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Authentication over Noisy Channels
TL;DR: An authentication counterpart of Wyner's study of the wiretap channel is developed, in which shared key information is used to provide simultaneous protection against both types of attacks and fundamental limits on message authentication over noisy channels are fully characterized.
Abstract: In this work, message authentication over noisy channels is studied. The model developed in this paper is the authentication theory counterpart of Wyner's wiretap channel model. Two types of opponent attacks, namely impersonation attacks and substitution attacks, are investigated for both single message and multiple message authentication scenarios. For each scenario, information theoretic lower and upper bounds on the opponent's success probability are derived. Remarkably, in both scenarios, lower and upper bounds are shown to match, and hence the fundamental limit of message authentication over noisy channels is fully characterized. The opponent's success probability is further shown to be smaller than that derived in the classic authentication model in which the channel is assumed to be noiseless. These results rely on a proposed novel authentication scheme in which key information is used to provide simultaneous protection again both types of attacks.
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TL;DR: A comprehensive review of the domain of physical layer security in multiuser wireless networks, with an overview of the foundations dating back to the pioneering work of Shannon and Wyner on information-theoretic security and observations on potential research directions in this area.
Abstract: This paper provides a comprehensive review of the domain of physical layer security in multiuser wireless networks. The essential premise of physical layer security is to enable the exchange of confidential messages over a wireless medium in the presence of unauthorized eavesdroppers, without relying on higher-layer encryption. This can be achieved primarily in two ways: without the need for a secret key by intelligently designing transmit coding strategies, or by exploiting the wireless communication medium to develop secret keys over public channels. The survey begins with an overview of the foundations dating back to the pioneering work of Shannon and Wyner on information-theoretic security. We then describe the evolution of secure transmission strategies from point-to-point channels to multiple-antenna systems, followed by generalizations to multiuser broadcast, multiple-access, interference, and relay networks. Secret-key generation and establishment protocols based on physical layer mechanisms are subsequently covered. Approaches for secrecy based on channel coding design are then examined, along with a description of inter-disciplinary approaches based on game theory and stochastic geometry. The associated problem of physical layer message authentication is also briefly introduced. The survey concludes with observations on potential research directions in this area.
1,294 citations
Cites background from "Authentication over Noisy Channels"
...The impact of both noise and errors in the channel was taken into account for the first time in [278]....
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Book•
12 Jun 2009TL;DR: Information Theoretic Security surveys the research dating back to the 1970s which forms the basis of applying this technique in modern systems to achieve secrecy for a basic wire-tap channel model as well as for its extensions to multiuser networks.
Abstract: Security is one of the most important issues in communications. Security issues arising in communication networks include confidentiality, integrity, authentication and non-repudiation. Attacks on the security of communication networks can be divided into two basic types: passive attacks and active attacks. An active attack corresponds to the situation in which a malicious actor intentionally disrupts the system. A passive attack corresponds to the situation in which a malicious actor attempts to interpret source information without injecting any information or trying to modify the information; i.e., passive attackers listen to the transmission without modifying it. Information Theoretic Security focuses on confidentiality issues, in which passive attacks are of primary concern. The information theoretic approach to achieving secure communication opens a promising new direction toward solving wireless networking security problems. Compared to contemporary cryptosystems, information theoretic approaches offer advantages such as eliminating the key management issue; are less vulnerable to the man-in-the-middle and achieve provable security that is robust to powerful eavesdroppers possessing unlimited computational resources, knowledge of the communication strategy employed including coding and decoding algorithms, and access to communication systems either through perfect or noisy channels. Information Theoretic Security surveys the research dating back to the 1970s which forms the basis of applying this technique in modern systems. It proceeds to provide an overview of how information theoretic approaches are developed to achieve secrecy for a basic wire-tap channel model as well as for its extensions to multiuser networks. It is an invaluable resource for students and researchers working in network security, information theory and communications.
877 citations
Cites background from "Authentication over Noisy Channels"
...Furthermore, compared to public-key algorithms for key management in hybrid cryptosystems, the information theoretic security approaches are less vulnerable to the man-in-themiddle attack [78, 113, 114, 141, 146, 162, 171] due to the intrinsic randomness shared by terminals....
