Opportunistic Networks: The Concept and Research Challenges

1. Opportunistic Networks:The Concept and Research Challenges Leszek Lilien, Zille Huma Kamal and Ajay Gupta In cooperation with: Vijay Bhuse and Zijiang (James) Yang Wireless Sensornet Laboratory (WiSe Lab) http://www.cs.wmich.edu/wsn Department of Computer Science Western Michigan University Kalamazoo, MI 49008

2. Basic Concepts for Opportunistic Networks • New paradigm and technology: Opportunistic Networks (Oppnets) • Facing thechallenge of Pervasive Computing • Advancing leading-edge pervasive computing and networking know-how • Applications ranging from EPR to mundane chores, etc. 2

3. Link to the World Wireless Nodes Base Station Startup: Seed Oppnet • Oppnet starts as a seedoppnet • Seed oppnet grows into an expandedoppnet 3

4. Satellite Link to the World Appliance (refrigerator) Cellphone Tower Wireless Nodes Base Station Microwave Relay Computer Network Overturned Vehicle with OnStar Growth: Expanded Oppnet • Heterogenous helpers join oppnet • Add communication, computing, sensing, storage, other resources 4

5. Important Concepts in Oppnets • Initial seed oppnet actions • Localize nodes • Configure seed oppnet • Adapt seed oppnet to environment • Seed oppnet growth • Detecting & identifying candidate helpers • Contacting & inviting selected candidate helpers • Admitting & integrating helpers • Offloading tasks to helpers • Determining useful colaborative functionalities • Managing offloaded tasks 5

6. Basic Oppnet Categories • 2 major oppnet categories: • Benevolent oppnets • Malevolent oppnets • Corresponding oppnets scenarios: • Benevolent oppnet scenario: “Citizens Called to Arms” • Malevolent oppnet scenario: “Bad Guys Gang Up” 6

7. 7 BenevolentOppnetScenario: “Citizens Called to Arms” (1) • Seed oppnet deployed after an earthquake (unpredictable disaster) • Seed is ad hoc wireless network with very powerful nodes • More energy, computing and communication resources • Seed tries to detect candidate helpers • For help in damage assessment and disaster recovery • Uses any available detection method — including: • Radio-based (including cellphone-based) detection • Searching for nodes using the IP address range for the affected geographic area • AI-based visual detection • E.g., visual detection of an overturned car via surveillance net / recognition of its license plate / finding OnStarconnection to it / contacting Body Area Networks on or within bodies of car occupants 7

8. 8 BenevolentOppnetScenario: “Citizens Called to Arms” (2) • Oppnet selects optimal subset of detected nodes • Invitingdevices, clusters & entire networks • Helpers for communicating, sensing, computing • Using“hidden” capabilities, e.g. for sensing: • Desktop can „sense” location of a potential victim at its keyboard • Cellphones can „sense” location (even ones w/o GPS can be triangulated) • Using emergency functionalities • Oppnet contacts 2 independent sensornets (SNs): water infrastructure control SN / public space surveillance SN • Ordered to abandon normal functions& help in disaster recovery • Water infrastructure SN(with multisensor capabilities, under road surfaces) —to sense vehicular movement and traffic jams • Public space surveillance SN —to search for images of human victims 8

9. MalevolentOppnetScenario: “Bad Guys Gang Up” (1) 9 • Scenario 1 — Terrorists createapparently harmless weather monito- ring sensornet (SN): • SN becomes a seed of a malevolent opportunistic SN • SN exploits other nodes from many other networks(w/o revealing its true goals) • “Critical mass” of the opportunistic SN is reached (in terms of geographical spread and sensing capabilities) • SN waits for wind patterns that can speed up spread of poisonous chemicals • Collected data used to decide when to start chemicalattack 9

10. MalevolentOppnetScenario: “Bad Guys Gang Up” (2) • Scenario 2 — network at home starts spying on you: • Becomes a seed oppnet • Exploits other devices/nets to collect all info on you: • From your fridge(& RFID-equipped food packaging): what/when you eat • From your computer: keylogs your passwords, sensitive data • From your cellphone: who you call & when • From your networked camera: what photos you take • From your home security surveillance system: your private images • Cyberfly with camera eyes and microphone ears • ... • Huge privacy problem! / Huge security problem! • Controls to counteract malevolent oppnets badly needed 10

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12. Section 2:Research Challengesfor Basic Oppnets Operations • Presented in the order defined by the order of basic oppnet operations • Security/privacy challenges covered later in Section 3 12

