79 research outputs found

    Trust in Crowds: probabilistic behaviour in anonymity protocols

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    The existing analysis of the Crowds anonymity protocol assumes that a participating member is either ‘honest’ or ‘corrupted’. This paper generalises this analysis so that each member is assumed to maliciously disclose the identity of other nodes with a probability determined by her vulnerability to corruption. Within this model, the trust in a principal is defined to be the probability that she behaves honestly. We investigate the effect of such a probabilistic behaviour on the anonymity of the principals participating in the protocol, and formulate the necessary conditions to achieve ‘probable innocence’. Using these conditions, we propose a generalised Crowds-Trust protocol which uses trust information to achieves ‘probable innocence’ for principals exhibiting probabilistic behaviour

    Quantifying and measuring anonymity

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    The design of anonymous communication systems is a relatively new field, but the desire to quantify the security these systems offer has been an important topic of research since its beginning. In recent years, anonymous communication systems have evolved from obscure tools used by specialists to mass-market software used by millions of people. In many cases the users of these tools are depending on the anonymity offered to protect their liberty, or more. As such, it is of critical importance that not only can we quantify the anonymity these tools offer, but that the metrics used represent realistic expectations, can be communicated clearly, and the implementations actually offer the anonymity they promise. This paper will discuss how metrics, and the techniques used to measure them, have been developed for anonymous communication tools including low-latency networks and high-latency email systems. © 2014 Springer-Verlag Berlin Heidelberg

    Protecting and Evaluating Genomic Privacy in Medical Tests and Personalized Medicine

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    In this paper, we propose privacy-enhancing technologies for medical tests and personalized medicine methods that use patients' genomic data. Focusing on genetic disease-susceptibility tests, we develop a new architecture (between the patient and the medical unit) and propose a "privacy-preserving disease susceptibility test" (PDS) by using homomorphic encryption and proxy re-encryption. Assuming the whole genome sequencing to be done by a certified institution, we propose to store patients' genomic data encrypted by their public keys at a "storage and processing unit" (SPU). Our proposed solution lets the medical unit retrieve the encrypted genomic data from the SPU and process it for medical tests and personalized medicine methods, while preserving the privacy of patients' genomic data. We also quantify the genomic privacy of a patient (from the medical unit's point of view) and show how a patient's genomic privacy decreases with the genetic tests he undergoes due to (i) the nature of the genetic test, and (ii) the characteristics of the genomic data. Furthermore, we show how basic policies and obfuscation methods help to keep the genomic privacy of a patient at a high level. We also implement and show, via a complexity analysis, the practicality of PDS

    On the issue of training specialists to the project activity in a modern university

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    В статье рассматривается подготовка к проектной деятельности и включение информационной составляющей в эту подготовку для увеличения эффективности проектной деятельности будущих специалистов.The author of the article deals with the preparation for the project activities and the inclusion of an information component in the preparation of the project to increase the efficiency of future professionals

    Data sharing in DHT based P2P systems

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    International audienceThe evolution of peer-to-peer (P2P) systems triggered the building of large scale distributed applications. The main application domain is data sharing across a very large number of highly autonomous participants. Building such data sharing systems is particularly challenging because of the "extreme" characteristics of P2P infrastructures: massive distribution, high churn rate, no global control, potentially untrusted participants... This article focuses on declarative querying support, query optimization and data privacy on a major class of P2P systems, that based on Distributed Hash Table (P2P DHT). The usual approaches and the algorithms used by classic distributed systems and databases forproviding data privacy and querying services are not well suited to P2P DHT systems. A considerable amount of work was required to adapt them for the new challenges such systems present. This paper describes the most important solutions found. It also identies important future research trends in data management in P2P DHT systems

