Nick Feamster (Princeton) - More Users, More Data... More Problems

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January 31, 2019 at 2:30pm - 3:30pm
JCL, Rm. 390
Event Audience:
Nick Feamster

Speaker: Nick Feamster Professor of Computer Science, Princeton University

Nick Feamster is a professor in the Computer Science Department at Princeton University and the Deputy Director of the Princeton University Center for Information Technology Policy (CITP), which he directed for two years. His research focuses on many aspects of computer networking and networked systems, with a focus on network operations, network security, and censorship-resistant communication systems.

Before joining the faculty at Princeton, he was a professor in the School of Computer Science at Georgia Tech. He received his Ph.D. in Computer science from MIT in 2005, and his S.B. and M.Eng. degrees in Electrical Engineering and Computer Science from MIT in 2000 and 2001, respectively. He was an early-stage employee at Looksmart (acquired by AltaVista), where he wrote the company's first web crawler; and at Damballa, where he helped design the company's first botnet-detection algorithm.

Nick is an ACM Fellow. He received the Presidential Early Career Award for Scientists and Engineers (PECASE) for his contributions to cybersecurity, notably spam filtering. He is an ACM Fellow. His other honors include the Technology Review 35 "Top Young Innovators Under 35" award, the ACM SIGCOMM Rising Star Award, a Sloan Research Fellowship, the NSF CAREER award, the IBM Faculty Fellowship, the IRTF Applied Networking Research Prize, and award papers at ACM SIGCOMM (network-level behavior of spammers), the SIGCOMM Internet Measurement Conference (measuring Web performance bottlenecks), and award papers at USENIX Security (circumventing web censorship using Infranet, web cookie analysis) and USENIX Networked Systems Design and Implementation (fault detection in router configuration, software-defined networking). His seminal work on the Routing Control Platform won the USENIX Test of Time Award for its influence on Software Defined Networking.

Nick is an avid distance runner, having completed nearly 20 marathons, including Boston, New York, and Chicago, as well as the Comrades Marathon, an iconic ultra-marathon in South Africa. He lives in Princeton, New Jersey.

Abstract: More Users, More Data... More Problems: Three Grand Challenges for the Modern Internet

The Internet was designed to make it easy for users and devices to connect and communicate. This ease of connectivity has resulted in more users, more devices, more traffic, more applications, and more user data. In this talk, I will describe three new challenges that the Internet faces as a result of these developments, and how we have begun to tackle them with new approaches and systems for network data analytics, ranging from lower-level measurement to higher-level inference and prediction.

First, Internet applications should be usable, for everyone. Internet access speeds continue to increase, with gigabit broadband access now a reality in many regions. Yet, faster access speeds does not imply that everyone is having a good experience. The digital divide has widened, performance bottlenecks have moved from the access network to other parts of the network, and the reliability and performance of the applications we use consistently fail to meet our expectations. Better measurement and inference capabilities can help, from improving diagnostics to informing public policy. I will describe data analytics systems that we have built that shed light on everything from the speed of a user’s Internet service provider to the causes of poor streaming video quality.

Second, the Internet should be secure and trustworthy. The Internet’s design has enabled malicious communications from denial-of-service to disinformation. Many citizens now rely on the Internet as their primary source of information and means to communicate. Yet, the protocols and platforms that the Internet uses to deliver this information to us remain extremely insecure and vulnerable to manipulation. I will describe data-driven systems that we have built to detect—and predict—Internet attacks, from Internet scams to disinformation.

Finally, the Internet should be private. Internet-connected “smart” infrastructure, from homes to cities, is poised to revolutionize personal health to urban planning. Devices from phones to fridges are recording everything from our locations to our eating habits. In light of these trends, we must ensure that the increasing amount of data that is collected about us remains private and is used only for the purposes that we expect and intend.  I will describe new measurement tools and techniques that shed light on the data collection practices in smart homes, the parties involved in collecting our data, what they can learn from our data, and methods we are developing to help protect our privacy in these environments.

Sometimes, these three goals can be at odds, such as when the data that is needed to improve network performance or security contains private information. I will briefly mention several areas where we are redesigning Internet protocols and systems to facilitate a better balance between performance, security and privacy. Finally, the solutions to these challenges are not exclusively the purview of Internet engineers: they ultimately lie at the intersection of systems, networking, machine learning, and Internet policy. I will touch on how each of these areas can play a role as we embark on this new set of exciting grand challenges for the modern Internet.

Host: Mike Franklin

Type: talk