- talks - lists.cs.princeton.edu

Muhammad Shahbaz will present his generals exam on Wednesday, May 11, 2016 at 2:30pm in CS 302
by Nicki Gotsis 02 May '16

02 May '16

Muhammad Shahbaz will present his generals exam on Wednesday, May 11, 2016 at 2:30pm in CS 302 The members of his committee are Nick Feamster (adviser), Jennifer Rexford, and Kyle Jamieson. *Title:* PISCES: A Programmable, Protocol-Independent Software Switch Abstract: Virtualized data centers use software hypervisor switches to steer packets to and from virtual machines (VMs). The switch frequently needs upgrading and customization—to support new protocol headers or encapsulations for tunneling or overlays, to improve measurement and debugging features, and even to add middlebox-like functions. Software switches are typically based on a large body of code, including kernel code. Changing the switch is a formidable undertaking requiring domain mastery of network protocol design and developing, testing, and maintaining a large, complex codebase. In this talk, we will argue that changing how a software switch forwards packets should not require intimate knowledge of its implementation. Instead, it should be possible to specify how packets are processed and forwarded in a high-level domain-specific language (DSL) such as P4, then compiled down to run on the underlying software switch. I will present PISCES, a software switch that is not hard-wired to specific protocols, which eases adding new features. We will also show how the compiler can analyze the high-level specification to optimize forwarding performance. Our evaluation shows that PISCES performs comparably to Open vSwitch, a hardwired hypervisor switch, and that PISCES programs are about 40 times shorter than equivalent Open vSwitch programs. *Reading List:* *Textbook* L. L. Peterson and B. S. Davie. "Computer Networks, Fifth Edition: A Systems Approach." Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 5th edition, 2011. *Papers* 1. Jose, Lavanya, et al. "Compiling packet programs to reconfigurable switches." NSDI 15. 2. Bosshart, Pat, et al. "P4: Programming protocol-independent packet processors." CCR 14. 3. Song, Haoyu. "Protocol-oblivious forwarding: Unleash the power of SDN through a future-proof forwarding plane." HotSDN 13. 4. Lattner, Chris, and Vikram Adve. "LLVM: A compilation framework for lifelong program analysis & transformation." CGO 04. 5. Adve, Vikram, et al. "LLVA: A low-level virtual instruction set architecture." MICRO 03. 6. Pfaff, Ben, et al. "The design and implementation of open vswitch." NSDI 15. 7. Belay, Adam, et al. "IX: A protected dataplane operating system for high throughput and low latency." OSDI 14. 8. Morris, Robert, et al. "The Click modular router." SOSP 99. 9. McCanne, Steven, and Van Jacobson. "The BSD packet filter: A new architecture for user-level packet capture." USENIX 93. 10. Bosshart, Pat, et al. "Forwarding metamorphosis: Fast programmable match-action processing in hardware for SDN."SIGCOMM 13. 11. Anwer, Muhammad Bilal, et al. "Switchblade: a platform for rapid deployment of network protocols on programmable hardware." SIGCOMM 10. 12. Emmerich, Paul, et al. "MoonGen: A Scriptable High-Speed Packet Generator." IMC 15. 13. Katta, Naga, et al. "HULA: Scalable Load Balancing Using Programmable Data Planes." SOSR 16. 14. Sivaraman, Anirudh, et al. "Towards Programmable Packet Scheduling." HotNets 15. 15. Jeyakumar, Vimalkumar, et al. "Millions of little minions: Using packets for low latency network programming and visibility." SIGCOMM 14.