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TL;DR: This survey introduces the fundamental theories of PHy-security, covering confidentiality and authentication, and provides an overview on the state-of-the-art works on PHY-security technologies that can provide secure communications in wireless systems, along with the discussions on challenges and their proposed solutions.
Abstract: Physical layer security (PHY-security) takes the advantages of channel randomness nature of transmission media to achieve communication confidentiality and authentication. Wiretap coding and signal processing technologies are expected to play vital roles in this new security mechanism. PHY-security has attracted a lot of attention due to its unique features and the fact that our daily life relies heavily on wireless communications for sensitive and private information transmissions. Compared to conventional cryptography that works to ensure all involved entities to load proper and authenticated cryptographic information, PHY-security technologies perform security functions without considering about how those security protocols are executed. In other words, it does not require to implement any extra security schemes or algorithms on other layers above the physical layer. This survey introduces the fundamental theories of PHY-security, covering confidentiality and authentication, and provides an overview on the state-of-the-art works on PHY-security technologies that can provide secure communications in wireless systems, along with the discussions on challenges and their proposed solutions. Furthermore, at the end of this paper, the open issues are identified as our future research directions.
530 citations
TL;DR: This paper provides a review of recent research in the field of physical layer security and an overview of the potential of the physical properties of the radio channel itself to provide communications security.
Abstract: Security in wireless networks has traditionally been considered to be an issue to be addressed separately from the physical radio transmission aspects of wireless systems. However, with the emergence of new networking architectures that are not amenable to traditional methods of secure communication such as data encryption, there has been an increase in interest in the potential of the physical properties of the radio channel itself to provide communications security. Information theory provides a natural framework for the study of this issue, and there has been considerable recent research devoted to using this framework to develop a greater understanding of the fundamental ability of the so-called physical layer to provide security in wireless networks. Moreover, this approach is also suggestive in many cases of coding techniques that can approach fundamental limits in practice and of techniques for other security tasks such as authentication. This paper provides an overview of these developments.
228 citations
TL;DR: An authentication scheme in the framework of hypothesis testing that suits a multiple wiretap channels environment with correlated fading, as is the case of multiple input multiple output (MIMO) systems and/or orthogonal frequency division multiplexing (OFDM) modulation is developed.
Abstract: In a wide band and multipath rich environment, precise channel estimation allows authenticating the source and protecting the integrity of a message at the physical layer without the need of a pre-shared secret key. This allows also a reduction of the burden on the authentication protocols at higher layers. In this paper we develop an authentication scheme in the framework of hypothesis testing that suits a multiple wiretap channels environment with correlated fading, as is the case of multiple input multiple output (MIMO) systems and/or orthogonal frequency division multiplexing (OFDM) modulation. By allowing some degree of correlation among the channels, we formulate the optimal attack strategy for the cases of both single attempt and multiple repeated trials. For the latter scenario, due to the complexity of the optimal solution, we also develop a simpler suboptimal attack strategy. The performance of the proposed methods is evaluated in a MIMO/OFDM scenario and numerical results show the merits of the proposed approaches that can be adopted as a layer one authentication mechanism.
120 citations
Cites background from "Authentication over Noisy Channels"
...However, the presence of both noise and errors in the channel was taken into account for the first time in [5]....
