Talks on Technology Science (ToTS) and Topics in Privacy (TIP)
This is the schedule of weekly talks on Technology Science from expert researchers, public interest groups, and others on the social impact of technology and its unforseen consequences.
Join us on most Monday afternoons 2:30-4 PM at CGIS Knafel, Room K354 (1737 Cambridge St, Cambridge, MA).
|2/1||Dave Choffnes, Northeastern University||ReCon: Identifying and Controlling Privacy Leaks from Mobile Devices|
|2/8||Cathy O'Neil||[Rescheduled due to weather] Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy|
|2/16 (Tue)||Eran Toch, Tel-Aviv University [Room K262]||Privacy Preservation Methods for Genetic and Location Data|
|2/22||Azer Bestavros, Boston University||Web-based Multi-Party Computation with Application to Anonymous Aggregate Compensation Analytics|
|3/7||Susan Crawford, Harvard Law School, and Holly St. Clair, Commonwealth of Massachusetts||How Data and Technology Can Help Improve Government|
ReCon: Identifying and Controlling Privacy Leaks from Mobile Devices
Mobile systems have become increasingly popular for providing ubiquitous Internet access; however, recent studies demonstrate that software running on these systems extensively tracks and leaks users' personally identifiable information (PII). I argue that these privacy leaks persist in large part because mobile users have little visibility into PII leaked through the network traffic generated by their devices, and have poor control over how, when and where that traffic is sent and handled by third parties.
In this talk, I describe ReCon, a cross-platform system that reveals PII leaks and gives users control over them without requiring any special privileges or custom OSes. Specifically, our key observation is that PII leaks must occur over the network, so we implement our system in the network using a software middlebox. We then use a machine learning approach to to efficiently and accurately detect users' PII without knowing a priori the content that is PII. Further, we develop techniques to block, obfuscate, or ignore the PII leak, by displaying leaks via a visualization tool and letting the user decide how the system should act on transmitted PII. I discuss the design and implementation of the system and evaluate its methodology with measurements from controlled experiments and flows from a user study with more than 100 participants. In addition to revealing and controlling PII leaks, we are using our machine-learning-based techniques to automatically identify and block malware based on network behaviors.
Speakers: David Choffnes is an assistant professor in the College of Computer and Information Science at Northeastern University. His research is primarily in the areas of distributed systems and networking, with a recent focus on mobile systems and privacy. Much of his work entails crowdsourcing measurement and performance evaluation of Internet systems by deploying software to users at the scale of tens or hundreds of thousands of users. He earned his PhD from Northwestern (not in the northwest), and completed a postdoc at the University of Washington (in the northwest) prior to joining Northeastern (both in the northeast and northwest). He sees no reason why this should at all be confusing. He is a co-author of three textbooks, and his research has been supported by the NSF, Google, the Data Transparency Lab, VidScale, M-Lab, and a Computing Innovations Fellowship.
[Rescheduled due to weather] Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy
Far too many algorithms in use today are being used as weapons against populations, whether they are consumers, workers, prisoners, or teachers. I'll talk about a few which I consider the worst kind - and which I call Weapons of Math Destuction - namely, those that are opaque, widespread, and powerful enough to cause tremendous destruction through feedback loops. I will also discuss suggestions for data scientists, policy makers, and the public for how to combat them.
Speakers: Cathy O’Neil earned a Ph.D. in math from Harvard, was a postdoc at the MIT math department, and a professor at Barnard College where she published a number of research papers in arithmetic algebraic geometry. She then switched over to the private sector, working as a quant for the hedge fund D.E. Shaw in the middle of the credit crisis, and then for RiskMetrics, a risk software company that assesses risk for the holdings of hedge funds and banks. She left finance in 2011 and started working as a data scientist in the New York start-up scene, building models that predicted people’s purchases and clicks. She wrote Doing Data Science in 2013 and launched the Lede Program in Data Journalism at Columbia in 2014. She is a weekly guest on the Slate Money podcast and is currently writing a book about the dark side of big data called Weapons of Math Destruction: how big data increases inequality and threatens democracy coming out September 2016 with Random House.
Privacy Preservation Methods for Genetic and Location Data
We will have this talk at CGIS Knafel, Room K262.
Massive data sets and sophisticated learning algorithms are routinely used by companies and governments to predict people’s behavior and to deduce key properties of individuals. While the ability to infer detailed knowledge about people can be tied to many privacy threats, existing models of statistical disclosure are limited in modeling the threat and in suggesting effective solutions. In many cases, the data about each individual is processed separately, ruling out solutions such as anonymization and attribute obfuscation. Therefore, we generalize the concept of inferential privacy, and suggest Decision Theory as a solid foundation that can model inferential attacks. In addition, we use Principle Component Analysis (PCA) to quantify the potential privacy loss through the ability of an attacker to infer an individual’s properties. We show initial results from two studies, one in the field of location databases and one in the field of genomic databases, in which we empirically describe an upper bound to privacy loss. Finally, the talk will discuss several privacy- enhancing technologies that rely on inferential privacy, and demonstrate how they can be applied to real-world problems.
Speakers: Prof. Eran Toch is a member of the faculty of Engineering at Tel-Aviv University, at the department of Industrial Engineering. Eran’s research group is working on usable privacy and security, currently running several projects funded by agencies such as the Israeli Science Foundation (ISF), Horizon 2020, DARPA, and Israel Ministry of Science. Prior to joining Tel Aviv University, Eran was a post-doc fellow at the Carnegie Mellon University, School of Computer Science, and he has a Ph.D. from the Technion – Israel Institute of Technology.