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Yinda Zhang will present his general exam on Monday, May 09, 2016 at 10am in CS 402.
by Nicki Gotsis 02 May '16

02 May '16

Yinda Zhang will present his general exam on Monday, May 09, 2016 at 10am in CS 402. The members of his committee are Jianxiong Xiao (adviser), Tom Funkhouser, and Szymon Rusinkiewicz. Everyone is invited to attend his talk, and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. Reading list: [DalalTriggs] Histograms of oriented gradients for human detection. [SIFT] Distinctive image features from scale-invariant keypoints. [ExemplarSVMs] Ensemble of exemplar-svms for object detection and beyond. [DPM] Object Detection with Discriminatively Trained Part Based Models. [SelectiveSearch] Segmentation as selective search for object recognition. [Context] Auto-context and Its Application to High-level Vision Tasks [RCNN] Rich feature hierarchies for accurate object detection and semantic segmentation [Places] Learning Deep Features for Scene Recognition using Places Database. [Room Layout] Ecient Exact Inference for 3D Indoor SceneUnderstanding [Geometric Context] Geometric Context from a Single Image [Spatial Layout] Recovering the Spatial Layout of Cluttered Rooms Text book: Richard Szeliski, Computer Vision: Algorithm and Application Abstract: My research mainly focus on scene understanding, which includes a variety of topics to allow computer to perceive and interact with the surrounding environment. These topics, e.g. scene parsing, eye gaze tracking, scene classification, act as important roles in many critical robotics applications. The goal of scene parsing is to understand the spatial layout of the environment and localize objects in 3D space. Apart from traditional object recognition, scene parsing analyze the input image from a large scale that involves multiple objects, which allows the investigation of relationships among objects. Scene parsing also takes advantage of evidence beyond the visual appearance shown in the color or depth image, like past and future states of the object, underlying physics rule, functionality and interaction between human and objects. All of these key factors for scene understanding is more invariant and natural to be modeled in 3D space. Our first effort for 3D scene parsing is the PanoContext, which models an entire scene in 3D space. The experiments show that based solely on 3D context, PanoContext can achieve comparable performance with the state-of-the-art 2D object detectors. The output of the algorithm can be directly rendered in 3D for a virtual exploration of the indoor environment. Recently, we proposed a context-aware deep learning architecture for scene parsing. We hardwires the prior context knowledge into the network, which can be optimized end-to-end. The model requires only a single pass of the data to detect all the major objects in the room, and therefore is very efficient. Besides these, I also worked actively on creating large scaled dataset for scene classification, eye tracking saliency, and room layout estimation. Building a dataset with several magnitudes of bigger than the state of arts requires new interface and algorithm to enable data collection on crowd sourcing platform and achieve efficiency sub-linear to the scale of the data. While the scale of the 2D image dataset already goes to millions, RGBD images dataset still contains roughly 10K images, mostly due to the laborious labelling procedure. We are currently working on utilizing a large amount of unlabelled 3D reconstructed scene to learn a better feature representation for 3D object, and thus achieve better 3D object recognition performance.

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Hansen Zhang will be presenting his general exam on Monday, May 9, 2016 at 1pm in CS 402.
by Nicki Gotsis 02 May '16

