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  • 1. RFID Steven DiBenedetto
  • 2. Outline • Introduction and Principles • Evolution of Security • Tag Counting • Context/Location Awareness • Secure Storage
  • 3. Introduction • Radio Frequency Identification (RFID) • Generally consists of a reader and tags. – Readers issue queries to tags which then respond. • RFID is among the most loved and reviled technologies of our time. – Poster child for ubiquitous computing. – Enemy #1 for privacy groups. • Lots of interesting problems concerning context awareness and privacy.
  • 4. RFID Equipment http://www.rfidc.com/docs/introductiontorfid_technology.htm
  • 5. RFID Principles • Active: require powered infrastructure or attached battery – Examples: aircraft IFF transponder – Pros: can generate own signal, wider range of uses – Cons: more expensive, limited battery life • Passive: powered by a tag reader – Example: labels – Pros: no battery or maintenance needed, cheap – Cons: few uses, still too expensive for some uses
  • 6. RFID Principles • 2 main methods to power passive devices – Near-field RFID • Works off of magnetic induction fields • Tag responds through load modulation • Limited effective range. – Far-field RFID • Tags capture EM waves emitted by a dipole antenna. • Response loses power more quickly than near-field.
  • 7. RFID Principles • Operates in 3 main frequency bands – Low (125/134 KHz) • Useful for access control – High (13.56 MHz) • Provides read ranges up to 1.5 meters – Ultra High (850 – 950 MHz) • High speed reading and range up to 3 meters. • Favored for inventory tracking.
  • 8. Example Applications • Originally developed for aircraft IFF systems. • More efficient check-out systems. • Automatic toll collection devices. • Access control.
  • 9. Outline • Introduction and Principles • Evolution of Security • Tag Counting • Context/Location Awareness • Secure Storage
  • 10. Past Security Issues • Sniffing and Tracking • Spoofing – Make adversary think you are someplace else. • Replay – Steal IFF transponder to answer identification challenges. • Denial of Service – Jamming radars result in hesitation or friendly fire.
  • 11. Modern Security Issues • Sniffing – Easy to eavesdrop or query tags with a compliant reader. • Tracking – Well placed readers can track you and “constellations” of who/what you associate with. • Spoofing – Tag cloning. See Oyster Cards. • Replay • Denial of Service – Tag relocation – Faraday cages
  • 12. Security Evolution • No longer a clear concept of who is an attacker. – Past: Allies vs. Axis – Present: Potentially everyone. • Physical security went out the window. – Past: IFF transponder was on a plane. – Present: Device may already be in adversary’s possession. • Security vs. Privacy – Past: Exclusively security. – Present: Security and privacy are now critical.
  • 13. Security Evolution • Back-end infrastructure – Past: Compromise affects a single plane. – Present: Potentially connected to important databases and other middleware. • Social factors – Past: Attacks are always attacks. – Present: Attacks may also be an attempt at self- defense.
  • 14. Evolution of Solutions • Cryptography – Past • Issue random challenge. • Friendly responds with encrypted challenge. • Interrogator validates response. – Present • Symmetric & asymmetric key cryptography. • May offload solution of a back-end device.
  • 15. Evolution of Solutions • Detection and evasion – Past: Radar predication devices showed radar locations on relief maps. – Present: RFID Guardian detects scans and logs their meaning. • Temporary deactivation – Past: Turn off IFF device. – Present: Password protected sleep or Faraday cages.
  • 16. Evolution of Solutions • Other techniques – Past • Hop between random frequencies to evade attacks. • Require a code to be periodically entered into transponder. – Present • Periodically regenerate tag name or ID. • Re-encrypt tag data.
  • 17. Security Feasibility • Application considerations – Past • Cost not an issue thanks to war time budget. • Size not an issue thanks to deployment on bombers. – Present: • Wide scale deployment requires low cost. • Size is an issue for ubiquitous deployment.
  • 18. Security Feasibility • On-tag cryptography – Past: Crypto makes sense in a war. – Present • Crypto may cause power/size constraints. • Move crypto off-tag. • Key revocation – Past: Revoke IFF key if a plane is stolen. – Present: Determining when a key has been compromised is difficult.
  • 19. Outline • Introduction and Principles • Evolution of Security • Tag Counting • Context/Location Awareness • Secure Storage
  • 20. Tag Counting • Objective: Quickly and accurately count the number of tags with a region. – Inventory items as they are unloaded. • Multiple tags responding can cause collisions. • Passive tags have little functionality. – Unable to detect collisions and neighbors. • Tags may be read multiple times.
  • 21. Tag Count Frame Slotted Aloha • Tag transmissions are scheduled by communication between tag and reader. • Tags should implement: – identified flag – Random number generator – Slot counter – Simple state machine
  • 22. Tag Count Frame Slotted Aloha Tag Count Frame Slotted Aloha: A Novel Anti-collision Protocol in RFID Systems. Xiaodong Deng, Mengtian Rong, Tao Liu, Yong Yuan and Dan Yu
  • 23. TCFSA Performance • Evaluate based on: • Number of arrivals = number of departures for simulations.
