Shantanu Rane

Publications (7)0 Total impact

• Article: On the Benefits of Sampling in Privacy Preserving Statistical Analysis on Distributed Databases

  Bing-Rong Lin, Ye Wang, Shantanu Rane
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  ABSTRACT: We consider a problem where mutually untrusting curators possess portions of a vertically partitioned database containing information about a set of individuals. The goal is to enable an authorized party to obtain aggregate (statistical) information from the database while protecting the privacy of the individuals, which we formalize using Differential Privacy. This process can be facilitated by an untrusted server that provides storage and processing services but should not learn anything about the database. This work describes a data release mechanism that employs Post Randomization (PRAM), encryption and random sampling to maintain privacy, while allowing the authorized party to conduct an accurate statistical analysis of the data. Encryption ensures that the storage server obtains no information about the database, while PRAM and sampling ensures individual privacy is maintained against the authorized party. We characterize how much the composition of random sampling with PRAM increases the differential privacy of system compared to using PRAM alone. We also analyze the statistical utility of our system, by bounding the estimation error - the expected l2-norm error between the true empirical distribution and the estimated distribution - as a function of the number of samples, PRAM noise, and other system parameters. Our analysis shows a tradeoff between increasing PRAM noise versus decreasing the number of samples to maintain a desired level of privacy, and we determine the optimal number of samples that balances this tradeoff and maximizes the utility. In experimental simulations with the UCI "Adult Data Set" and with synthetically generated data, we confirm that the theoretically predicted optimal number of samples indeed achieves close to the minimal empirical error, and that our analytical error bounds match well with the empirical results.
  04/2013;
• Article: Information-Theoretically Secure Three-Party Computation with One Corrupted Party

  Ye Wang, Prakash Ishwar, Shantanu Rane
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  ABSTRACT: The problem in which one of three pairwise interacting parties is required to securely compute a function of the inputs held by the other two, when one party may arbitrarily deviate from the computation protocol (active behavioral model), is studied. An information-theoretic characterization of unconditionally secure computation protocols under the active behavioral model is provided. A protocol for Hamming distance computation is provided and shown to be unconditionally secure under both active and passive behavioral models using the information-theoretic characterization. The difference between the notions of security under the active and passive behavioral models is illustrated through the BGW protocol for computing quadratic and Hamming distances; this protocol is secure under the passive model, but is shown to be not secure under the active model.
  06/2012;
• Source

  Available from: ArXiv

  Article: A Theoretical Analysis of Authentication, Privacy and Reusability Across Secure Biometric Systems

  Ye Wang, Shantanu Rane, Stark C. Draper, Prakash Ishwar
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  ABSTRACT: We present a theoretical framework for the analysis of privacy and security tradeoffs in secure biometric authentication systems. We use this framework to conduct a comparative information-theoretic analysis of two biometric systems that are based on linear error correction codes, namely fuzzy commitment and secure sketches. We derive upper bounds for the probability of false rejection ($P_{FR}$) and false acceptance ($P_{FA}$) for these systems. We use mutual information to quantify the information leaked about a user's biometric identity, in the scenario where one or multiple biometric enrollments of the user are fully or partially compromised. We also quantify the probability of successful attack ($P_{SA}$) based on the compromised information. Our analysis reveals that fuzzy commitment and secure sketch systems have identical $P_{FR}, P_{FA}, P_{SA}$ and information leakage, but secure sketch systems have lower storage requirements. We analyze both single-factor (keyless) and two-factor (key-based) variants of secure biometrics, and consider the most general scenarios in which a single user may provide noisy biometric enrollments at several access control devices, some of which may be subsequently compromised by an attacker. Our analysis highlights the revocability and reusability properties of key-based systems and exposes a subtle design tradeoff between reducing information leakage from compromised systems and preventing successful attacks on systems whose data have not been compromised.
  12/2011;
• Source

  Available from: 140.124.72.88

  Conference Proceeding: Privacy preserving probabilistic inference with Hidden Markov Models.

  Manas A. Pathak, Shantanu Rane, Wei Sun, Bhiksha Raj
  Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011, May 22-27, 2011, Prague Congress Center, Prague, Czech Republic; 01/2011
• Source

  Available from: ArXiv

  Article: On Unconditionally Secure Computation with Vanishing Communication Cost

  Ye Wang, Shantanu Rane, Wei Sun, Prakash Ishwar
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  ABSTRACT: We propose a novel distortion-theoretic approach to a secure three-party computation problem. Alice and Bob have deterministic sequences, and Charlie wishes to compute a normalized sum-type function of those sequences. We construct three-party protocols that allow Charlie to compute the function with arbitrarily high accuracy, while maintaining unconditional privacy for Alice and Bob and achieving vanishing communication cost. This work leverages a striking dimensionality reduction that allows a high accuracy estimate to be produced from only a random subsampling of the sequences. The worst-case distortion of the estimate, across all arbitrary deterministic sequences of any length, is independent of the dimensionality (length) of the sequences and proportional to inverse square root of the number of samples that the estimate is based upon. Comment: 7 pages, 1 figure. Appeared in the Proceedings of the 2010 Allerton Conference On Communication, Control, and Computing
  10/2010;
• Source

  Available from: Anthony Vetro

  Conference Proceeding: Privacy-preserving approximation of L1 distance for multimedia applications.

  Shantanu Rane, Wei Sun, Anthony Vetro
  Proceedings of the 2010 IEEE International Conference on Multimedia and Expo, ICME 2010, 19-23 July 2010, Singapore; 01/2010
• Conference Proceeding: Secure distortion computation among untrusting parties using homomorphic encryption.

  Shantanu Rane, Wei Sun, Anthony Vetro
  Proceedings of the International Conference on Image Processing, ICIP 2009, 7-10 November 2009, Cairo, Egypt; 01/2009