13. Deploy seed oppnet Need to grow? NO YES GROWTH Detect candidate helpers (system) Enough good candidates? Command Center NO YES Admit candidates into oppnet Integrate helper’s resources Collaborative processing Workdone? Clean up all helpers Release helpers NO YES 13

14. Challenges in Seed Oppnet Deployment • Localization • Self-configuration & reconfiguration • Adaptability 14

15. Deploy seed oppnet Need to grow? NO YES GROWTH Detect candidate helpers (system) Enough good candidates? Command Center NO YES Admit candidates into oppnet Integrate helper’s resources Collaborative processing Workdone? Clean up all helpers Release helpers NO YES 15

16. Challenges in DetectingHelper Systems (1) • Develop primitives/methods to detecthelpers • Overheterogeneous communication media • Wired/WiFi • Bluetooth • Satellite • Ham radios • …  ability to integrate diverse technologies 16

17. Challenges in DetectingHelper Systems (2) • Identify and categorize detected candidates • E.g., a system detect on Bluetooth: is it cellphone or laptop? • Classify detected candidates • Based on dependability and usefulness • Evaluate candidates • Can given candidate facilitate oppnet operations? 17

18. Deploy seed oppnet Need to grow? NO YES GROWTH Detect candidate helpers (system) Enough good candidates? Command Center NO YES Admit candidates into oppnet Integrate helper’s resources Collaborative processing Workdone? Clean up all helpers Release helpers NO YES 18

19. Invite & Admit Candidate Helpers • Select candidates to invite • Design primitives/methods to send invitations • Develop methods that enable helper toaccept or reject invitation • Candidates are helpersnot slaves • But in emergency situations could be forced to joined • Design primitives/methods to admithelper into oppnet • Devise primitives/methods to manage expanded oppnet 19

20. Deploy seed oppnet Need to grow? NO YES GROWTH Detect candidate helpers (system) Enough good candidates? Command Center NO YES Admit candidates into oppnet Integrate helper’s resources Collaborative processing Workdone? Clean up all helpers Release helpers NO YES 20

21. Integrate Helper Resources • Select goals to be facilittated by helpers • Determine tasks to be offloaded to helpers • Coordinate all tasks 21

22. Deploy seed oppnet Need to grow? NO YES GROWTH Detect candidate helpers (system) Enough good candidates? Command Center NO YES Admit candidates into oppnet Integrate helper’s resources Collaborative processing Workdone? Clean up all helpers Release helpers NO YES 22

23. Collaborative Processing • Collaborative tasks: • Growth • Data collection and querying • Data aggregation / information fusion • Routing • Assuring connectivity • ... • Issues: • Effectiveness • In emergencies, effectiveness outweighs efficiency • Ideally, no cost on human life or suffering • Efficiency • Energy conservation • Efficient querying • Security and privacy • … 23

24. Deploy seed oppnet Need to grow? NO YES GROWTH Detect candidate helpers (system) Enough good candidates? Command Center NO YES Admit candidates into oppnet Integrate helper’s resources Collaborative processing Workdone? Clean up all helpers Release helpers NO YES 24

25. CleanUp and Release Helpers • Oppnet restores “original state” of helpers • As close as possible to their state just before they joined • Imperative to minimize intrusiveness of helper • Oppnet releases helpers from “duty” 25

26. Deploy seed oppnet Need to grow? NO YES GROWTH Detect candidate helpers (system) Enough good candidates? Command Center NO YES Admit candidates into oppnet Integrate helper’s resources Collaborative processing Workdone? Clean up all helpers Release helpers NO YES 26

27. Command Center (CC) • CC capable of interactive (human intervention)or autonomous actions • CC tasks include: • Determine/modify goals • Activate actuators/sensors • Manage oppnet • Decide when/how to grow • Optimize resources • ... • Facilitate human input for interactive heuristics • Determine critical mass of seed oppnet & expanded oppnet • Optimize oppnet configuration • ... • CC assures realization of oppnet goals 27

28. RelatedResearch • Oppnets viewed as a superset of MANET (MANET = Mobile Ad hoc NETwork) => Challenges inherent to MANET carried over to oppnets • Localization, data integration & aggregation • Growth in P2Psystems • Searching for peers in unstructured systems • Grid Systems • Integrating and managing heterogeneous systems • Trojan Horses • Mimic their spread capabilities in search for helpers • Others • CenWits 28

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30. Section 3: Research Challengesfor Security and Privacy in Oppnets (1) • Prevent malicious helpers from joining • Common attacks • MITM • Packet dropping • DoS attack on weak devices • ID spoofing • ... • Finding “good”cryptographic primitives 30

