Pub Date : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174022
Jeongmin Chae, Songnam Hong
We propose a novel greedy algorithm to recover a sparse signal from a small number of noisy measurements. In the proposed method, a new support index is identified for each iteration, based on bit-wise maximum a posteriori (B-MAP) detection. This approach is an optimal in the sense of detecting one of the remaining support indices, provided that all the indices during the previous iterations are perfectly recovered. Unfortunately, the exact computation of B-MAP detection is not practical since it requires a heavy marginalization of a highdimensional sparse vector to compute a posteriori probability of each remaining support. Our major contribution is to present a good proxy, named B-MAP proxy, on the a posteriori probability. The proposed proxy is easily evaluated only using vector correlations as in popular orthogonal matching pursuit (OMP) and accurate enough to represent a relative ordering on the probabilities. Via simulations, we demonstrate that the proposed greedy algorithm yields a higher recovery accuracy than the existing benchmark methods as OMP and MAP-OMP, having the same computational complexity.A full version of this paper is accessible at: https://arxiv.org/abs/1910.12512/
{"title":"A Novel B-MAP Proxy for Greedy Sparse Signal Recovery Algorithms","authors":"Jeongmin Chae, Songnam Hong","doi":"10.1109/ISIT44484.2020.9174022","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174022","url":null,"abstract":"We propose a novel greedy algorithm to recover a sparse signal from a small number of noisy measurements. In the proposed method, a new support index is identified for each iteration, based on bit-wise maximum a posteriori (B-MAP) detection. This approach is an optimal in the sense of detecting one of the remaining support indices, provided that all the indices during the previous iterations are perfectly recovered. Unfortunately, the exact computation of B-MAP detection is not practical since it requires a heavy marginalization of a highdimensional sparse vector to compute a posteriori probability of each remaining support. Our major contribution is to present a good proxy, named B-MAP proxy, on the a posteriori probability. The proposed proxy is easily evaluated only using vector correlations as in popular orthogonal matching pursuit (OMP) and accurate enough to represent a relative ordering on the probabilities. Via simulations, we demonstrate that the proposed greedy algorithm yields a higher recovery accuracy than the existing benchmark methods as OMP and MAP-OMP, having the same computational complexity.A full version of this paper is accessible at: https://arxiv.org/abs/1910.12512/","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"297 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115135506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174272
A. Lenz, Yi Liu, Cyrus Rashtchian, P. Siegel, A. Wachter-Zeh, Eitan Yaakobi
For DNA data storage to become a feasible technology, all aspects of the encoding and decoding pipeline must be optimized. Writing the data into DNA, which is known as DNA synthesis, is currently the most costly part of existing storage systems. As a step toward more efficient synthesis, we study the design of codes that minimize the time and number of required materials needed to produce the DNA strands. We consider a popular synthesis process that builds many strands in parallel in a step-by-step fashion using a fixed supersequence S. The machine iterates through S one nucleotide at a time, and in each cycle, it adds the next nucleotide to a subset of the strands. The synthesis time is determined by the length of S. We show that by introducing redundancy to the synthesized strands, we can significantly decrease the number of synthesis cycles. We derive the maximum amount of information per synthesis cycle assuming S is an arbitrary periodic sequence. To prove our results, we exhibit new connections to cost-constrained codes.
{"title":"Coding for Efficient DNA Synthesis","authors":"A. Lenz, Yi Liu, Cyrus Rashtchian, P. Siegel, A. Wachter-Zeh, Eitan Yaakobi","doi":"10.1109/ISIT44484.2020.9174272","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174272","url":null,"abstract":"For DNA data storage to become a feasible technology, all aspects of the encoding and decoding pipeline must be optimized. Writing the data into DNA, which is known as DNA synthesis, is currently the most costly part of existing storage systems. As a step toward more efficient synthesis, we study the design of codes that minimize the time and number of required materials needed to produce the DNA strands. We consider a popular synthesis process that builds many strands in parallel in a step-by-step fashion using a fixed supersequence S. The machine iterates through S one nucleotide at a time, and in each cycle, it adds the next nucleotide to a subset of the strands. The synthesis time is determined by the length of S. We show that by introducing redundancy to the synthesized strands, we can significantly decrease the number of synthesis cycles. We derive the maximum amount of information per synthesis cycle assuming S is an arbitrary periodic sequence. To prove our results, we exhibit new connections to cost-constrained codes.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"41 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116989197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174484
Yuuya Yoshida, Masahito Hayashi
Differential privacy (DP) is an influential privacy measure and has been studied to protect private data. DP has been often studied in classical probability theory, but few researchers studied quantum versions of DP. In this paper, we consider classical-quantum DP mechanisms which (i) convert binary private data to quantum states and (ii) satisfy a quantum version of the DP constraint. The class of classical-quantum DP mechanisms contains classical DP mechanisms. As a main result, we show that some classical DP mechanism optimizes any information quantity satisfying the information processing inequality. Therefore, the performance of classical DP mechanisms attains that of classical-quantum DP mechanisms.