02 May '16

Hansen Zhang will be presenting his general exam on Monday, May 9,2016 at 1pm in CS 402. The members of his committee are David August (adviser), David Wentzlaff and Arvind Narayanan. Everyone is invited to attend his talk, and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. Abstract: The TrustGuard architecture prevents the leakage of users’ information in the presence of malicious system components (processor and memory). The basis of trust in the system is a pluggable hardware element called the Sentry which physically separates the untrusted components and the interface to the outside world. To gain access to the external interfaces of the system, the untrusted components have to prove to the Sentry that their intended communication results from the correct execution of trusted software. This work improves upon the original TrustGuard design in two ways. First, it introduces optimizations that reduce the bandwidth requirements between the untrusted processor and the Sentry. Second, it adds protection from replay attacks to the original TrustGuard design. Simulation results show that the new design is able to reduce bandwidth by 60% while maintaining the performance of the original design and add protection from replay attacks. Reading List: Textbooks: John L. Hennessy and David A. Patterson. 2011. Computer Architecture, Fifth Edition: A Quantitative Approach (5th ed.). Morgan Kaufmann Publishers Inc., San Francisco, CA, USA. Ross J. Anderson. 2008. Security Engineering: A Guide to Building Dependable Distributed Systems (2 ed.). Wiley Publishing. Chapter 3,4,5,11,16 Papers: 1, Secure processors/coprocessors [1] G.E. Suh, D Clarke, B. Gassend, M. van Dijk, S. Devadas. AEGIS: architecture for tamper-evident and tamper-resistant processing. In Proceedings of the 17th annual international conference on Supercomputing, ICS’03, pages 160-171 [2] D. Y. Deng, D. Lo, G. Malysa, S. Schneider and G. E. Suh, "Flexible and Efficient Instruction-Grained Run-Time Monitoring Using On-Chip Reconfigurable Fabric," Microarchitecture (MICRO), 2010 43rd Annual IEEE/ACM International Symposium on, Atlanta, GA, 2010, pp. 137-148. [3] R. Kannavara and N. G. Bourbakis, "Surveying secure processors," in IEEE Potentials, vol. 28, no. 1, pp. 28-34, January-February 2009. [4] T. M. Austin, "DIVA: a reliable substrate for deep submicron microarchitecture design," Microarchitecture, 1999. MICRO-32. Proceedings. 32nd Annual International Symposium on, Haifa, 1999, pp. 196-207. 2, High Performance Caching [5] M. K. Qureshi, A. Jaleel, Y. N. Patt, S. C. Steely, and J. Emer. Adaptive insertion policies for high performance caching. In Proceedings of the 34th annual international symposium on Computer architecture (ISCA '07). ACM, New York, NY, USA, 381-391 [6] A. Jaleel, K. B. Theobald, S. C. Steely, Jr., and J. Emer. High performance cache replacement using re-reference interval prediction (RRIP). In Proceedings of the 37th annual international symposium on Computer architecture (ISCA '10). ACM, New York, NY, USA, 60-71 3, Compression [7] M. Thuresson, L. Spracklen and P. Stenstrom, "Memory-Link Compression Schemes: A Value Locality Perspective," in IEEE Transactions on Computers, vol. 57, no. 7, pp. 916-927, July 2008. [8] X. Chen, L. Yang, R. Dick, L. Shang and H. Lekatsas, "C-Pack: A High-Performance Microprocessor Cache Compression Algorithm," in IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 18, no. 8, pp. 1196-1208, Aug. 2010. 4, Memory Integrity Verification [9] B. Gassend, G. E. Suh, D. Clarke, M. van Dijk and S. Devadas, "Caches and hash trees for efficient memory integrity verification," High-Performance Computer Architecture, 2003. HPCA-9 2003. Proceedings. The Ninth International Symposium on, 2003, pp. 295-306. [10] B. Rogers, S. Chhabra, M. Prvulovic and Y. Solihin, "Using Address Independent Seed Encryption and Bonsai Merkle Trees to Make Secure Processors OS- and Performance-Friendly," Microarchitecture, 2007. MICRO 2007. 40th Annual IEEE/ACM International Symposium on, Chicago, IL, 2007, pp. 183-196.

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systems lunch talk 12:30-1:30pm (with noon-12:30pm lunch) on Monday May 2 in CS 302
by Jennifer Rexford 01 May '16

01 May '16

Speaker: Asaf Cidon, Stanford Unviersity Title: Cliffhanger: Scaling Performance Cliffs in Web Memory Caches Date/time: 12:30-1:30pm Monday May 2, with lunch available starting at noon Location: CS 302 Abstract: Web-scale applications are heavily reliant on memory cache systems such as Memcached to improve throughput and reduce user latency. Small performance improvements in these systems can result in large end-to-end gains. By analyzing measurements from a widely used caching service, Memcachier, we demonstrate that existing cache allocation techniques leave significant room for improvement. We develop Cliffhanger, a lightweight iterative algorithm that runs on memory cache servers, which incrementally optimizes the resource allocations across and within applications based on dynamically changing workloads. We also present our long term vision for a centrally controlled data center caching layer that manages applications' varying workloads across heterogeneous caches. Bio: Asaf Cidon is the CEO and co-founder of Sookasa, which was acquired by Barracuda Networks in March 2016. He completed his PhD at the Stanford University Computer Systems Lab, where he conducted research on cloud storage under Professors Mendel Rosenblum and Sachin Katti. Asaf previously worked at Google Israel in the web search team and served as a team leader in the Israeli army. He obtained his PhD and MS in Electrical Engineering from Stanford and his BS in Computer and Software Engineering Cum Laude from the Technion. In addition, he is a recipient of the Stanford Graduate Fellowship and Sohnis Promising Scientist Award.