    Engineering Privacy in Public: Confounding Face Recognition

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    The objective of DARPA’s Human ID at a Distance (HID) program is to develop automated biometric identification technologies to detect, recognize and identify humans at great distances. While nominally intended for security applications, if deployed widely, such technologies could become an enormous privacy threat, making practical the automatic surveillance of individuals on a grand scale. Face recognition, as the HID technology most rapidly approaching maturity, deserves immediate research attention in order to understand its strengths and limitations, with an objective of reliably foiling it when it is used inappropriately. This paper is a status report for a research program designed to achieve this objective within a larger goal of similarly defeating all HID technologies

    cMix: Mixing with Minimal Real-Time Asymmetric Cryptographic Operations

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    We introduce cMix, a new approach to anonymous communications. Through a precomputation, the core cMix protocol eliminates all expensive realtime public-key operations --- at the senders, recipients and mixnodes --- thereby decreasing real-time cryptographic latency and lowering computational costs for clients. The core real-time phase performs only a few fast modular multiplications. In these times of surveillance and extensive profiling there is a great need for an anonymous communication system that resists global attackers. One widely recognized solution to the challenge of traffic analysis is a mixnet, which anonymizes a batch of messages by sending the batch through a fixed cascade of mixnodes. Mixnets can offer excellent privacy guarantees, including unlinkability of sender and receiver, and resistance to many traffic-analysis attacks that undermine many other approaches including onion routing. Existing mixnet designs, however, suffer from high latency in part because of the need for real-time public-key operations. Precomputation greatly improves the real-time performance of cMix, while its fixed cascade of mixnodes yields the strong anonymity guarantees of mixnets. cMix is unique in not requiring any real-time public-key operations by users. Consequently, cMix is the first mixing suitable for low latency chat for lightweight devices. Our presentation includes a specification of cMix, security arguments, anonymity analysis, and a performance comparison with selected other approaches. We also give benchmarks from our prototype

    A Universally Composable Framework for the Privacy of Email Ecosystems

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    Email communication is amongst the most prominent online activities, and as such, can put sensitive information at risk. It is thus of high importance that internet email applications are designed in a privacy-aware manner and analyzed under a rigorous threat model. The Snowden revelations (2013) suggest that such a model should feature a global adversary, in light of the observational tools available. Furthermore, the fact that protecting metadata can be of equal importance as protecting the communication context implies that end-to-end encryption may be necessary, but it is not sufficient. With this in mind, we utilize the Universal Composability framework [Canetti, 2001] to introduce an expressive cryptographic model for email ``ecosystems\u27\u27 that can formally and precisely capture various well-known privacy notions (unobservability, anonymity, unlinkability, etc.), by parameterizing the amount of leakage an ideal-world adversary (simulator) obtains from the email functionality. Equipped with our framework, we present and analyze the security of two email constructions that follow different directions in terms of the efficiency vs. privacy tradeoff. The first one achieves optimal security (only the online/offline mode of the users is leaked), but it is mainly of theoretical interest; the second one is based on parallel mixing [Golle and Juels, 2004] and is more practical, while it achieves anonymity with respect to users that have similar amount of sending and receiving activity

    Probable Innocence and Independent Knowledge

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    International audienceWe analyse the \textsc{Crowds} anonymity protocol under the novel assumption that the attacker has independent knowledge on behavioural patterns of individual users. Under such conditions we study, reformulate and extend Reiter and Rubin's notion of probable innocence, and provide a new formalisation for it based on the concept of protocol vulnerability. Accordingly, we establish new formal relationships between protocol parameters and attackers' knowledge expressing necessary and sufficient conditions to ensure probable innocence

    On the Optimal Placement of Mix Zones

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    In mobile wireless networks, third parties can track the location of mobile nodes by monitoring the pseudonyms used for identification. A frequently proposed solution to protect the location privacy of mobile nodes suggests to change pseudonyms in regions called mix zones. In this paper, we propose a novel metric based on the mobility profiles of mobile nodes to evaluate the mixing effectiveness of possible mix zone locations. Then, as the location privacy achieved with mix zones depends on their placement in the network, we analyze the optimal placement of mix zones with combinatorial optimization techniques. The proposed algorithm maximizes the achieved location privacy in the system and takes into account the cost on mobile nodes induced by mix zones. By means of simulations, we show that the placement recommended by our algorithm significantly reduces the tracking success by the adversary