Conference Paper

Simplified VSS and Fact-Track Multiparty Computations with Applications to Threshold Cryptography.

Source: DBLP
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    ABSTRACT: Secure multiparty computation (SMC) has gained tremendous importance with the growth of the Internet and e-commerce, where mutually untrusted parties need to jointly compute a function of their private inputs. However, SMC protocols usually have very high computational complexities, rendering them practically unusable. In this paper, we tackle the problem of comparing two input values in a secure distributed fashion. We propose efficient secure comparison protocols for both the homomorphic encryption and secret sharing schemes. We also give experimental results to show their practical relevance.
    Database and Expert Systems Application, 2009. DEXA '09. 20th International Workshop on; 10/2009
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    ABSTRACT: Secure multiparty computation (MPC) allows joint privacy-preserving computations on data of multiple parties. Although MPC has been studied substantially, building solutions that are practical in terms of computation and communication cost is still a major challenge. In this paper, we investigate the practical usefulness of MPC for multi-domain network security and monitoring. We first optimize MPC comparison operations for processing high volume data in near real-time. We then design privacy-preserving protocols for event correlation and aggregation of network traffic statistics, such as addition of volume metrics, computation of feature entropy, and distinct item count. Optimizing performance of parallel invocations, we implement our protocols along with a complete set of basic operations in a library called SEPIA. We evaluate the running time and bandwidth requirements of our protocols in realistic settings on a local cluster as well as on PlanetLab and show that they work in near real-time for up to 140 input providers and 9 computation nodes. Compared to implementations using existing general-purpose MPC frameworks, our protocols are significantly faster, requiring, for example, 3 minutes for a task that takes 2 days with general-purpose frameworks. This improvement paves the way for new applications of MPC in the area of networking. Finally, we run SEPIA’s protocols on real traffic traces of 17 networks and show how they provide new possibilities for distributed troubleshooting and early anomaly detection.
    Proceedings of USENIX Security Symposium. 01/2010;
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    ABSTRACT: We present a new statistical asynchronous verifiable secret sharing (AVSS) protocol with optimal resilience; i.e. with n = 3t + 1, where n is the total number of participating parties and t is the maximum number of parties that can be under the control of a computationally unbounded active adversary At{\mathcal A}_t. Our protocol privately communicates O((ln3 + n4 k) k){\mathcal O}((\ell n^3 + n^4 \kappa) \kappa) bits and A-casts O(n3 log(n)){\mathcal O}(n^3 \log(n)) bits to simultaneously share ℓ ≥ 1 elements from a finite field \mathbb F{\mathbb F}, where κ is the error parameter. There are only two known statistical AVSS protocols with n = 3t + 1, reported in [11] and [26]. The AVSS protocol of [11] requires a private communication of O(n9 k4){\mathcal O}(n^9 \kappa^4) bits and A-cast of O(n9 k2 log(n)){\mathcal O}(n^9 \kappa^2 \log(n)) bits to share a single element from \mathbb F{\mathbb F}. Thus our AVSS protocol shows a significant improvement in communication complexity over the AVSS of [11]. The AVSS protocol of [26] requires a private communication of O((ln3 + n4) k){\mathcal O}((\ell n^3 + n^4) \kappa) bits and A-cast of O((ln3 + n4) k){\mathcal O}((\ell n^3 + n^4) \kappa) bits to share ℓ ≥ 1 elements. However, the shared element(s) may be NULL \not Î \mathbb FNULL \not \in {\mathbb F}. Thus our AVSS is better than the AVSS of [26] due to two reasons: (a) The A-cast communication of our AVSS is independent of the number of secrets i.e. ℓ; (b) Our AVSS makes sure that the shared value(s) always belong to \mathbb F{\mathbb F}. Using our AVSS, we design a new primitive called Asynchronous Complete Secret Sharing (ACSS) which is an essential building block of asynchronous multiparty computation (AMPC). Using our ACSS scheme, we can design a statistical AMPC with optimal resilience; i.e., with n = 3t + 1, that privately communicates O(n5 k){\mathcal O}(n^5 \kappa) bits per multiplication gate. This will significantly improve the only known statistical AMPC of [8] with n = 3t + 1, which privately communicates Ω(n 11 κ 4) bits and A-cast Ω(n 11 κ 2 log(n)) bits per multiplication gate.
    Information Theoretic Security, 4th International Conference, ICITS 2009, Shizuoka, Japan, December 3-6, 2009. Revised Selected Papers; 01/2009