PCD

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Page 96 blank. Cataloged from PDF version of thesis.Includes bibliographical references (p. 87-95).The security of systems can often be expressed as ensuring that some property is maintained at every step of a distributed computation conducted by untrusted parties. Special cases include integrity of programs running on untrusted platforms, various forms of confidentiality and side-channel resilience, and domain-specific invariants. We propose a new approach, proof-carrying data (PCD), which sidesteps the threat of faults and leakage by reasoning about properties of a computation's output data, regardless of the process that produced it. In PCD, the system designer prescribes the desired properties of a computation's outputs. Corresponding proofs are attached to every message flowing through the system, and are mutually verified by the system's components. Each such proof attests that the message's data and all of its history comply with the prescribed properties. We construct a general protocol compiler that generates, propagates, and verifies such proofs of compliance, while preserving the dynamics and efficiency of the original computation. Our main technical tool is the cryptographic construction of short non-interactive arguments (computationally-sound proofs) for statements whose truth depends on "hearsay evidence": previous arguments about other statements. To this end, we attain a particularly strong proof-of-knowledge property. We realize the above, under standard cryptographic assumptions, in a model where the prover has blackbox access to some simple functionality - essentially, a signature card.by Alessandro Chiesa.M.Eng

Secure multi-party protocols under a modern lens

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 263-272).A secure multi-party computation (MPC) protocol for computing a function f allows a group of parties to jointly evaluate f over their private inputs, such that a computationally bounded adversary who corrupts a subset of the parties can not learn anything beyond the inputs of the corrupted parties and the output of the function f. General MPC completeness theorems in the 1980s showed that every efficiently computable function can be evaluated securely in this fashion [Yao86, GMW87, CCD87, BGW88] using the existence of cryptography. In the following decades, progress has been made toward making MPC protocols efficient enough to be deployed in real-world applications. However, recent technological developments have brought with them a slew of new challenges, from new security threats to a question of whether protocols can scale up with the demand of distributed computations on massive data. Before one can make effective use of MPC, these challenges must be addressed. In this thesis, we focus on two lines of research toward this goal: " Protocols resilient to side-channel attacks. We consider a strengthened adversarial model where, in addition to corrupting a subset of parties, the adversary may leak partial information on the secret states of honest parties during the protocol. In presence of such adversary, we first focus on preserving the correctness guarantees of MPC computations. We then proceed to address security guarantees, using cryptography. We provide two results: an MPC protocol whose security provably "degrades gracefully" with the amount of leakage information obtained by the adversary, and a second protocol which provides complete security assuming a (necessary) one-time preprocessing phase during which leakage cannot occur. * Protocols with scalable communication requirements. We devise MPC protocols with communication locality: namely, each party only needs to communicate with a small (polylog) number of dynamically chosen parties. Our techniques use digital signatures and extend particularly well to the case when the function f is a sublinear algorithm whose execution depends on o(n) of the n parties' inputs.by Elette Chantae Boyle.Ph.D

Minimum disclosure proofs of knowledge

AbstractProtocols are given for allowing a “prover” to convince a “verifier” that the prover knows some verifiable secret information, without allowing the verifier to learn anything about the secret. The secret can be probabilistically or deterministically verifiable, and only one of the prover or the verifier need have constrained resources. This paper unifies and extends models and techniques previously put forward by the authors, and compares some independent related work

User-Centric Security and Privacy Mechanisms in Untrusted Networking and Computing Environments

Our modern society is increasingly relying on the collection, processing, and sharing of digital information. There are two fundamental trends: (1) Enabled by the rapid developments in sensor, wireless, and networking technologies, communication and networking are becoming more and more pervasive and ad hoc. (2) Driven by the explosive growth of hardware and software capabilities, computation power is becoming a public utility and information is often stored in centralized servers which facilitate ubiquitous access and sharing. Many emerging platforms and systems hinge on both dimensions, such as E-healthcare and Smart Grid. However, the majority information handled by these critical systems is usually sensitive and of high value, while various security breaches could compromise the social welfare of these systems. Thus there is an urgent need to develop security and privacy mechanisms to protect the authenticity, integrity and confidentiality of the collected data, and to control the disclosure of private information. In achieving that, two unique challenges arise: (1) There lacks centralized trusted parties in pervasive networking; (2) The remote data servers tend not to be trusted by system users in handling their data. They make existing security solutions developed for traditional networked information systems unsuitable. To this end, in this dissertation we propose a series of user-centric security and privacy mechanisms that resolve these challenging issues in untrusted network and computing environments, spanning wireless body area networks (WBAN), mobile social networks (MSN), and cloud computing. The main contributions of this dissertation are fourfold. First, we propose a secure ad hoc trust initialization protocol for WBAN, without relying on any pre-established security context among nodes, while defending against a powerful wireless attacker that may or may not compromise sensor nodes. The protocol is highly usable for a human user. Second, we present novel schemes for sharing sensitive information among distributed mobile hosts in MSN which preserves user privacy, where the users neither need to fully trust each other nor rely on any central trusted party. Third, to realize owner-controlled sharing of sensitive data stored on untrusted servers, we put forward a data access control framework using Multi-Authority Attribute-Based Encryption (ABE), that supports scalable fine-grained access and on-demand user revocation, and is free of key-escrow. Finally, we propose mechanisms for authorized keyword search over encrypted data on untrusted servers, with efficient multi-dimensional range, subset and equality query capabilities, and with enhanced search privacy. The common characteristic of our contributions is they minimize the extent of trust that users must place in the corresponding network or computing environments, in a way that is user-centric, i.e., favoring individual owners/users

Calculs multipartites

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal

Anonymity meets game theory: secure data integration with malicious participants

Data integration methods enable different data providers to flexibly integrate their expertise and deliver highly customizable services to their customers. Nonetheless, combining data from different sources could potentially reveal person-specific sensitive information. In VLDBJ 2006, Jiang and Clifton (Very Large Data Bases J (VLDBJ) 15(4):316–333, 2006) propose a secure Distributed k-Anonymity (DkA) framework for integrating two private data tables to a k-anonymous table in which each private table is a vertical partition on the same set of records. Their proposed DkA framework is not scalable to large data sets. Moreover, DkA is limited to a two-party scenario and the parties are assumed to be semi-honest. In this paper, we propose two algorithms to securely integrate private data from multiple parties (data providers). Our first algorithm achieves the k-anonymity privacy model in a semi-honest adversary model. Our second algorithm employs a game-theoretic approach to thwart malicious participants and to ensure fair and honest participation of multiple data providers in the data integration process. Moreover, we study and resolve a real-life privacy problem in data sharing for the financial industry in Sweden. Experiments on the real-life data demonstrate that our proposed algorithms can effectively retain the essential information in anonymous data for data analysis and are scalable for anonymizing large data sets

New Fundamental Technologies in Data Mining

The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining