A fast fixed-point algorithm for independent component analysis
Neural Computation
An analysis of security incidents on the Internet 1989-1995
An analysis of security incidents on the Internet 1989-1995
Crowds: anonymity for Web transactions
ACM Transactions on Information and System Security (TISSEC)
Communications of the ACM
A non-instrusive, wavelet-based approach to detecting network performance problems
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
Estimating Overcomplete Independent Component Bases for Image Windows
Journal of Mathematical Imaging and Vision
Introducing MorphMix: peer-to-peer based anonymous Internet usage with collusion detection
Proceedings of the 2002 ACM workshop on Privacy in the Electronic Society
From a Trickle to a Flood: Active Attacks on Several Mix Types
IH '02 Revised Papers from the 5th International Workshop on Information Hiding
ANODR: anonymous on demand routing with untraceable routes for mobile ad-hoc networks
Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing
SNDSS '96 Proceedings of the 1996 Symposium on Network and Distributed System Security (SNDSS '96)
P5: A Protocol for Scalable Anonymous Communication
SP '02 Proceedings of the 2002 IEEE Symposium on Security and Privacy
Mixminion: Design of a Type III Anonymous Remailer Protocol
SP '03 Proceedings of the 2003 IEEE Symposium on Security and Privacy
Proceedings of the 1st ACM international workshop on Wireless mobile applications and services on WLAN hotspots
Gathering correlated data in sensor networks
Proceedings of the 2004 joint workshop on Foundations of mobile computing
VOR base stations for indoor 802.11 positioning
Proceedings of the 10th annual international conference on Mobile computing and networking
Anonymous Secure Routing in Mobile Ad-Hoc Networks
LCN '04 Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks
Tor: the second-generation onion router
SSYM'04 Proceedings of the 13th conference on USENIX Security Symposium - Volume 13
Compromising Location Privacy inWireless Networks Using Sensors with Limited Information
ICDCS '07 Proceedings of the 27th International Conference on Distributed Computing Systems
Towards an information theoretic metric for anonymity
PET'02 Proceedings of the 2nd international conference on Privacy enhancing technologies
PET'02 Proceedings of the 2nd international conference on Privacy enhancing technologies
Dummy traffic against long term intersection attacks
PET'02 Proceedings of the 2nd international conference on Privacy enhancing technologies
A new set of passive routing attacks in mobile ad hoc networks
MILCOM'03 Proceedings of the 2003 IEEE conference on Military communications - Volume II
Statistical disclosure or intersection attacks on anonymity systems
IH'04 Proceedings of the 6th international conference on Information Hiding
The traffic analysis of continuous-time mixes
PET'04 Proceedings of the 4th international conference on Privacy Enhancing Technologies
A blind source separation technique using second-order statistics
IEEE Transactions on Signal Processing
Blind source separation using clustering-based multivariate densityestimation algorithm
IEEE Transactions on Signal Processing
Traffic analysis attacks on Skype VoIP calls
Computer Communications
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We propose a class of anonymity attacks to both wired and wireless anonymity networks. These attacks are based on the blind source separation algorithms widely used to recover individual signals from mixtures of signals in statistical signal processing. Since the philosophy behind the design of current anonymity networks is to mix traffic or to hide in crowds, the proposed anonymity attacks are very effective. The flow separation attack proposed for wired anonymity networks can separate the traffic in a mix network. Our experiments show that this attack is effective and scalable. By combining the flow separation method with frequency spectrum matching, a passive attacker can derive the traffic map of the mix network. We use a nontrivial network to show that the combined attack works. The proposed anonymity attacks for wireless networks can identify nodes in fully anonymized wireless networks using collections of very simple sensors. Based on a time series of counts of anonymous packets provided by the sensors, we estimate the number of nodes with the use of principal component analysis. We then proceed to separate the collected packet data into traffic flows that, with help of the spatial diversity in the available sensors, can be used to estimate the location of the wireless nodes. Our simulation experiments indicate that the estimators show high accuracy and high confidence for anonymized TCP traffic. Additional experiments indicate that the estimators perform very well in anonymous wireless networks that use traffic padding.