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Sergiy Popovych will be presenting his General Exam on Tuesday, May 3, 2016 at 2pm in CS 402.
by Nicki Gotsis 29 Apr '16

29 Apr '16

Sergiy Popovych will be presenting his General Exam on Tuesday, May 3, 2016 at 2pm in CS 402. The members of his committee are David August (adviser), Nick Feamster and Arvind Narayanan. Everyone is invited to attend his talk, and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. As has been demonstrated time and again, almost all systems can be compromised. Connecting to an external network through a unidirectional gateway physically disallows any outgoing traffic, and thus prevents data theft. Existing unidirectional gateways act as stateless links, only supporting inherently unidirectional applications. In an attempt to support applications that require request/response behavior (e.g. web browsing), Starlight adds a second, bidirectionally connected machine not entrusted with sensitive information, which improves usability but makes the system vulnerable to attacks involving the user (e.g. phishing, insider attacks). This work demonstrates the benefit of making unidirectional gateways stateful. The proposed solution, Moonshine, uses this state to pre-cache content from the external network, after which an illusion of request/reply behavior can be achieved, thus partially supporting such applications as web browsing and software updates without compromising security. Books: [1] Ross J. Anderson. 2008. Security Engineering: A Guide to Building Dependable Distributed Systems (2 ed.). Wiley Publishing. (Chapters 2, 3, 4, 6, 8, 9, 21) [2] Asaf Shabtai, Yuval Elovici, Lior Rokach. 2012. A Survey of Data Leakage Detection and Prevention Solutions. Springer US. Papers: [1] J. H. Saltzer, D. P. Reed, and D. D. Clark. 1984. End-to-end arguments in system design. ACM Trans. Comput. Syst. 2, 4 (November 1984), 277-288. [2] David L. Chaum. 1981. Untraceable electronic mail, return addresses, and digital pseudonyms. Commun. ACM 24, 2 (February 1981), 84-90. [3] M. H. Kang and I. S. Moskowitz, "A Pump for rapid, reliable, secure communication", Proc. ACM Conf. Computer Commun. Security, pp. 119-129, 1993. [4] M. Anderson, C. North, J. Griffin, R. Milner, J. Yesberg and K. Yiu, "Starlight: Interactive Link," Computer Security Applications Conference, 1996., 12th Annual, San Diego, CA, 1996, pp. 55-63. [5] R. T. Barker and C. J. Cheese, "The application of data diodes for securely connecting nuclear power plant safety systems to the corporate IT network," System Safety, incorporating the Cyber Security Conference 2012, 7th IET International Conference on, Edinburgh, 2012, pp. 1-6. [6] B. S. Jeon and J. C. Na, "A study of cyber security policy in industrial control system using data diodes," 2016 18th International Conference on Advanced Communication Technology (ICACT), Pyeongchang, 2016, pp. 314-317. [7] J. Epstein, "Fifteen Years after TX: A Look Back at High Assurance Multi-Level Secure Windowing," 2006 22nd Annual Computer Security Applications Conference (ACSAC'06), Miami Beach, FL, 2006, pp. 301-320. [8] Eric Byres. 2013. The air gap: SCADA's enduring security myth. Commun. ACM 56, 8 (August 2013), 29-31 [9] Butler W. Lampson. 1973. A note on the confinement problem. Commun. ACM 16, 10 (October 1973), 613-615. [10] A. Wool. 2004. A Quantitative Study of Firewall Configuration Errors. Computer 37, 6 (June 2004), 62-67.