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References
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Book•
01 Jan 1991TL;DR: The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.
Abstract: Preface to the Second Edition. Preface to the First Edition. Acknowledgments for the Second Edition. Acknowledgments for the First Edition. 1. Introduction and Preview. 1.1 Preview of the Book. 2. Entropy, Relative Entropy, and Mutual Information. 2.1 Entropy. 2.2 Joint Entropy and Conditional Entropy. 2.3 Relative Entropy and Mutual Information. 2.4 Relationship Between Entropy and Mutual Information. 2.5 Chain Rules for Entropy, Relative Entropy, and Mutual Information. 2.6 Jensen's Inequality and Its Consequences. 2.7 Log Sum Inequality and Its Applications. 2.8 Data-Processing Inequality. 2.9 Sufficient Statistics. 2.10 Fano's Inequality. Summary. Problems. Historical Notes. 3. Asymptotic Equipartition Property. 3.1 Asymptotic Equipartition Property Theorem. 3.2 Consequences of the AEP: Data Compression. 3.3 High-Probability Sets and the Typical Set. Summary. Problems. Historical Notes. 4. Entropy Rates of a Stochastic Process. 4.1 Markov Chains. 4.2 Entropy Rate. 4.3 Example: Entropy Rate of a Random Walk on a Weighted Graph. 4.4 Second Law of Thermodynamics. 4.5 Functions of Markov Chains. Summary. Problems. Historical Notes. 5. Data Compression. 5.1 Examples of Codes. 5.2 Kraft Inequality. 5.3 Optimal Codes. 5.4 Bounds on the Optimal Code Length. 5.5 Kraft Inequality for Uniquely Decodable Codes. 5.6 Huffman Codes. 5.7 Some Comments on Huffman Codes. 5.8 Optimality of Huffman Codes. 5.9 Shannon-Fano-Elias Coding. 5.10 Competitive Optimality of the Shannon Code. 5.11 Generation of Discrete Distributions from Fair Coins. Summary. Problems. Historical Notes. 6. Gambling and Data Compression. 6.1 The Horse Race. 6.2 Gambling and Side Information. 6.3 Dependent Horse Races and Entropy Rate. 6.4 The Entropy of English. 6.5 Data Compression and Gambling. 6.6 Gambling Estimate of the Entropy of English. Summary. Problems. Historical Notes. 7. Channel Capacity. 7.1 Examples of Channel Capacity. 7.2 Symmetric Channels. 7.3 Properties of Channel Capacity. 7.4 Preview of the Channel Coding Theorem. 7.5 Definitions. 7.6 Jointly Typical Sequences. 7.7 Channel Coding Theorem. 7.8 Zero-Error Codes. 7.9 Fano's Inequality and the Converse to the Coding Theorem. 7.10 Equality in the Converse to the Channel Coding Theorem. 7.11 Hamming Codes. 7.12 Feedback Capacity. 7.13 Source-Channel Separation Theorem. Summary. Problems. Historical Notes. 8. Differential Entropy. 8.1 Definitions. 8.2 AEP for Continuous Random Variables. 8.3 Relation of Differential Entropy to Discrete Entropy. 8.4 Joint and Conditional Differential Entropy. 8.5 Relative Entropy and Mutual Information. 8.6 Properties of Differential Entropy, Relative Entropy, and Mutual Information. Summary. Problems. Historical Notes. 9. Gaussian Channel. 9.1 Gaussian Channel: Definitions. 9.2 Converse to the Coding Theorem for Gaussian Channels. 9.3 Bandlimited Channels. 9.4 Parallel Gaussian Channels. 9.5 Channels with Colored Gaussian Noise. 9.6 Gaussian Channels with Feedback. Summary. Problems. Historical Notes. 10. Rate Distortion Theory. 10.1 Quantization. 10.2 Definitions. 10.3 Calculation of the Rate Distortion Function. 10.4 Converse to the Rate Distortion Theorem. 10.5 Achievability of the Rate Distortion Function. 10.6 Strongly Typical Sequences and Rate Distortion. 10.7 Characterization of the Rate Distortion Function. 10.8 Computation of Channel Capacity and the Rate Distortion Function. Summary. Problems. Historical Notes. 11. Information Theory and Statistics. 11.1 Method of Types. 11.2 Law of Large Numbers. 11.3 Universal Source Coding. 11.4 Large Deviation Theory. 11.5 Examples of Sanov's Theorem. 11.6 Conditional Limit Theorem. 11.7 Hypothesis Testing. 11.8 Chernoff-Stein Lemma. 11.9 Chernoff Information. 11.10 Fisher Information and the Cram-er-Rao Inequality. Summary. Problems. Historical Notes. 12. Maximum Entropy. 12.1 Maximum Entropy Distributions. 12.2 Examples. 12.3 Anomalous Maximum Entropy Problem. 12.4 Spectrum Estimation. 12.5 Entropy Rates of a Gaussian Process. 12.6 Burg's Maximum Entropy Theorem. Summary. Problems. Historical Notes. 13. Universal Source Coding. 13.1 Universal Codes and Channel Capacity. 13.2 Universal Coding for Binary Sequences. 13.3 Arithmetic Coding. 13.4 Lempel-Ziv Coding. 