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Low Cost and Secure Smart Meter Communications using the TV White Spaces PowerPoint Presentation
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Low Cost and Secure Smart Meter Communications using the TV White Spaces

Low Cost and Secure Smart Meter Communications using the TV White Spaces

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Low Cost and Secure Smart Meter Communications using the TV White Spaces

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  1. Low Cost and Secure Smart Meter Communications using the TV White Spaces OmidFatemieh (UIUC) RanveerChandra (Microsoft Research) Carl A. Gunter (UIUC)

  2. Advanced Meter Infrastructure (AMI) • AMI: integral part of smart grid • Reconfigurable nature and communication capabilities of advanced (smart) meters allow for deploying a rich set of applications • Automated meter reading • Outage management • Demand response • Electricity theft detection • Support for distributed power generation

  3. Existing AMI Communications • ISM bands • Crowded in urban areas • Short distances notsuitable for rural areas • Cellular links • Expensive and low bandwidth • Crowded in urban areas and limited in rural areas • Proprietary mesh network technology reduces inter-operability and impedes meter diversity • Idea: Use white spaces for AMI communications • Propose a secure architecture that yields benefits in cost, bandwidth, and deployment

  4. White Spaces • White spaces are unused portions of TV spectrum (54-698MHz) • Excellent long-range communication and penetration properties • FCC’s recent rulings (Nov ‘08, Sep ‘10) allows for unlicensed communication in white spaces • Spectrum sensing helps with identifying and assessing quality of unused channels • Standards and research prototypes • IEEE 802.22 Wireless Broadband Regional Area Network • Point to multipoint architecture • Typical range: 17 - 33 km (but up to 100 km) • WhiteFi[BahlCMMW09 - Sigcomm‘09] • Wi-Fi like connectivity over white spaces for up to 2km • Adaptively operates in most efficient chunk of available spectrum • Both require centrally aggregating spectrum sensing data

  5. Proposed Architecture • Utility operates WhiteFi networks • Utility buys service from independent 802.22 service provider • Large number and geographical spread of meters -> great for spectrum sensing -> utility can offer data to 802.22 provider

  6. Benefits • High data rates (at low cost) • Single hop from meters to WhiteFi base station • No need for complex meshes • Saves energy used in mesh maintenance and routing • Large base of sensors for the 802.22 provider • Lowers cost for 802.22 service provider • Lowers 802.22 service cost for utility • Lowers cost for providing broadband service to rural areas • Facilitates additional meters deployments in rural areas (particularly along power lines)

  7. Challenges and Security Considerations • Cost of equipping meters with CRs and antennas • Will be lowered with large-scale production • May be lowered for utility by contract with 802.22 provider • Limited availability of white-spaces • Unlikely in rural and suburban areas • Can use ISM or narrow licensed bands as backup • Primary emulation / unauthorized spectrum usage attacks • Transmitter localization [ChenPR – JSAC ‘08], Anomaly detection [LiuCTG09 - Infocom ‘09], Signal authentication [LiuND10 - Oakland ‘10] • Malicious false spectrum sensing report attacks • Vandalism: falsely declare a frequency as free • Exploitation: falsely declare a frequency as occupied

  8. Detecting False Reports • Particularly important for AMI • Errors will disrupt AMI communication • 802.22 provider cannot only rely on meters • Meters owned by a different entity (utility) • Meters may not be well-distributed, or get compromised • Must use additional sources for spectrum sensing: mobile units, consumer premise equipment, or deployed sensors • Sensors have unknown integrity and or get compromised • Detecting false reports • Based on propagation models[FatemiehCG– DySPAN ‘10] • Based on propagation data[FatemiehFCG– NDSS ‘11]

  9. Data-based (Classification-based) Detection • Model-based schemes: not clear which signal propagation models, parameters, or outlier thresholds should be used • Idea: Let dataspeak for itself • Provide natural and un-natural signal propagation patterns to train a machine learning SVM classifier • Subsequently use classifier to detect unnatural propagation patterns -> attacker-dominatedcells FatemiehFCG – NDSS 2011

  10. Evaluation Hilly Southwest Pennsylvania (Stress Test) Flat East-Central Illinois • Transmitter data from FCC • Terrain data from NASA • House density data from US Census Bureau FatemiehFCG – NDSS 2011

  11. Pennsylvania Stress Test Results • 20km by 20km area • Data from 37 transmitters in 150km radius • Train using data from 29 • Test on the data from 8 • Represent un-accounted fading and other signal variations: add Gaussian variations with mean 0 and std. dev up to 6 (dB-Spread) only to test data FatemiehFCG – NDSS 2011

  12. Summary • AMI communications a key part of smart grid • Proposed communication architecture that offers improvements in bandwidth, deployment, and cost • Discussed security and reliability challenges • Identified exploitation/vandalism as important attacks and proposed techniques to detect them • References • O. Fatemieh, R. Chandra, C. A. Gunter, Low Cost and Secure Smart Meter Communications using the TV White Spaces, ISRCS ’10. • O. Fatemieh, R. Chandra, C. A. Gunter, Secure Collaborative Sensing for Crowdsoucing Spectrum Data in White Space Networks, DySPAN ’10. • O. Fatemieh, A. Farhadi, R. Chandra, C. A. Gunter, Using Classification to Protect the Integrity of Spectrum Measurements in White Space Networks, NDSS ’11.

  13. Backup

  14. Standards and Research Prototypes for White-Space Communications • IEEE 802.22 standard draft • Wireless broadband regional area networks over TV white spaces • Point to multipoint architecture (base station to up to 255 clients), with the possibility of having repeaters in between • Each access point covers 17 - 33 km (typical) but up to 100 km • Antennas 10m above the ground, similar to TV antennas • Support for co-existence between cells • WhiteFi [BahlCMMW09 - Sicgomm ‘09] • Wi-Fi like connectivity over white spaces for up to 2km • Adaptively operates in most efficient contiguous chunk of available spectrum • Client to access point communication: using modified stock Wi-Fi cards • Requires a separate antenna and board for spectrum sensing • For spectrum allocation, both techniques support spectrum sensing and using transmitter databases