31. Research Challengesfor Security and Privacy in Oppnets (2) • Increasing trust • Routing through more trusted systems • Shared secrets for each communicating pair • Using shared secrets with broadcast authentication • Using digital signatures • Assuring privacy • Privacy of communications and data storage • Communication patterns • Broadcast/multicast from the base station • Messages among nodes & from nodes to the base station 31

32. Research Challengesfor Security and Privacy in Oppnets (3) • Intrusion detection • Why? • When prevention fails • Lack of initial authentication mechanism • Issues in intrusion detection • Securely distributing information about malicious entities • Heterogeneous – real-time intrusion detection and response 32

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34. Section 4a:Conclusions • High-payoff potential for the oppnet Initiative • Reduction of human suffering & loss of life • Economic benefits • Technological, educational & research benefits 34

35. Impact of Oppnets on the Society • Impact onEmergency Preparadness and Response operationsin Homeland Security (HS) — current app focus • Tremendous leveraging potential in emergencies • A wealth of freely availableresources • Reduction of human suffering & loss of life • Increasing safety & efficiency of the first responders • Impact on other applications in HS and outside HS • Economic impact • Technology transfer &commercialization • Benefits for the computer industry • Production of software / networking equipment • Benefits for other industries • Enhancing many products with standard oppnet interfaces • E.g.: cars with oppnet-capable nodes — auto industry benefits 35

36. Impact of Oppnets on Technology • Advancing the network know-how • By development of the oppnet technology • Enhancing distributed applications served by „regular” networks • Enabling new application niches we can not even foresee • Advancing other critical areas of computer technology • Including wireless systems, sensornets, ad hoc systems & pervasive computing • Aside effect of oppnet developments • Technology impacts speeded up & enhanced by the planned technology transferpluscommercialization activities 36

37. Impact of Oppnets onEducation & Research • Impact on students • For project participants: hands-on B.S./M.S./Ph.Dtraining • For others: course enhancements / course projects / seminars • Oppnet prototype used for lab experiments • Dissemination of research results • Publications, presentations, seminars, poster sessions, web site • Public availability of the oppnet prototype, tools & data • Outreach activities • Including K-12 demos for underrepresented minorities • All activities will broadenthe America’s talent pool in critical technologies and applications • Training more minority & female students at all levels 37

38. Section 4b:Future Work • Building a prototype • To demonstrate technical prowess & economic benefits • Technology transfer&commercialization • Discussed above 38

39. Future Work:EPR Oppnet Initiative — Milestones • Building state-of-the-art lab facilities • Constructing an oppnetprototype in the lab • Developing performance analysis tools to support testing & fine-tuning activities • Extendingthe prototype toinclude living-laboratoryresources available in our sensor- & computer-rich building • Testingthe prototype within the living laboratory • For fine-tuning design & implementation • Obtainingexternal assessment of the prototype • From computer & homeland security labs in MI, IN, IL 39