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Xiaozhou Li will present his FPO on Thursday, 5/5/2016 at 2pm in CS 302 "Systems and Algorithms for High-Performance, Cost-Efficient Key-Value Storage"
by Nicki Gotsis 28 Apr '16

28 Apr '16

Xiaozhou Li will present his FPO on Thursday, 5/5/2016 at 2pm in CS 302 "Systems and Algorithms for High-Performance, Cost-Efficient Key-Value Storage" The members of his committee are Michael Freedman (adviser); Kyle Jamieson and Michael Kaminsky (Intel) (Readers); Jennifer Rexford and Kai Li (examiners). A copy of his thesis is available in Room 310. Everyone is invited to attend his talk. The talk abstract follow below. Key-value storage systems are increasingly essential building blocks of modern cloud and big data applications. The workloads these systems support often require random access to small objects over massive datasets with highly skewed and dynamic key popularity. It is challenging for a storage cluster to serve these workloads with both high performance and low-cost operations. Today’s systems usually sacrifice one for the other. In this dissertation, we present novel approaches to improve both the performance and cost-efficiency of key-value systems by combining new hardware and software techniques with careful architectural design and algorithmic optimizations. First, at cluster scale, we build SwitchKV, a heterogeneous system that uses small highend cache nodes to guarantee load balancing across many SSD-based backend nodes under nearly-arbitrary workloads. The cache nodes absorb the hottest queries so that no individual backend node is over-burdened or underutilized. The system exploits OpenFlow switches to enable efficient content-aware routing so that it can achieve scalable high throughput, low tail latency, and high availability. It uses new algorithms to keep the cache and switch forwarding rules updated with low overhead, and to ensure stable high performance under rapidly changing workloads. SwitchKV can meet the service level objectives for many cloud services more efficiently than traditional systems. Second, to improve the efficiency of each individual multi-core server, we build a highthroughput and memory-efficient concurrent hash table based around optimistic cuckoo hashing. Our re-design minimizes critical section length, reduces interprocessor coherence traffic, and enables effective prefetching through careful algorithm and data structure engineering. We explore hardware transactional memory and fine-grained locking for concurrency control, and find that both of them require the same level of algorithmic efforts to achieve high performance. Our new hash table design greatly outperforms other optimized concurrent hash tables for both read- and write-heavy workloads, even while using substantially less memory for small key-value items.

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Swati Roy will present her General Exam Wednesday, May 4, 2016 in CS 302 at 2:30pm
by Nicki Gotsis 27 Apr '16

