Compromising Anonymous Communication Systems Using Blind Source Separation

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

Compromising Anonymous Communication Systems Using Blind Source Separation

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

Power Side Channels in Security ICs: Hardware Countermeasures

Power side-channel attacks are a very effective cryptanalysis technique that can infer secret keys of security ICs by monitoring the power consumption. Since the emergence of practical attacks in the late 90s, they have been a major threat to many cryptographic-equipped devices including smart cards, encrypted FPGA designs, and mobile phones. Designers and manufacturers of cryptographic devices have in response developed various countermeasures for protection. Attacking methods have also evolved to counteract resistant implementations. This paper reviews foundational power analysis attack techniques and examines a variety of hardware design mitigations. The aim is to highlight exposed vulnerabilities in hardware-based countermeasures for future more secure implementations

Household economic decisions under the shadow of terrorism : [This Version: January 4, 2009]

We investigate, using the 2002 US Health and Retirement Study, the factors influencing individuals’ insecurity and expectations about terrorism, and study the effects these last have on households’ portfolio choices and spending patterns. We find that females, the religiously devout, those equipped with a better memory, the less educated, and those living close to where the events of September 2001 took place worry a lot about their safety. In addition, fear of terrorism discourages households from investing in stocks, mostly through the high levels of insecurity felt by females. Insecurity due to terrorism also makes single men less likely to own a business. Finally, we find evidence of expenditure shifting away from recreational activities that can potentially leave one exposed to a terrorist attack and towards goods that might help one cope with the consequences of terrorism materially (increased use of car and spending on the house) or psychologically (spending on personal care products by females in couples)

Comparison of Empirical Data from Two Honeynets and a Distributed Honeypot Network

In this paper we present empirical results and speculative analysis based on observations collected over a two month period from studies with two high interaction honeynets, deployed in a corporate and an SME (small to medium enterprise) environment, and a distributed honeypots deployment. All three networks contain a mixture of Windows and Linux hosts. We detail the architecture of the deployment and results of comparing the observations from the three environments. We analyze in detail the times between attacks on different hosts, operating systems, networks or geographical location. Even though results from honeynet deployments are reported often in the literature, this paper provides novel results analyzing traffic from three different types of networks and some initial exploratory models. This research aims to contribute to endeavours in the wider security research community to build methods, grounded on strong empirical work, for assessment of the robustness of computer-based systems in hostile environments