{"title":"Classical Mechanism is Optimal in Classical-Quantum Differentially Private Mechanisms","authors":"Yuuya Yoshida, Masahito Hayashi","doi":"10.1109/ISIT44484.2020.9174484","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174484","url":null,"abstract":"Differential privacy (DP) is an influential privacy measure and has been studied to protect private data. DP has been often studied in classical probability theory, but few researchers studied quantum versions of DP. In this paper, we consider classical-quantum DP mechanisms which (i) convert binary private data to quantum states and (ii) satisfy a quantum version of the DP constraint. The class of classical-quantum DP mechanisms contains classical DP mechanisms. As a main result, we show that some classical DP mechanism optimizes any information quantity satisfying the information processing inequality. Therefore, the performance of classical DP mechanisms attains that of classical-quantum DP mechanisms.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123564683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174352
Kazuho Watanabe
The optimal reconstruction distribution achieving the rate-distortion function is elusive except for limited examples of sources and distortion measures if the rate-distortion function is strictly greater than the Shannon lower bound. In this paper, focusing on the Itakura-Saito distortion measure, we prove that if the Shannon lower bound is not tight, the optimal reconstruction distribution is purely discrete. Combined with the fact that the Shannon lower bound is tight for the gamma source, this result shows that it is the only source that has continuous optimal reconstruction distributions for the range of entire positive rate.
{"title":"Discrete Optimal Reconstruction Distributions for Itakura-Saito Distortion Measure","authors":"Kazuho Watanabe","doi":"10.1109/ISIT44484.2020.9174352","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174352","url":null,"abstract":"The optimal reconstruction distribution achieving the rate-distortion function is elusive except for limited examples of sources and distortion measures if the rate-distortion function is strictly greater than the Shannon lower bound. In this paper, focusing on the Itakura-Saito distortion measure, we prove that if the Shannon lower bound is not tight, the optimal reconstruction distribution is purely discrete. Combined with the fact that the Shannon lower bound is tight for the gamma source, this result shows that it is the only source that has continuous optimal reconstruction distributions for the range of entire positive rate.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125548178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174000
Maha Zohdy, A. Tajer, S. Shamai
Effective interference management in the multiuser interference channel strongly hinges on the availability of the channel state information at the transmitters (CSIT). In a broad range of emerging large-scale and distributed networks (e.g., the Internet of Things), however, acquiring the CSIT is prohibitive, due to the extensive information exchange that it imposes. In such circumstances, as a result, the interference management approaches that rely on the CSIT lose their effectiveness. This paper focuses on the two-user interference channel, and proposes a broadcast approach to interference management. Its hallmark is that the transmitters, unlike the receivers, are completely oblivious to instantaneous channel states. Each transmitter splits its message into multiple superimposed encoded information layers, where each layer is adapted to a given possible state for the combined states of all channels. Depending on the relative strengths of the direct and interfering channels, each receiver opportunistically decodes a subset of the received layers from both transmitters. An average achievable rate region is delineated serving as an inner bound on the average capacity region of the Gaussian interference channel in the absence of CSIT. Finally, it characterizes the gap between the achievable average sum-rate and the sum-rate capacity with the full CSIT in the asymptote of high signal-to-noise ratio. Numerical evaluations show that the cost of lacking CSIT is often insignificant.
