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IEEE Journal of Selected Topics in Signal Processing

Issue 7 • Oct. 2015

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Displaying Results 1 - 23 of 23
  • Front Cover

    Publication Year: 2015, Page(s): C1
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  • IEEE Journal of Selected Topics in Signal Processing publication information

    Publication Year: 2015, Page(s): C2
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  • Table of Contents

    Publication Year: 2015, Page(s):1171 - 1172
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  • Introduction to the Issue on Signal and Information Processing for Privacy

    Publication Year: 2015, Page(s):1173 - 1175
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  • The Staircase Mechanism in Differential Privacy

    Publication Year: 2015, Page(s):1176 - 1184
    Cited by:  Papers (7)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2042 KB) | HTML iconHTML

    Adding Laplacian noise is a standard approach in differential privacy to sanitize numerical data before releasing it. In this paper, we propose an alternative noise adding mechanism: the staircase mechanism, which is a geometric mixture of uniform random variables. The staircase mechanism can replace the Laplace mechanism in each instance in the literature and for the same level of differential pr... View full abstract»

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  • Optical Signal Processing and Stealth Transmission for Privacy

    Publication Year: 2015, Page(s):1185 - 1194
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1479 KB) | HTML iconHTML

    Optical encryption, key generation, and optical stealth transmission techniques for protecting the privacy of communication in optical networks are proposed and summarized. The signal processing methods based on fiber components provide ways to encrypt data and generate encryption keys at the speed of data transmission in optical fibers. Private and confidential communication is achieved without c... View full abstract»

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  • Achieving Undetectable Communication

    Publication Year: 2015, Page(s):1195 - 1205
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2222 KB) | HTML iconHTML

    In this paper we consider the problem of achieving a positive error-free communications rate without being detected by an eavesdropper-we coin this the privacy rate. Specifically, we analyze the privacy rate over additive white Gaussian Noise (AWGN) channels with finite and infinite number of samples and Rayleigh single input-single (SISO) and multiple input-multiple output (MIMO) channels with in... View full abstract»

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  • Distributed Secret Dissemination Across a Network

    Publication Year: 2015, Page(s):1206 - 1216
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1653 KB) | HTML iconHTML

    Shamir's (n,k) threshold secret sharing is an important component of several cryptographic protocols, such as those for secure multiparty-computation and key management. These protocols typically assume the presence of direct communication links from the dealer to all participants, in which case the dealer can directly pass the shares of the secret to each participant. In this paper, we consider t... View full abstract»

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  • Secure Comparison Protocols in the Semi-Honest Model

    Publication Year: 2015, Page(s):1217 - 1228
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1709 KB) | HTML iconHTML

    Due to high complexity, comparison protocols with secret inputs have been a bottleneck in the design of privacy-preserving cryptographic protocols. Different solutions based on homomorphic encryption, garbled circuits and secret sharing techniques have been proposed over the last few years, each claiming high efficiency. Unfortunately, a fair comparison of existing protocols in terms of run-time, ... View full abstract»

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  • Efficient Private Information Retrieval Over Unsynchronized Databases

    Publication Year: 2015, Page(s):1229 - 1239
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2192 KB) | HTML iconHTML

    Web search histories can reveal detailed and sensitive information about people. Private information retrieval (PIR) tackles this potential privacy violation by allowing users to retrieve the wth record of a database without revealing w to the server. However, most known PIR schemes are either very inefficient (and therefore unlikely to gain traction in a practical sense) or reliant on some restri... View full abstract»

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  • Managing Your Private and Public Data: Bringing Down Inference Attacks Against Your Privacy

    Publication Year: 2015, Page(s):1240 - 1255
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2845 KB) | HTML iconHTML

    We propose a practical methodology to protect a user's private data, when he wishes to publicly release data that is correlated with his private data, to get some utility. Our approach relies on a general statistical inference framework that captures the privacy threat under inference attacks, given utility constraints. Under this framework, data is distorted before it is released, according to a ... View full abstract»

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  • Privacy or Utility in Data Collection? A Contract Theoretic Approach

    Publication Year: 2015, Page(s):1256 - 1269
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2862 KB) | HTML iconHTML

    With the growing popularity of data mining, privacy has become an issue of growing importance. Privacy can be seen as a special type of goods, in a sense that it can be traded by the owner for incentives. In this paper, we consider a private data collecting scenario where a data collector buys data from multiple data owners and employs anonymization techniques to protect data owners' privacy. Anon... View full abstract»