Web-based Multi-Party Computation with Application to Anonymous Aggregate Compensation Analytics
In this talk, I will describe the definition, design, implementation, and deployment of a simple multi-party computation protocol and supporting web-based infrastructure. The protocol and infrastructure constitute a software application that allows groups of cooperating parties, such as companies or other organizations, to perform computation over their respective data assets for the purpose of obtaining aggregate analytics without the need to communicate or share their private data sets. The application was developed specifically to support a Boston Women’s Workforce Council (BWWC) study of the gender wage gap among employers within the Greater Boston Area. The application was deployed successfully to collect aggregate statistical data pertaining to compensation levels across genders and demographics at a number of participating organizations. Time permitting, I will summarize our experience with the rollout of this application, lessons learned, and future plans to extend the capabilities we developed by incorporating them into a programming environment that leverages popular cloud platforms for computing analytics over large private data sets.
This work was done at Boston University in collaboration with Andrei Lapets, Eric Dunton, Kyle Holzinger, and Frederick Jansen. It was funded in part by NSF awards #1414119 and #1430145 and by the Initiative on Cities at Boston University.
Speakers: Azer Bestavros (PhD 1992, Harvard University) is a Professor in the CS Department at Boston University, which he joined in 1991 and chaired from 2000 to 2007. He is the Founding Director of the BU Hariri Institute for Computing, which was set up in 2010 to "create and sustain a community of scholars who believe in the transformative potential of computational perspectives in research and education." His research contributions include pioneering the web push content distribution model adopted years later by industry, seminal work on Internet traffic characterization, game-theoretic approaches to cloud resource management, and safety certification of networked systems and software. Supported by over $20M of awards from government and industry, his work yielded 18 PhD theses, 6 issued patents, 3 startups, and hundreds of refereed papers that are cited over 15,000 times. His current research is focused on mechanism design for efficient and secure cloud computing. Azer served as chair of the IEEE Computer Society TC on the Internet and as chair or member of the editorial boards of major computer systems and networking conferences and journals. Currently, he co-chairs the Research, Education, and Outreach Committee of the MGHPCC, and is a board member of the Cloud Computing Caucus, a non-profit, non-partisan coalition of industry and key government stakeholders, focused on raising awareness and educating lawmakers and the public on issues associated with cloud computing. Azer received a number of distinguished service awards and best papers awards, most notably the ACM Sigmetrics Inaugural Test of Time Award for technical contributions "whose impact is still felt 10-15 years after initial publication." In 2010, he received the United Methodist Scholar Teacher Award in recognition of "outstanding dedication and contributions to the learning arts and to the institution" at Boston University.
How Data and Technology Can Help Improve Government
This will be a brainstorming session on the ways data and technology can improve local government. The session begins with a presentation by Susan Crawford. Her recent book The Responsive City highlights the promising intersection of government and data through vivid case studies featuring municipal pioneers and big data success stories from Boston, Chicago, New York, and more. She explores topics including:
Holly St. Clair will respond and provide a few words about her thoughts and vision for the State of Massachusetts.
Then, the remainder of the session will be spent brainstorming ideas for how data and technology can help improve government. What are some low-hanging opportunities?
Speakers: Susan Crawford is a professor at Harvard Law School and a co-director of the Berkman Center. She is the author of Captive Audience: The Telecom Industry and Monopoly Power in the New Gilded Age, co-author of The Responsive City: Engaging Communities Through Data-Smart Governance, and a contributor to Medium.com’s Backchannel. She served as Special Assistant to the President for Science, Technology, and Innovation Policy (2009) and co-led the FCC transition team between the Bush and Obama administrations. She also served as a member of Mayor Michael Bloomberg’s Advisory Council on Technology and Innovation and is now a member of Mayor Bill de Blasio’s Broadband Task Force. Ms. Crawford was formerly a (Visiting) Stanton Professor of the First Amendment at Harvard’s Kennedy School, a Visiting Professor at Harvard Law School, and a Professor at the University of Michigan Law School (2008-2010). As an academic, she teaches Internet law and communications law. She was a member of the board of directors of ICANN from 2005-2008 and is the founder of OneWebDay, a global Earth Day for the internet that takes place each Sept. 22. One of Politico’s 50 Thinkers, Doers and Visionaries Transforming Politics in 2015; one of Fast Company’s Most Influential Women in Technology (2009); IP3 Awardee (2010); one of Prospect Magazine’s Top Ten Brains of the Digital Future (2011); and one of TIME Magazine’s Tech 40: The Most Influential Minds in Tech (2013). Ms. Crawford received her B.A. and J.D. from Yale University.
Holly St. Clair is the Director of Enterprise Level Data Management overseeing the Commonwealth of Massachusett's activities in data management, data analysis, research, and public access to data. Ms. St. Clair has pioneered the use of advanced decision support tools in Metropolitan Boston, managing a variety of projects that use scenarios modeling, community indicators, and innovative meeting formats to engage stakeholders in dialogue about policy choices. She has a excellent track record in public sector innovation and is recognized by Planetizen as one of the Leading Thinkers and Innovators in the field of Urban Planning and Technology.