{"title":"Interference Management without CSIT: A Broadcast Approach","authors":"Maha Zohdy, A. Tajer, S. Shamai","doi":"10.1109/ISIT44484.2020.9174000","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174000","url":null,"abstract":"Effective interference management in the multiuser interference channel strongly hinges on the availability of the channel state information at the transmitters (CSIT). In a broad range of emerging large-scale and distributed networks (e.g., the Internet of Things), however, acquiring the CSIT is prohibitive, due to the extensive information exchange that it imposes. In such circumstances, as a result, the interference management approaches that rely on the CSIT lose their effectiveness. This paper focuses on the two-user interference channel, and proposes a broadcast approach to interference management. Its hallmark is that the transmitters, unlike the receivers, are completely oblivious to instantaneous channel states. Each transmitter splits its message into multiple superimposed encoded information layers, where each layer is adapted to a given possible state for the combined states of all channels. Depending on the relative strengths of the direct and interfering channels, each receiver opportunistically decodes a subset of the received layers from both transmitters. An average achievable rate region is delineated serving as an inner bound on the average capacity region of the Gaussian interference channel in the absence of CSIT. Finally, it characterizes the gap between the achievable average sum-rate and the sum-rate capacity with the full CSIT in the asymptote of high signal-to-noise ratio. Numerical evaluations show that the cost of lacking CSIT is often insignificant.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115339513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174034
Grace Villacrés, T. Koch, G. Vazquez-Vilar
The channel capacity of wireless networks Is often studied under the assumption that the communicating nodes have perfect channel-state information and that interference is always present. In this paper, we study the channel capacity of a wireless network without these assumptions, i.e., a bursty noncoherent wireless network where the users are grouped in cells and the base-station features several receive antennas. We demonstrate that the channel capacity is bounded in the signal-to-noise ratio (SNR) when the number of receive antennas is finite and the probability of presence of interference is strictly positive.
{"title":"Bursty Wireless Networks of Bounded Capacity","authors":"Grace Villacrés, T. Koch, G. Vazquez-Vilar","doi":"10.1109/ISIT44484.2020.9174034","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174034","url":null,"abstract":"The channel capacity of wireless networks Is often studied under the assumption that the communicating nodes have perfect channel-state information and that interference is always present. In this paper, we study the channel capacity of a wireless network without these assumptions, i.e., a bursty noncoherent wireless network where the users are grouped in cells and the base-station features several receive antennas. We demonstrate that the channel capacity is bounded in the signal-to-noise ratio (SNR) when the number of receive antennas is finite and the probability of presence of interference is strictly positive.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116043879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174342
H. Boche, R. Schaefer, H. Poor
A coding theorem consists of two parts: achievability and converse which establish lower and upper bounds on the capacity. This paper analyzes these bounds from a fundamental, algorithmic point of view by studying whether or not such bounds can be computed algorithmically in principle (without putting any constraints on the computational complexity of such algorithms). For this purpose, the concept of Turing machines is used which provides the fundamental performance limits of digital computers. To this end, computable continuous functions are studied and properties of computable sequences of such functions are identified. Subsequently, these findings are exemplarily applied to two different open problems. The first one is the ϵ-capacity of compound channels which is unknown to date. It is studied whether or not the ϵ-capacity can be algorithmically computed and it is shown that there is no computable characterization of the difference between computable upper and lower bounds possible. Thus, computable sharp lower and upper bounds on the ϵ-capacity of computable compound channels cannot exist. The crucial consequence is that the ϵ-capacity cannot be characterized by a finite-letter entropic expression. The second application involves asymptotic bounds for error-correcting codes which is a long-standing open problem in coding theory. Only lower and upper bounds are known which are not sharp. It is conjectured that the asymptotic bound is indeed a non-computable function which would then imply with the previous findings that it is impossible to find computable lower and upper bounds that are asymptotically tight.
{"title":"On the Algorithmic Computability of Achievability and Converse: ϵ-Capacity of Compound Channels and Asymptotic Bounds of Error-Correcting Codes","authors":"H. Boche, R. Schaefer, H. Poor","doi":"10.1109/ISIT44484.2020.9174342","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174342","url":null,"abstract":"A coding theorem consists of two parts: achievability and converse which establish lower and upper bounds on the capacity. This paper analyzes these bounds from a fundamental, algorithmic point of view by studying whether or not such bounds can be computed algorithmically in principle (without putting any constraints on the computational complexity of such algorithms). For this purpose, the concept of Turing machines is used which provides the fundamental performance limits of digital computers. To this end, computable continuous functions are studied and properties of computable sequences of such functions are identified. Subsequently, these findings are exemplarily applied to two different open problems. The first one is the ϵ-capacity of compound channels which is unknown to date. It is studied whether or not the ϵ-capacity can be algorithmically computed and it is shown that there is no computable characterization of the difference between computable upper and lower bounds possible. Thus, computable sharp lower and upper bounds on the ϵ-capacity of computable compound channels cannot exist. The crucial consequence is that the ϵ-capacity cannot be characterized by a finite-letter entropic expression. The second application involves asymptotic bounds for error-correcting codes which is a long-standing open problem in coding theory. Only lower and upper bounds are known which are not sharp. It is conjectured that the asymptotic bound is indeed a non-computable function which would then imply with the previous findings that it is impossible to find computable lower and upper bounds that are asymptotically tight.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122411287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174329
Mohannad Shehadeh, F. Kschischang
Just as rank-metric or Gabidulin codes may be used to construct rate-diversity tradeoff optimal space-time codes, a recently introduced generalization for the sum-rank metric, linearized Reed-Solomon codes, accomplishes the same in the case of multiple fading blocks. We provide the first explicit construction of minimal-delay rate-diversity optimal multiblock space-time codes as an application of linearized Reed-Solomon codes. We then demonstrate in simulation an example of a 2-block 2-by-2 code which, with a small performance penalty—less than 1 dB at a codeword error rate of 1e-4—matches the bit rate of a full diversity alternative while using a much smaller transmitted constellation. A stack decoder for this code is then suggested.
