Jamming and sensing of encrypted wireless ad hoc networks
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Preventing active timing attacks in low-latency anonymous communication
PETS'10 Proceedings of the 10th international conference on Privacy enhancing technologies
Location privacy and resilience in wireless sensor networks querying
Computer Communications
Effective digital forensics research is investigator-centric
HotSec'11 Proceedings of the 6th USENIX conference on Hot topics in security
Privacy vulnerabilities in encrypted HTTP streams
PET'05 Proceedings of the 5th international conference on Privacy Enhancing Technologies
Beyond TOR: the truenyms protocol
SIIS'11 Proceedings of the 2011 international conference on Security and Intelligent Information Systems
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To explore mission-critical information, an adversary using active traffic analysis attacks injects probing traffic into the victim network and analyzes the status of underlying payload traffic. Active traffic analysis attacks are easy to deploy and hence become a serious threat to mission critical applications. This paper suggests statistical pattern recognition as a fundamental technology to evaluate effectiveness of active traffic analysis attacks and corresponding countermeasures. Our evaluation shows that sample entropy of ping packets' round trip time is an effective feature statistic to discover the payload traffic rate. We proposesimple countermeasures that can significantly reduce the effectiveness of ping-based active traffic analysis attacks. Our experiments validate the effectiveness of this scheme, whichcan also be used in other scenarios.