27 Apr '16

The members of her committee are Nick Feamster (Adviser), Jennifer Rexford, and Kyle Jamieson. Everyone is invited to attend her talk, and those faculty wishing to remain for the oral exam following are welcome to do so. Please find her abstract and reading list below. Abstract: As smartphone users increasingly rely on cellular networks to access voice, video, and web applications, guaranteeing good performance and high availability is more important than ever. Historically, managing cellular network configuration has been a manual, error-prone process; recently, however, automated solutions such as SON (Self Organizing Networks) controllers are being deployed for dynamic tuning of network configuration. Self-organizing networks (SON) are a new paradigm in cellular networks that dynamically react to changes in network and traffic conditions, automatically adjusting the network configuration to improve performance for end users. For example, when a cell tower becomes congested, a SON controller might automatically tune the transmission power or antenna tilt of neighboring cell towers to better distribute load. Large cellular network providers are currently deploying SON in their cellular networks to improve end-user performance for voice, video, and web applications. SON automates many aspects of cellular network configuration, but it is nonetheless susceptible to software bugs. Additionally, if it is configured incorrectly, it may provide suboptimal performance for particular network conditions and traffic load. One of the biggest challenges in SON configuration is determining how a configuration change affects the performance that end users experience. Existing systems are based on classic time-series prediction, and compare the performance between a study group (where a particular configuration change was implemented) and a control group (where the change was not implemented) to tackle the impact of external factors or rely on comparisons of a particular configuration change against a baseline. Yet, because a SON controller operates in a dynamic environment, isolating the effects of any single configuration change against a control group or a baseline is incredibly difficult. We propose a capability (Veracity) to analyze and quantify the performance effects of SON actions. Assessing the effects of SON control is difficult because of the dynamic nature of SON and the dependency of end-user performance on factors such as radio channel quality, mobility and traffic load. Veracity addresses these using model-driven impact detection and quantification. Our evaluation using data collected from an operational cellular network demonstrates that Veracity is accurate. Veracity is now being used by the service providers' field operation teams for the assessment of SON effectiveness in arenas and stadiums. Reading List: [1] Ajay Mahimkar, Han Hee Song, Zihui Ge, Aman Shaikh, Jia Wang, Jennifer Yates, Yin Zhang, Joanne Emmons: Detecting the performance impact of upgrades in large operational networks. In ACM SIGCOMM, 2010. [2] A. Mahimkar, Z. Ge, J. Yates, C. Hristov, V. Cordaro, S. Smith, J. Xu, and M. Stockert: Robust assessment of changes in cellular networks. In ACM CoNEXT, 2013. [3] M. Shafiq, L. Ji, A. Liu, J. Pang, S. Venkataraman, and J. Wang: A first look at cellular network performance during crowded events. In SIGMETRICS, 2013. [4] M. Zubair Shafiq, Lusheng Ji, Alex X. Liu, Jia Wang: Characterizing and Modeling Internet Traffic Dynamics of Cellular Devices, In SIGMETRICS, 2011. [5] S. Sundaresan, W. de Donato, N. Feamster, R. Teixeira, S. Crawford, and A. Pescape: Broadband Internet Performance: A View From the Gateway . In SIGCOMM, Aug. 2011. [6] Srikanth Sundaresan , Nick Feamster , Renata Teixeira: Measuring the Performance of User Traffic in Home Wireless Networks. In PAM, 2015 [7] Mingzhe Li, Feng Li, Mark Claypool, and Robert Kinicki: Weather Forecasting - Predicting Performance for Streaming Video over Wireless LANs, In NOSSDAV, June 2005. [8] Naga Katta, Haoyu Zhang, Michael Freedman, and Jennifer Rexford. Ravana: Controller Fault-Tolerance in Software-Defined Networking, In SIGCOMM Symposium For SDN Research (SOSR), June 2015. [9] Athula Balachandran, Vaneet Aggarwal, Emir Halepovic, Jeffrey Pang, Srinivasan Seshan, Shobha Venkataraman, He Yan: Modeling Web Quality-of-Experience on Cellular Networks. In MobiCom 2014. [10] Xin Jin, Li Erran Li, Laurent Vanbever, and Jennifer Rexford. SoftCell: Scalable and Flexible Cellular Core Network Architecture. In CoNext 2013. [11] L. L. Peterson and B. S. Davie. Computer Networks, Fifth Edition: A Systems Approach. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 5th edition, 2011. Best, Swati

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Yixin Sun will present her General Exam on Monday, May 2, 2016 at 10:15am in CS 402
by Nicki Gotsis 25 Apr '16

