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Wireless Sensor Route Obfuscation

Wireless Sensor Route Obfuscation. Mark W. Propst Scientific Research Corporation. Outline. Attack Motivations Vulnerability Classification Traffic Pattern Analysis Testing Barriers Concluding Remarks. Wireless Sensor Network Utilization.

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Wireless Sensor Route Obfuscation

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  1. Wireless Sensor Route Obfuscation Mark W. Propst Scientific Research Corporation

  2. Outline • Attack Motivations • Vulnerability Classification • Traffic Pattern Analysis • Testing Barriers • Concluding Remarks

  3. Wireless Sensor Network Utilization • Wireless Sensor Network link-layer protocols are derived from mobile ad hoc networks which leaves them vulnerable to the same type of attacks • They are typically deployed in un-secured hostile environments leaving them vulnerable to physical attack • The sensor nodes lack the processing power and battery life to perform countermeasures typically utilized in many fixed and mobile ad hoc networks

  4. Three Vulnerability Classifications1 • Unauthorized data observation • Unauthorized data manipulation • Data unavailability 1) Bertino, E., & Sandhu, R. (2005). Database Security-Concepts, Approaches, and Challenges. IEEE Trans. Dependable Secur. Comput., Vol 2, issue 1, pp. 2–19.

  5. Unauthorized Data Observation/Manipulation There is currently a plethora of research attempting to understand and counter the manipulation of individual nodes within a wireless sensor network • Threshold Cryptography and Authentication2 is an example of unique methods to protect and detect • Similarly, Adaptive Intrusion Detection3 detects malicious nodes in a sensor network 2) Piya, T., & Andrew, J. (2007). Adaptive Intrusion Detection in Wireless Sensor Networks. Intelligent Pervasive Computing, International Conference on, 0, 23-28. 3) Marianne, A. A., Sherif, M. E.-K., & Magdy, S. E.-S. (2007). Threshold Cryptography and Authentication in Ad Hoc Networks Survey and Challenges. Systems and Networks Communication, International Conference on, 0, 5.

  6. Data UnavailabilityCluster Head Attack Motivations • Cluster heads typically have greater processing power, provide geo-location, encryption keys, and act as a gateway of information from the sensor network to the outside world • Attacking and defeating a cluster head will render the entire sensor cluster non-operational • Unlike mobile networks, sensor networks are typically static, leading to predictable routing paths • With predictable routing paths, the cluster head of a sensor network can be detected

  7. Cluster Head Attack Methodology • There are two methods to attack the same static path vulnerability: • Route Correlation (Rate Monitoring) • Frequency Domain Analysis (Time Correlation) • Both rely on the correlation of time between transmission events on successive nodes to determine the path to the cluster head

  8. Obfuscation Techniques • Link-layer encryption, such as onion encryption, can effectively prevent packet sniffing. • To defeat frequency domain analysis, most obfuscation techniques attempt to bring the noise floor up to the transmission level by generating excess packets

  9. Transmission Time Correlation SHF Power SHF Power ΔT ΔT Easily identifiable transmission sequence Theoretical obfuscation

  10. Obfuscation Methodology Most current methodologies attempt to obfuscate routing signatures by introducing superfluous traffic. • Flooding • Generic Random Walk • Greedy Random Walk • Directed Random Walks • Store and Forward

  11. Obfuscation Short Comings • Onion Routing requires every node to encrypt the packet, consuming valuable battery power encrypting every packet for every hop • Bringing up the noise floor through the utilization of random walk strategies effectively obfuscates the traffic, but at the cost of sensor network life Mark W. Propst DCIS 730

  12. Testing How do we test network routing obfuscation? • This is typically done in simulation by applying a propositional satisfiability solver such as GSAT4 • Propositional satisfiability solvers are very efficient at comparing obfuscation methodologies, however, the results between different implementers are NOT comparable • There is currently no repeatability in testing 4) Selman, B., Levesque, H., & Mitchell, D. (1992). A new method for solving hard satisfiability problems. In National conference on artificial intelligence (pp. 440-446).

  13. Conclusion • Development of new energy efficient routing protocols with high obfuscation properties which mask the RF signature of the routing topology must happen to stay ahead of current and developing threats • The development of standardized test tools to compare and contrast new obfuscation protocols is just as important as developing the obfuscation protocols

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