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  • A Study of Online Social Network Privacy Via the TAPE Framework

    Publication Year: 2015, Page(s):1270 - 1284
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1941 KB) | HTML iconHTML

    While personal information privacy is threatened by online social networks, researchers are seeking for privacy protection tools and methods to assist online social network users. In this paper, we propose a Trust-Aware Privacy Evaluation framework, called TAPE, aiming to address this problem. Under the TAPE framework we investigate how to quantitatively evaluate the privacy risk, as a function of... View full abstract»

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  • Enabling Data Exchange in Two-Agent Interactive Systems Under Privacy Constraints

    Publication Year: 2015, Page(s):1285 - 1297
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2367 KB) | HTML iconHTML

    It is advantageous for collecting agents in interconnected systems to exchange information (e.g., functions of their measurements) in order to improve their local processing (e.g., state estimation) because of the typically correlated nature of the data in such systems. However, privacy concerns may limit or prevent this exchange leading to a tradeoff between state estimation fidelity and privacy ... View full abstract»

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  • A Secure Radio Environment Map Database to Share Spectrum

    Publication Year: 2015, Page(s):1298 - 1305
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1166 KB) | HTML iconHTML

    A robust and secure database for spectrum sharing in cognitive radio networks that is obscured from the viewpoint of secondary users is presented. The database allocations secure features of white space resource usage from being learned. The design of non-inferable database is based on two cases. In the first case, the primary or spectrum lender has no knowledge of secondary users or potential jam... View full abstract»

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  • A Belief Propagation Approach to Privacy-Preserving Item-Based Collaborative Filtering

    Publication Year: 2015, Page(s):1306 - 1318
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2167 KB) | HTML iconHTML

    Collaborative filtering (CF) is the most popular recommendation algorithm, which exploits the collected historic user ratings to predict unknown ratings. However, traditional recommender systems run at the central servers, and thus users have to disclose their personal rating data to other parties. This raises the privacy issue, as user ratings can be used to reveal sensitive personal information.... View full abstract»

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  • The Price of Privacy in Untrusted Recommender Systems

    Publication Year: 2015, Page(s):1319 - 1331
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2713 KB) | HTML iconHTML

    Recent increase in online privacy concerns prompts the following question: can a recommender system be accurate if users do not entrust it with their private data? To answer this, we study the problem of learning item-clusters under local differential privacy, a powerful, formal notion of data privacy. We develop bounds on the sample-complexity of learning item-clusters from privatized user inputs... View full abstract»

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  • PPDM: A Privacy-Preserving Protocol for Cloud-Assisted e-Healthcare Systems

    Publication Year: 2015, Page(s):1332 - 1344
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2702 KB) | HTML iconHTML

    E-healthcare systems have been increasingly facilitating health condition monitoring, disease modeling and early intervention, and evidence-based medical treatment by medical text mining and image feature extraction. Owing to the resource constraint of wearable mobile devices, it is required to outsource the frequently collected personal health information (PHI) into the cloud. Unfortunately, dele... View full abstract»

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  • Privacy-Aware Distributed Bayesian Detection

    Publication Year: 2015, Page(s):1345 - 1357
    Cited by:  Papers (3)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2460 KB) | HTML iconHTML

    We study the eavesdropping problem in the remotely distributed sensing of a privacy-sensible hypothesis from the Bayesian detection perspective. We consider a parallel distributed detection network where remote decision makers independently make local decisions defined on finite domains and forward them to the fusion center which makes the final decision. An eavesdropper is assumed to intercept a ... View full abstract»

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  • [Blank page]

    Publication Year: 2015, Page(s): B1358
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  • IEEE Journal of Selected Topics in Signal Processing information for authors

    Publication Year: 2015, Page(s):1359 - 1360
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  • IEEE Signal Processing Society Information

    Publication Year: 2015, Page(s): C3
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  • [Blank page - back cover]

    Publication Year: 2015, Page(s): C4
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Aims & Scope

The Journal of Selected Topics in Signal Processing (J-STSP) solicits special issues on topics that cover the entire scope of the IEEE Signal Processing Society including the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals by digital or analog devices or techniques.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief

Shrikanth (Shri) S. Narayanan
Viterbi School of Engineering 
University of Southern California
Los Angeles, CA 90089 USA
shri@sipi.usc.edu