25 Apr '16

Yixin Sun will present her General Exam on Monday, May 2, 2016 at 10:15am in CS 402. The members of her committee are Mung Chiang & Prateek Mittal (advisers), Nick Feamster, and Arvind Narayanan. Everyone is invited to attend her talk, and those faculty wishing to remain for the oral exam following are welcome to do so. Her abstract and reading list follow below. Abstract: The Tor network is a widely used system for anonymous communication. However, the vulnerability of the Tor network to adversaries who can monitor Internet traffic, such as Autonomous Systems (ASes), is not well understood. We present a suite of new attacks, called Raptor, that can be launched by Autonomous Systems (ASes) to compromise user anonymity. First, AS-level adversaries can exploit the asymmetric nature of Internet routing to increase the chance of observing at least one direction of user traffic at both ends of the communication. Second, strategic adversaries can manipulate Internet routing via BGP hijacks (to discover the users using specific Tor guard nodes) and interceptions (to perform traffic analysis). We demonstrate the feasibility of Raptor attacks by performing real-world attacks on the live Tor network, while ensuring that we do not harm real users. Third, we measure the vulnerability of the Tor network to such active BGP attacks. We show that more than 90% of BGP prefixes hosting Tor relays are vulnerable to more-specific prefix attacks, and some Autonomous Systems that carry a large portion of Tor traffic, such as OVH, also have low resilience to equally-specific prefix attacks. Finally, we present the BGP monitoring system that detects routing anomalies on the Tor network in real time. We evaluate the system on live BGP data and show that it has no false positives while successfully detects an attack injected by us. Reading list: Computer Networks (5th Edition) by TANENBAUM and WETHERALL. Chapters 1, 5-8. Security Engineering (2nd Edition) by Anderson. Chapters 1-8, 21-24. 1. Ballani, H., Francis, P. and Zhang, X., 2007, August. A study of prefix hijacking and interception in the Internet. In ACM SIGCOMM Computer Communication Review (Vol. 37, No. 4, pp. 265-276). ACM. 2. Lad, M., Oliveira, R., Zhang, B. and Zhang, L., 2007, June. Understanding resiliency of internet topology against prefix hijack attacks. In Dependable Systems and Networks, 2007. DSN'07. 37th Annual IEEE/IFIP International Conference on (pp. 368-377). IEEE. 3. Lad, M., Massey, D., Pei, D., Wu, Y., Zhang, B. and Zhang, L., 2006, August. PHAS: A Prefix Hijack Alert System. In Usenix Security. 4. Dingledine, R., Mathewson, N. and Syverson, P., 2004. Tor: The second-generation onion router. Naval Research Lab Washington DC. 5. Johnson, A., Wacek, C., Jansen, R., Sherr, M. and Syverson, P., 2013, November. Users get routed: Traffic correlation on Tor by realistic adversaries. In Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security (pp. 337-348). ACM. 6. Murdoch, S.J. and Zieliński, P., 2007, June. Sampled traffic analysis by internet-exchange-level adversaries. In Privacy Enhancing Technologies (pp. 167-183). Springer Berlin Heidelberg. 7. Akhoondi, M., Yu, C. and Madhyastha, H.V., 2012, May. LASTor: A low-latency AS-aware Tor client. In Security and Privacy (SP), 2012 IEEE Symposium on (pp. 476-490). IEEE. 8. Edman, M. and Syverson, P., 2009, November. AS-awareness in Tor path selection. In Proceedings of the 16th ACM conference on Computer and communications security (pp. 380-389). ACM. 9. Feamster, N. and Dingledine, R., 2004, October. Location diversity in anonymity networks. In Proceedings of the 2004 ACM workshop on Privacy in the electronic society (pp. 66-76). ACM. 10. Starov, O., Nithyanand, R., Zair, A., Gill, P. and Schapira, M., 2015. Measuring and mitigating AS-level adversaries against Tor. arXiv preprint arXiv:1505.05173.

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Fwd: EE Seminar - April 28, 2016, 11:00 am, E-Quad B205 - Dr. Zhichun Li
by Jennifer Rexford 25 Apr '16

