1. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 1 Research in Networking Dong Xuan Dept. of Computer Science and Engineering The Ohio State University

2. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 2 Outline r Group Research Overview r Performance - Optimal Deployment in Wireless Sensor Networks r Security - Flow Marking in the Internet

3. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 3 Group Members r Student members: Xiaole Bai, Adam Champion, Sriram Chellappan (to be assistant professor in Univ. of Missouri at Rolla), Boxuan Gu, Wenjun Gu, Thang Le, Zhimin Yang r Former members: Sandeep Reddy (M.S., 2004, Microsoft), Lamonte Glove (M.S., 2004, Avaya) and Kurt Schosek (M.S., 2005), Xun Wang (Ph.D, 2007, CISCO) r Faculty member: Dong Xuan

4. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 4 Research Interests r Real-time computing and communications m Deterministic and statistic QoS guarantees [ICDCS00, INFOCOM01, RTSS01, ToN04] m Voice over IP [RTAS02, TPDS05] r Performance m Topology control [MOBIHOC06, INFOCOM08] m Mobility control [TPDS06, TMC07] r Security m Internet security Overlay security [ICDCS04, TPDS06] Anonymous communications [IPDPS05, SP07, INFOCOM08_mini] Worm/Malware defense[SECURECOM06, 07, ACSAC06] m Wireless network security [IWQoS06, TPDS06]

5. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 5 Research Grants r ARO: “Defending against Physical Attacks in Wireless Sensor Networks”, (PI, 2007-2010) r NSF: “Efficient Resource Over-Provisioning for Network Systems and Services”, (PI, CAREER award, 2005-2010) r NSF: “Overlay Network Support to Remote Visualization on Time-Varying Data”, (PI, 2003- 2006) r SBC/Ameritech: “Providing Statistic Real-time Guarantees to Multimedia Teleconferences”, (PI, 2002-2003)

6. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 6 Performance: Optimal Deployment Patterns in WSNs r Xiaole Bai, Santosh Kumar, Dong Xuan, Ziqiu Yun and Ten H. Lai, Deploying Wireless Sensors to Achieve Both Coverage and Connectivity, in ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), 2006 r Xiaole Bai, Ziqiu Yun, Dong Xuan, Ten H. Lai and Weijia Jia, Deploying Four-Connectivity And Full-Coverage Wireless Sensor Networks, in IEEE International Conference on Computer Communications (INFOCOM), 2008

7. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 7 Problem Definition r What is the optimal number of sensors needed to achieve p-coverage and q-connectivity in WSNs? r An important problem in WSNs: m Connectivity is for information transmission and coverage is for information collection m Avoid ad hoc deployment to save cost m To help design topology control algorithms and protocols m other practical benefits The Ohio State University

8. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 8 p-Coverage and q-Connectivity r q-connectivity: there are at least q disjoint paths between any two sensors r p-coverage: every point in the plane is covered by at least p different sensors rsrs rcrc Node A Node B For example, nodes A, B, C and D are two connected Node C Node D

9. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 9 Relationship between r s and r c r Most existing work is focused on r In reality, there are various values of  The communication range of the Extreme Scale Mote (XSM) platform is 30 m and the sensing range of the acoustics sensor is 55 m  Sometimes even when it is claimed for a sensor to have, it may not hold in practice because the reliable communication range is often 60-80% of the claimed value

10. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 10 A Big Picture Research on Asymptotically Optimal Number of Nodes [1] R. Kershner. The number of circles covering a set. American Journal of Mathematics, 61:665–671, 1939, reproved by Zhang and Hou recently. [2] R. Iyengar, K. Kar, and S. Banerjee. Low-coordination topologies for redundancy in sensor networks. MobiHoc2005. MobiHoc06 INFOCOM 08

11. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 11 Known Results: Triangle Pattern [1] Notice it actually achieves 1-coverage and 6-connectivity d1 d2

12. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 12 r Place enough disks between the strips to connect them m See the paper for a precise expression m The number is disks needed is negligible asymptotically Our Optimal Pattern for 1-Connectivity Note : it may be not the only possible deployment pattern

13. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 13 r Connect the neighboring horizontal strips at its two ends Our Optimal Pattern for 2-Connectivity Note : it may be not the only possible deployment pattern

14. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 14 Our Optimal Pattern for 4-Connectivity Note : it may be not the only possible deployment pattern Square pattern

15. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 15 Our Optimal Pattern for 4-Connectivity Note : it may be not the only possible deployment pattern d1 d2 A Diamond pattern

16. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 16 Workflow of optimality proof (1) r Step 1 m We lay out the theoretical foundation of the optimality proof: for any collection of the Voronoi polygons forming a tessellation, the average edge number of them is not larger than six asymptotically. It is built on the well known Euler formula. r Step 2 m We show that any collection of Voronoi polygons generated in any deployment can be transformed into the same number of Voronoi polygons generated in a regular deployment while full coverage and desired connectivity can still be achieved. The proof is based on the technique of pattern transformation and the theoretical foundation obtained in Step 1.

17. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 17 Workflow of optimality proof (2) r Step 3 m We prove the number of Voronoi polygons from any regular deployment has a lower bound. r Step 4 m We show that the number of Voronoi polygons used in the patterns we proposed is exactly the lower bound value. Hence the patterns we proposed are the optimal in all regular deployment patterns. Based on the conclusion obtained in Step 2, the patterns we proposed are also the optimal among all the deployment patterns.

18. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 18 Future Work Research on Asymptotically Optimal Number of Nodes

19. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 19 Security: Flow Marking Techniques in the Internet Security r Wei Yu, Xinwen Fu, Steve Graham, Dong Xuan and Wei Zhao, DSSS-Based Flow Marking Technique for Invisible Traceback, in Proc. of IEEE Symposium on Security and Privacy (Oakland), May 2007, pp18-32 r Xun Wang, Wei Yu, Xinwen Fu, Dong Xuan and Wei Zhao, iLOC: An invisible LOCalization Attack to Internet Threat Monitoring System, accepted to appear in the mini-conference conjunction with IEEE International Conference on Computer Communications (INFOCOM), April 2008.

20. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 20 Invisible Traceback in the Internet r Internet has brought convenience to our everyday lives r However, it has also become a breeding ground for a variety of crimes r Network forensics has become part of legal surveillance r We study flow marking for a fundamental network-based forensic technique, traceback

21. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 21 Problem Definition r Suspect Sender is sending traffic through encrypted and anonymous channel, how can Investigators trace who is the receiver? Receiver Sender Network

22. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 22 Traffic Confirmation by Flow Marking r Investigators want to know if Sender and Receiver are communicating Receiver Sender Sniffer Interferer Anonymous Channel The investigators know that Sender communicates with Receiver Investigator HQ

23. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 23 Issues in Flow Marking r Traceback accuracy m Periodic pattern ok? r Traceback secrecy m Traceback without conscience of suspects DSSS-based technique for accuracy and secrecy in traceback!

24. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 24 Basic Direct Sequence Spread Spectrum (DSSS) r A pseudo-noise code is used for spreading a signal and despreading the spread signal DespreadingSpreading PN Code Original Signal tbtb ctct dtdt PN Code crcr Recovered Signal noisy channel InterfererSniffer rbrb drdr

25. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 25 Example – Spreading and Despreading r Signal d t : 1 -1 r DSSS code c t : 1 1 1 -1 1 -1 -1 r Spread signal t b =d t.c t =1 1 1 -1 1 -1 -1 -1 -1 -1 +1 -1 1 1 m One symbol is “represented” by 7 chips m PN code is random and not visible in time and frequency domains r Despreading is the reverse process of spreading +1 dtdt t ctct +1 T c (chip) t NcTcNcTc t tbtb

26. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 26 Mark Generation by Interferer 1.Choose a random signal 2.Obtain the spread signal 3.Modulate a target traffic flow by appropriate interference  Chip +1: without interference  Chip -1: with interference  Low interference favors traceback secrecy PN Code Original Signal d t Flow Modulator Internet rx = spread signal + noise tbtb ctct tx

27. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 27 Mark Recognition by Sniffer 1.Sample received traffic to derive traffic rate time series 2.Use high-pass filter to remove direct component by Fast Fourier Transform (FFT) 3.Despreading by local DSSS code 4.Use low-pass filter to remove high-frequency noise 5.Make decision  Recovered signal == Original signal? PN Code Decision Rule rx = spread signal + noise High-pass Filter Low-pass Filter rx’ rbrb crcr

28. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 28 Invisible Location Attack to Internet Monitoring Systems r Widespread attackers attempt to evade the distributed monitoring/detection systems m We design invisible LOCalization (iLOC) attack which can locate the detection monitors accurately and invisibly. Then the widespread attacks can evade these located monitors. r Effectiveness of iLOC attack m We implement iLOC attack, carry out experiments and analyze the effectiveness of iLOC attack.

29. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 29 Internet Threat Monitoring Systems Global traffic monitoring based Internet Threat Monitor Systems (ITM): - Distributed monitors - Data center Data center monitors Network A Network B Internet Attacker Network C MONITORS’ LOG UPDATE monitors Attacker  A vulnerability: location privacy of monitors (ITM only monitors a small part of whole IP address space.)

30. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 30 invisible LOCalization Attack Basic idea: Verify attack traffic in traffic report, verify existence of monitors. Two Stages: - Attack traffic generating - Attack traffic decoding Embed an attack mark in the attack traffic, which can be recognized by the attacker.

31. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 31 Final Remarks r Group research: theorem and implementation r Research on Performance m Optimal deployment pattern in WSNs m Limited mobility WSNs r Research Security m Flow marking in internet security m Worm detection m Wireless security

32. Dong Xuan: CSE885 on 11/07/07 The Ohio State University 32 Thank you ! Questions?