  • 24. TCFSA vs. Other Aloha-based Tag Count Frame Slotted Aloha: A Novel Anti-collision Protocol in RFID Systems. Xiaodong Deng, Mengtian Rong, Tao Liu, Yong Yuan and Dan Yu
  • 25. TCFSA vs. ABS Tag Count Frame Slotted Aloha: A Novel Anti-collision Protocol in RFID Systems. Xiaodong Deng, Mengtian Rong, Tao Liu, Yong Yuan and Dan Yu
  • 26. Outline • Introduction and Principles • Evolution of Security • Tag Counting • Context/Location Awareness • Secure Storage
  • 27. Context Awareness • Goal: Determine user’s location and what actions are being taken. • Relative vs. Absolute location measurements – Measuring based on last known location • E.g. measure distance walked based on pace and time – Measurement based on reference E.g. GPS system
  • 28. Context Awareness Challenges • Environment may be constantly changing. • Heterogeneous data sources with varying levels of reliability. • May desire different levels of privacy based on location. – Location is more than a set of coordinates. – Expected behavior at location? • Privacy varies based on who is looking for information.
  • 29. Location Sensing • Objective: Track people or objects within a given area. • Variety of commonly used solutions. – GPS – Infrared sensors – Ultrasonic sensors – RFID – 802.11
  • 30. RFID-based Location Placement of 9 readers with two different ranges and the sub- regions. LANDMARC: Indoor Location Sensing Using Active RFID. LIONEL M. NI, YUNHAO LIU, YIU CHO LAU and ABHISHEK P. PATIL. Wireless Networks 10, 701–710, 2004
  • 31. LANDMARC • Objective: Create a location sensing system using off the shelf hardware. • Equipment: – RFID readers • 8 power levels • Event-based or continuous update scheme • Detection range of 150 ft • 802.11b interface – Active RFID tags
  • 32. LANDMARC Approach • Adding more readers increases accuracy. – Expensive – Static obstructions and human movement can effect readings. • Add static tags to act as landmarks. – Reference tags will behave similar to target tags. – Requires active tags.
  • 33. LANDMARC Approach • Maintain signal strength vectors. – Moving tag: S = (S1 , S2 , . . . , Sn ) – Reference tag: θ = (θ1 , θ2 , . . . , θ) • Measure using Euclidean distance of strengths
  • 34. LANDMARC Approach • K-nearest neighbors algorithm for coordinates • w represents the weight of a reference tag. – Uniform weights results in more errors. – Calibrate weights based on E
  • 35. LANDMARC Evaluation • Reference tags limit some interference effects. • More readers improves accuracy, but very expensive. LANDMARC: Indoor Location Sensing Using Active RFID. LIONEL M. NI, YUNHAO LIU, YIU CHO LAU and ABHISHEK P. PATIL. Wireless Networks 10, 701–710, 2004
  • 36. LANDMARC Evaluation LANDMARC: Indoor Location Sensing Using Active RFID. LIONEL M. NI, YUNHAO LIU, YIU CHO LAU and ABHISHEK P. PATIL. Wireless Networks 10, 701–710, 2004
  • 37. Outline • Introduction and Principles • Evolution of Security • Tag Counting • Context/Location Awareness • Secure Storage
  • 38. Location-based Storage • Use the properties of a physical location as implicit access control. – May be enough security for a given piece of data. – Analogous to how people use to manage privacy. • Requirements: – Fluid boundaries – Time variance – Time continuity – Secure storage
  • 39. FragDB Approach • Fluid boundaries – Use tag IDs are pointers to memory holding a fragment of data. – Data is fragmented based level of redundancy. • Simple split (no redundancy) • Redundant split • FEC 2:1 – Allows reassembly with any set of half the fragments.
  • 40. FragDB Approach • Time variance – Tag should change its ID periodically. • Timer component on tag • Change ID upon query with probability • Time continuity – Old IDs must be stored on tag. – Gradually expire old IDs.
  • 41. FragDB Approach • Secure storage – Data is not stored at location. – Only need knowledge about location key. FragDB – Secure Localized Storaged Based on Super-Distributed RFID-Tag Infrastructures. Marc Langheinrich
  • 42. Summary • RFID does not provide a one size fits all solution for computing needs. • Lots of security and privacy concerns remain to be answered. • RFID will continue to be a solid foundation for ubiquitous computing applications.
  • 43. References • RFID Centre. http://www.rfidc.com • An Introduction to RFID Technology. Roy Want. • Activity and Location Recognition Using Wearable Sensors. Seon- Woo Lee and Kenji Mase. • Managing Context Information in Mobile Devices. Panu Korpipää, Jani Mäntyjärvi, Juha Kela, Heikki Keränen, and Esko-Juhani Malm • Tag Count Frame Slotted Aloha: A Novel Anti-collision Protocol in RFID Systems. Xiaodong Deng, Mengtian Rong, Tao Liu, Yong Yuan and Dan Yu. • FragDB – Secure Localized Storaged Based on Super-Distributed RFID-Tag Infrastructures. Marc Langheinrich • LANDMARC: Indoor Location Sensing Using Active RFID. LIONEL M. NI, YUNHAO LIU, YIU CHO LAU and ABHISHEK P. PATIL. Wireless Networks 10, 701–710, 2004