25 Apr '16

> > From: Sania Sadhvani <sadhvani(a)Princeton.EDU> > Subject: EE Seminar - April 28, 2016, 11:00 am, E-Quad B205 - Dr. Zhichun Li > Date: April 25, 2016 at 2:54:21 PM EDT > To: ee-seminar(a)Princeton.EDU > Reply-To: Sania Sadhvani <sadhvani(a)Princeton.EDU> > > > DEPARTMENT OF > ELECTRICAL ENGINEERING SEMINAR SERIES > > > > > Speaker: Zhichun Li > NEC Research Labs > Title: Counter Advanced Persistent Threat through Big-Data Enabled Security > Intelligence > Date: April 28, 2016 > Time: 11:00 a.m. > Room: B205 Engineering Quadrangle > Host: Prof. Prateek Mittal > > Abstract: Today serious security incidents keep appearing in mainstream media. Cyber-attack is no longer just for fun but has grown up and become a large dark industry. Data breaches from Target, Home Depot, JP Morgan Chase, Sony, eBay, OPM.gov etc., not only cause severe impact to the business or government agency, but also affect millions of people. The attacks behind the scene are so call Advanced Persistent Threats (APTs). In this talk, I will introduce what is an APT, and what characteristics those attacks have by going through a case study on how Target got hacked. Then, I will examine why APT is hard to detect by existing industry security solutions, and potentially how we can do better. To fight against APT, we started the Automated Security Intelligence (ASI) project in 2012, and later found DARPA Transparent Computing (TC) program BAA in 2014 shared the same vision, which is “connecting the dots” across multiple activities that are individually not suspicious enough, but collectively indicate malice or abnormal behavior. The ASI project achieves ubiquitous monitoring inside enterprises with Windows, Linux and Mac agents, includes a big-data middleware to handle the massive events collected, and provides a platform that supports various security applications. In particular, in this talk, I will highlight research progress from two early efforts on “connecting the dots”: temporal behavior query language, which enables a search tool for security analysts to quickly explore the potential linkage among events, and activity backtracking, which is a semi-automatic tool on answering “how this happens”. > > Biography: Zhichun (ZL) Li is a senior researcher at NEC Research Labs in Princeton, NJ. At NEC Labs, he manages the newly formed Computer Security Department. He has initiated and led the large-scale interdisciplinary research project called Automated Security Intelligence involving 15 researchers from Princeton and Tokyo. He has broad research interests in the areas of security and systems with an emphasis on enterprise security with big-data, smartphone security, network security etc. Before joining NEC Labs, he received his Ph.D. on Dec 2009 from Northwestern University. He earned both M.S. and B.S. degrees from Tsinghua University in China. Previously, he has conducted research at Microsoft Research Redmond and International Computer Science Institute (ICSI) in UC Berkeley. > > > > > > > > > > >

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Colloquium Speaker Ben Shneiderman, Today, 12:30pm
by Nicole E. Wagenblast 22 Apr '16

22 Apr '16

Colloquium Speaker Ben Shneiderman, University of Maryland Friday, April 22, 12:30pm Computer Science 105 The New ABCs of Research: Achieving Breakthrough Collaborations All Princeton ACM / IEEE-CS meetings are open to the public. Students and their parents are welcome. How should we organize research programs in computer science and technology? Research helps us produce innovative new products (the next iPhone), and research also delivers “foundational theories” (new algorithms and supporting technologies). Solving the immense problems of the 21st century will require ambitious research teams that are skilled at producing practical solutions and foundational theories simultaneously – that is the ABC Principle: Applied & Basic Combined. Then these research teams can deliver high-impact outcomes by applying the SED Principle: Blend Science, Engineering and Design Thinking, which encourages use of the methods from all three disciplines. These guiding principles (ABC & SED) are meant to replace Vannevar Bush’s flawed linear model from 1945 that has misled researchers for 70+ years. These new guiding principles will enable students, faculty, business leaders, and government policy makers to accelerate discovery and innovation. The examples in the talk will emphasize how these guiding principles can be applied to reinvigorate computing research. Ben Shneiderman is a Distinguished University Professor in the Department of Computer Science at the University of Maryland. He is also the Founding Director (1983-2000) of the Human-Computer Interaction Laboratory (http://www.cs.umd.edu/hcil/), and a Member of the University of Maryland Institute for Advanced Computer Studies (UMIACS). He is a Fellow of the AAAS, ACM, IEEE, and NAI, and a Member of the National Academy of Engineering, in recognition of his pioneering contributions to human-computer interaction and information visualization. His contributions include the direct manipulation concept, clickable highlighted web-links, touchscreen keyboards, dynamic query sliders for Spotfire, development of treemaps, novel network visualizations for NodeXL, and temporal event sequence analysis for electronic health records. Ben is the co-author with Catherine Plaisant of Designing the User Interface: Strategies for Effective Human-Computer Interaction (6th ed., 2016). His book Leonardo’s Laptop (MIT Press) won the IEEE book award for Distinguished Literary Contribution. Shneiderman’s latest book is The New ABCs of Research: Achieving Breakthrough Collaborations (Oxford, February 2016).

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