differential privacy became to be a rich, fast evolving framework for developing privacy preserving algorithms and for studying some of the fundamental properties of privacy. Moreover, differential privacy proved to interact fruitfully with many other research areas, and even to influence applications that are (seemingly) not related to privacy. With a mature theoretical basis, differential privacy is now at prime time for inclusion in real-world systems.
We will look into the intuition behind differential privacy, review some of is theory, and some of the challenges towards using differential privacy in practice. In particular, we will focus on a new legal-technological methodology for making rigorous claims that differential privacy satisfies existing legal privacy regulations.
The talk would be self-contained and no prior background on privacy would be assumed.
Host: CS Department
Location: Olin Hall of Engineering (OHE) - 136
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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CS Colloquium: Qixing Huang (Toyata Technical Institute Chicago) - Visual Computing Using Big 3D Data
Tue, Apr 12, 2016 @ 04:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Qixing Huang, Toyata Technical Institute Chicago
Talk Title: Visual Computing Using Big 3D Data
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium
Over the past decade, the quantity of accessible visual data has undergone unprecedented expansion. This data is not only vast but also exists within numerous modalities such as images, videos, and 3D models. While researchers have aptly exploited the inflation of these first two areas, the significant growth in 3D data has been predominantly overlooked. In this talk, I will present algorithms that utilize big 3D data to accomplish many previously hard or even impossible tasks in visual computing. These include reconstructing complete 3D models from single images, identifying meaningful correspondences between drastically different objects (e.g., between an elephant and a cat) as well as extracting semantic parts of an object without supervision. The guiding principle is to establish high-quality maps for aggregating and propagating information. I will discuss fundamental map computation tools for large-scale datasets.
Biography: Qixing 'Peter' Huang is currently a research assistant professor at the Toyata Technical Institute in Chicago. He obtained his PhD in Computer Science from Stanford University and his MS and BS in Computer Science from Tsinghua University. He has also worked at Adobe Research and Google Research, where he developed some of the key technologies for Google Street View. Dr. Huang's research spans the fields of computer vision, computer graphics, and machine learning. In particular, he is interested in designing new algorithms that process and analyze big geometric data (e.g., 3D shapes/scenes). He is also interested in statistical data analysis, compressive sensing, low-rank matrix recovery, and large-scale optimization, which provides theoretical foundation for his research. Qixing has published extensively at SIGGRAPH, CVPR and ICCV, and has received grants from NSF and various industry gifts. He also received the best paper award at the Symposium on Geometry Processing 2013.
Host: CS Department
More Info: https://bluejeans.com/345837634
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
Event Link: https://bluejeans.com/345837634
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CS Colloquium: Julia Rubin (MIT CSAIL) -The Secret Life of Mobile Applications
Mon, Apr 18, 2016 @ 02:00 PM - 03:15 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Julia Rubin, MIT CSAIL
Talk Title: The Secret Life of Mobile Applications
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium
As software becomes increasingly more complex and yet more pervasive, poor understanding of software behavior compromises the quality and the integrity of software systems that we use. In this talk, I will show that automated analysis techniques can help to identify and reason about software behavior characteristics that matter to humans. After a brief overview of my current research directions, I will focus on techniques for identifying privacy violations in mobile applications, i.e., leakages of sensitive information such as user location and shopping preferences. I will present a set of solutions that rely on contextual, functional and usage-based clues for improving the accuracy of leakage detection and for distinguishing between "legitimate" and "illegitimate" information distribution patterns.
Biography: Julia Rubin is a Postdoctoral Researcher in the EECS department at MIT. Prior to that, she was a Research Staff Member and, part of the time, a manager at IBM Research in Haifa, Israel. She received her PhD in Computer Science from the University of Toronto, Canada in 2014. Julia's research interests are in software engineering, program analysis and software security, focusing on improving the quality and the integrity of modern software systems. Her recent work in this area won an ACM Distinguished Paper Award at ASE, two Best Paper Awards, at SPLC and CSMR, and was nominated for Facebook's Internet Defense Prize at the USENIX Security Symposium.
Host: CS Department
More Info: https://bluejeans.com/706751366
Location: John Stauffer Science Lecture Hall (SLH) - 102
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
Event Link: https://bluejeans.com/706751366