40. WiSe Lab Publications onSensornets, Oppnets & Pervasive Computing • L. Lilien and A. Gupta, ” Opportunistic Networks for Emergency Preparadness and Response” (submitted for publication). • V. Bhuse, A. Gupta, and L. Lilien, "Research challenges in lightweight intrusion detection for sensornets" (submitted for publication). • L. Lilien and B. Bhargava, ”A Scheme for Privacy-preserving Data Dissemination,” IEEE Transactions on Systems, Man and Cybernetics (to appear). • L. Lilien, Z. Kamal, V. Bhuse and A. Gupta, "Opportunistic Networks: The Concept and Research Challenges,” International Workshop on Research Challenges in Security and Privacy for Mobile and Wireless Networks (WSPWN 2006), Miami, Florida, March 2006 (to appear). • T. Canli, M. Terwilliger, A. Gupta and A. Khokhar, "Power Efficient Algorithms for Computing Fast Fourier Transform over Wireless Sensor Networks," The Fourth ACS/IEEE Conference on Computer Systems and Applications, Dubai, UAE, March 2006. • V. Bhuse, A. Gupta and L. Lilien, "DPDSN: Detection of packet-dropping attacks for wireless sensor networks," Proceedings of the 4th   International Trusted Internet Workshop (TIW), International Conference on High Performance Computing, Goa, India, December 2005. • A. Gupta and V. Bhuse, "Anamoly Intrusion Detection in Wireless Sensor Networks," Journal of High Speed Networks,  vol. 15, issue 1, January-March 2006. • M. Terwilliger, A. Gupta, A. Khokhar and G. Greenwood,"Localization using Evolution Strategies in Sensornets," Proceedings of the IEEE Congress on Evolutionary Computation, Edinburgh, UK, September 2005. • V. Bhuse, A. Gupta, M. Terwilliger, Z. Yang and Z. Kamal, "Using Routing Data for Information Authentication in Sensor Networks," Proceedings of the 3rd   International Trusted Internet Workshop (TIW), International Conference on High Performance Computing, Bangalore, India, December 2004. • T. Canli, M. Terwilliger, A. Gupta and A. Khokhar, "Power-Time Efficient Algorithm for Computing FFT in Sensor Networks," (Extended Abstract). Proceedings of the Second ACM Conference on Embedded Networked Sensor Systems (SenSys), Baltimore, Maryland, November 2004. • B. Bhargava, L. Lilien, A. Rosenthal, and M. Winslett, “PervasiveTrust,” IEEE Intelligent Systems, vol. 19(5), Sep./Oct.2004, pp. 74-77. • B. Bhargava and L. Lilien, “Private and Trusted Collaborations,” Proc. Secure Knowledge Management (SKM 2004): A Workshop, Amherst, NY, Sep. 2004. • M. Jenamani, L. Lilien, and B. Bhargava, “Anonymizing Web Services Through a Club Mechanism with Economic Incentives,” Proc. International Conference on Web Services (ICWS 2004), San Diego, California, July 2004, pp. 792-795. • Z. Kamal, M. Salahuddin, A. Gupta, M. Terwilliger, V. Bhuse and B. Beckmann, "Analytical Analysis of Data and Decision Fusion in Sensor Networks," The 2004 International Conference on Embedded Systems and Applications. Las Vegas, June 2004. • M. Terwilliger, A. Gupta, V. Bhuse, Z. Kamal, and M. Salahuddin, "A Localization System Using Wireless Sensor Networks: A Comparison of Two Techniques," Proceedings of the 2004 Workshop on Positioning, Navigation and Communication, Hanover, Germany, March 2004 , pp. 95-100. • V. Bhuse, A. Gupta and R. Pidva, "A Distributed Approach to Security in Sensornets," The 58th IEEE Semiannual Vehicular Technology Conference, Orlando, Florida, USA, October 2003. • L. Lilien, “Developing Pervasive Trust Paradigm for Authentication and Authorization,” Proc. Third Cracow Grid Workshop (CGW’03), Kraków (Cracow), Poland, October 2003, pp. 42-49 (invited paper). 40

41. WiSe Lab Experience in Sensornets – Selected Projects Since 1/03 • Designing of WiSe Security Protocols: DSPS • Location Tracker Using Motes (*) • RHS: Remote Home Surveillance (*) • Directed Diffusion: Attacks & Countermeasures • Improving the Accuracy of Mote Measurements by UsingNeural Networks • SOMS: Smart Occupancy Monitoring System Using Motes (*) • Comparative Study of Network Simulators • Collaborative Image Processing (*) • DENSe: a Development Environment for Networked Sensors • Incorporating Mobile-ware in Distributed Computations / Grids (*) • Extendingthe ns-2 Simulator to Satellite and WCN Simulations • Smart Antennas for WCNs • Energy Efficient MAC Protocols for IEEE 802.11x • A Wireless Security Testing System (*) • Mobile and Self-Calibrating Irrigation System • Collective Communications for Sensornets (*) * Results directly useful for oppnets 41

42. Sensor Node • Node Structure Event detection Wireless communication Sen- sors Radio CPU Neighboring Nodes Battery • Node implementation (MICA-2) 42

43. Thank you very much for your time and attention! 43

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46. Sensor Node • Node Structure Event detection Wireless communication Sen- sors Radio CPU Neighboring Nodes Battery • Node implementation (MICA-2) 46

47. Startup: Seed Oppnet • Oppnet starts as a seedoppnet Link to the World Wireless Nodes Base Station • Seed oppnet grows into an expandedoppnet 47

48. Link to the World Wireless Nodes Base Station Growth: Expanded Oppnet Satellite Appliance (refrigerator) Cellphone Tower Microwave Relay Computer Network Overturned Vehicle with OnStar • Heterogenous helpers join oppnet • Add communication, computing, sensing, other resources 48

49. 49 49 Fig - Expanded Oppnet (size : 50%) Best version above; worse, older version below: 49

50. >>FIX OR SKIP:<<Integrate Helper Resources • Select goals to be facilittated by helpers • Determine tasks to be offloaded to helpers • Coordinate all tasks • ADD SOME MORE POINTS • ANOTHER POINT • ONE MORE POINT • … 50