{"title":"Rate-Diversity Optimal Multiblock Space-Time Codes via Sum-Rank Codes","authors":"Mohannad Shehadeh, F. Kschischang","doi":"10.1109/ISIT44484.2020.9174329","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174329","url":null,"abstract":"Just as rank-metric or Gabidulin codes may be used to construct rate-diversity tradeoff optimal space-time codes, a recently introduced generalization for the sum-rank metric, linearized Reed-Solomon codes, accomplishes the same in the case of multiple fading blocks. We provide the first explicit construction of minimal-delay rate-diversity optimal multiblock space-time codes as an application of linearized Reed-Solomon codes. We then demonstrate in simulation an example of a 2-block 2-by-2 code which, with a small performance penalty—less than 1 dB at a codeword error rate of 1e-4—matches the bit rate of a full diversity alternative while using a much smaller transmitted constellation. A stack decoder for this code is then suggested.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121914333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174439
Jonathan Ponniah, Liang-Liang Xie
A general network is studied in which messages are relayed from multiple sources to multiple destinations according to a certain hierarchical order. The framework of flow decomposition is used to show the class of regular-order decode-forward index-coding schemes is computable. A shifting algorithm finds encoding/decoding schemes in ${text{P}}(|mathcal{N}|){text{EXP}}(|mathcal{S}|)$ time that achieve desired rate-vectors, where $mathcal{N}$ is the set of nodes and $mathcal{S} subseteq mathcal{N}$ is the subset of source nodes in the channel.
{"title":"Multi-Cast Channels with Hierarchical Flow","authors":"Jonathan Ponniah, Liang-Liang Xie","doi":"10.1109/ISIT44484.2020.9174439","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174439","url":null,"abstract":"A general network is studied in which messages are relayed from multiple sources to multiple destinations according to a certain hierarchical order. The framework of flow decomposition is used to show the class of regular-order decode-forward index-coding schemes is computable. A shifting algorithm finds encoding/decoding schemes in ${text{P}}(|mathcal{N}|){text{EXP}}(|mathcal{S}|)$ time that achieve desired rate-vectors, where $mathcal{N}$ is the set of nodes and $mathcal{S} subseteq mathcal{N}$ is the subset of source nodes in the channel.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117300146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISIT44484.2020.9174492
Fangwei Ye, Hyunghoon Cho, S. Rouayheb
The growing availability of personal genomics services comes with increasing concerns for genomic privacy. Individuals may wish to withhold sensitive genotypes that contain critical health-related information when sharing their data with such services. A straightforward solution that masks only the sensitive genotypes does not ensure privacy due to the correlation structure within the genome. Here, we develop an informationtheoretic mechanism for masking sensitive genotypes, which ensures no information about the sensitive genotypes is leaked. We also propose an efficient algorithmic implementation of our mechanism for genomic data governed by hidden Markov models. Our work is a step towards more rigorous control of privacy in genomic data sharing.
{"title":"Mechanisms for Hiding Sensitive Genotypes with Information-Theoretic Privacy","authors":"Fangwei Ye, Hyunghoon Cho, S. Rouayheb","doi":"10.1109/ISIT44484.2020.9174492","DOIUrl":"https://doi.org/10.1109/ISIT44484.2020.9174492","url":null,"abstract":"The growing availability of personal genomics services comes with increasing concerns for genomic privacy. Individuals may wish to withhold sensitive genotypes that contain critical health-related information when sharing their data with such services. A straightforward solution that masks only the sensitive genotypes does not ensure privacy due to the correlation structure within the genome. Here, we develop an informationtheoretic mechanism for masking sensitive genotypes, which ensures no information about the sensitive genotypes is leaked. We also propose an efficient algorithmic implementation of our mechanism for genomic data governed by hidden Markov models. Our work is a step towards more rigorous control of privacy in genomic data sharing.","PeriodicalId":159311,"journal":{"name":"2020 IEEE International Symposium on Information Theory (ISIT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128319846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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