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

Processpatching: defining new methods in aRt&D

In the context of a rapidly changing domain of contemporary electronic art practice- where the speed of technological innovation and the topicality of art 'process as research' methods are both under constant revision- the process of collaboration between art, computer science and engineering is an important addition to existing 'R&D'. Scholarly as well as practical exploration of artistic methods, viewed in relation to the field of new technology, can be seen to enable and foster innovation in both the conceptualisation and practice of the electronic arts. At the same time, citing new media art in the context of technological innovation brings a mix of scientific and engineering issues to the fore and thereby demands an extended functionality that may lead to R&D, as technology attempts to take account of aesthetic and social considerations in its re-development. This new field of new media or electronic art R&D is different from research and development aimed at practical applications of new technologies as we see them in everyday life. A next step for Research and Development in Art (aRt&D) is a formalisation of the associated work methods, as an essential ingredient for interdisciplinary collaboration. This study investigates how electronic art patches together processes and methods from the arts, engineering and computer science environments. It provides a framework describing the electronic art methods to improve collaboration by informing others about one's artistic research and development approach. This investigation is positioned in the electronic art laboratory where new alliances with other disciplines are established. It provides information about the practical and theoretical aspects of the research and development processes of artists. The investigation addresses fundamental questions about the 'research and development methods' (discussed and defined at length in these pages), of artists who are involved in interdisciplinary collaborations amongst and between the fields of Art, Computer Science, and Engineering. The breadth of the fields studied necessarily forced a tight focus on specific issues in the literature, addressed herein through a series of focused case studies which demonstrate the points of synergy and divergence between the fields of artistic research and development, in a wider art&D' context. The artistic methods proposed in this research include references from a broad set of fields (e. g. Technology, Media Arts, Theatre and Performance, Systems Theories, the Humanities, and Design Practice) relevant to and intrinsically intertwined with this project and its placement in an interdisciplinary knowledge domain. The aRt&D Matrix provides a complete overview of the observed research and development methods in electronic arts, including references to related disciplines and methods from other fields. The new Matrix developed and offered in this thesis also provides an instrument for analysing the interdisciplinary collaboration process that exclusively reflects the information we need for the overview of the team constellation. The tool is used to inform the collaborators about the backgrounds of the other participants and thus about the expected methods and approaches. It provides a map of the bodies of knowledge and expertise represented in any given cross-disciplinary team, and thus aims to lay the groundwork for a future aRt&D framework of use to future scholars and practitioners alike

Non-Hierarchical Networks for Censorship-Resistant Personal Communication.

The Internet promises widespread access to the world’s collective information and fast communication among people, but common government censorship and spying undermines this potential. This censorship is facilitated by the Internet’s hierarchical structure. Most traffic flows through routers owned by a small number of ISPs, who can be secretly coerced into aiding such efforts. Traditional crypographic defenses are confusing to common users. This thesis advocates direct removal of the underlying heirarchical infrastructure instead, replacing it with non-hierarchical networks. These networks lack such chokepoints, instead requiring would-be censors to control a substantial fraction of the participating devices—an expensive proposition. We take four steps towards the development of practical non-hierarchical networks. (1) We first describe Whisper, a non-hierarchical mobile ad hoc network (MANET) architecture for personal communication among friends and family that resists censorship and surveillance. At its core are two novel techniques, an efficient routing scheme based on the predictability of human locations anda variant of onion-routing suitable for decentralized MANETs. (2) We describe the design and implementation of Shout, a MANET architecture for censorship-resistant, Twitter-like public microblogging. (3) We describe the Mason test, amethod used to detect Sybil attacks in ad hoc networks in which trusted authorities are not available. (4) We characterize and model the aggregate behavior of Twitter users to enable simulation-based study of systems like Shout. We use our characterization of the retweet graph to analyze a novel spammer detection technique for Shout.PhDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/107314/1/drbild_1.pd

On traffic analysis in anonymous communication networks

In this dissertation, we address issues related to traffic analysis attacks and the engineering in anonymous communication networks. Mixes have been used in many anonymous communication systems and are supposed to provide countermeasures that can defeat various traffic analysis attacks. In this dissertation, we first focus on a particular class of traffic analysis attack, flow correlation attacks, by which an adversary attempts to analyze the network traffic and correlate the traffic of a flow over an input link at a mix with that over an output link of the same mix. Two classes of correlation methods are considered, namely time-domain methods and frequency-domain methods. We find that a mix with any known batching strategy may fail against flow correlation attacks in the sense that, for a given flow over an input link, the adversary can correctly determine which output link is used by the same flow. We theoretically analyze the effectiveness of a mix network under flow correlation attacks. We extend flow correlation attack to perform flow separation: The flow separation attack separates flow aggregates into either smaller aggregates or individual flows. We apply blind source separation techniques from statistical signal processing to separate the traffic in a mix network. Our experiments show that this attack is effective and scalable. By combining flow separation and frequency spectrum matching method, a passive attacker can get the traffic map of the mix network. We use a non-trivial network to show that the combined attack works. The second part of the dissertation focuses on engineering anonymous communication networks. Measures for anonymity in systems must be on one hand simple and concise, and on the other hand reflect the realities of real systems. We propose a new measure for the anonymity degree, which takes into account possible heterogeneity. We model the effectiveness of single mixes or of mix networks in terms of information leakage and measure it in terms of covert channel capacity. The relationship between the anonymity degree and information leakage is described, and an example is shown

Artificial general intelligence: Proceedings of the Second Conference on Artificial General Intelligence, AGI 2009, Arlington, Virginia, USA, March 6-9, 2009

Artificial General Intelligence (AGI) research focuses on the original and ultimate goal of AI – to create broad human-like and transhuman intelligence, by exploring all available paths, including theoretical and experimental computer science, cognitive science, neuroscience, and innovative interdisciplinary methodologies. Due to the difficulty of this task, for the last few decades the majority of AI researchers have focused on what has been called narrow AI – the production of AI systems displaying intelligence regarding specific, highly constrained tasks. In recent years, however, more and more researchers have recognized the necessity – and feasibility – of returning to the original goals of the field. Increasingly, there is a call for a transition back to confronting the more difficult issues of human level intelligence and more broadly artificial general intelligence