13.5 Optimality of Lempel-Ziv Algorithms. Compression. Summary. Problems. Historical Notes. 14. Kolmogorov Complexity. 14.1 Models of Computation. 14.2 Kolmogorov Complexity: Definitions and Examples. 14.3 Kolmogorov Complexity and Entropy. 14.4 Kolmogorov Complexity of Integers. 14.5 Algorithmically Random and Incompressible Sequences. 14.6 Universal Probability. 14.7 Kolmogorov complexity. 14.9 Universal Gambling. 14.10 Occam's Razor. 14.11 Kolmogorov Complexity and Universal Probability. 14.12 Kolmogorov Sufficient Statistic. 14.13 Minimum Description Length Principle. Summary. Problems. Historical Notes. 15. Network Information Theory. 15.1 Gaussian Multiple-User Channels. 15.2 Jointly Typical Sequences. 15.3 Multiple-Access Channel. 15.4 Encoding of Correlated Sources. 15.5 Duality Between Slepian-Wolf Encoding and Multiple-Access Channels. 15.6 Broadcast Channel. 15.7 Relay Channel. 15.8 Source Coding with Side Information. 15.9 Rate Distortion with Side Information. 15.10 General Multiterminal Networks. Summary. Problems. Historical Notes. 16. Information Theory and Portfolio Theory. 16.1 The Stock Market: Some Definitions. 16.2 Kuhn-Tucker Characterization of the Log-Optimal Portfolio. 16.3 Asymptotic Optimality of the Log-Optimal Portfolio. 16.4 Side Information and the Growth Rate. 16.5 Investment in Stationary Markets. 16.6 Competitive Optimality of the Log-Optimal Portfolio. 16.7 Universal Portfolios. 16.8 Shannon-McMillan-Breiman Theorem (General AEP). Summary. Problems. Historical Notes. 17. Inequalities in Information Theory. 17.1 Basic Inequalities of Information Theory. 17.2 Differential Entropy. 17.3 Bounds on Entropy and Relative Entropy. 17.4 Inequalities for Types. 17.5 Combinatorial Bounds on Entropy. 17.6 Entropy Rates of Subsets. 17.7 Entropy and Fisher Information. 17.8 Entropy Power Inequality and Brunn-Minkowski Inequality. 17.9 Inequalities for Determinants. 17.10 Inequalities for Ratios of Determinants. Summary. Problems. Historical Notes. Bibliography. List of Symbols. Index.
45,034 citations
TL;DR: A theory of secrecy systems is developed on a theoretical level and is intended to complement the treatment found in standard works on cryptography.
Abstract: THE problems of cryptography and secrecy systems furnish an interesting application of communication theory.1 In this paper a theory of secrecy systems is developed. The approach is on a theoretical level and is intended to complement the treatment found in standard works on cryptography.2 There, a detailed study is made of the many standard types of codes and ciphers, and of the ways of breaking them. We will be more concerned with the general mathematical structure and properties of secrecy systems.
8,777 citations
"Authentication over Noisy Channels" refers background in this paper
...Transmission is said to be perfectly secure, if the signal received at the opponent does not provide it with any information aboutM ....
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TL;DR: This paper finds the trade-off curve between R and d, assuming essentially perfect (“error-free”) transmission, and implies that there exists a Cs > 0, such that reliable transmission at rates up to Cs is possible in approximately perfect secrecy.
Abstract: We consider the situation in which digital data is to be reliably transmitted over a discrete, memoryless channel (dmc) that is subjected to a wire-tap at the receiver. We assume that the wire-tapper views the channel output via a second dmc). Encoding by the transmitter and decoding by the receiver are permitted. However, the code books used in these operations are assumed to be known by the wire-tapper. The designer attempts to build the encoder-decoder in such a way as to maximize the transmission rate R, and the equivocation d of the data as seen by the wire-tapper. In this paper, we find the trade-off curve between R and d, assuming essentially perfect (“error-free”) transmission. In particular, if d is equal to Hs, the entropy of the data source, then we consider that the transmission is accomplished in perfect secrecy. Our results imply that there exists a C s > 0, such that reliable transmission at rates up to C s is possible in approximately perfect secrecy.
7,129 citations
"Authentication over Noisy Channels" refers background in this paper
...The source-wiretapper channel is said to be less noisy than the main channel, if for all possibleU that satisfy the above Markov chain relationship, one hasI(U ; Z) > I(U ; Y )....
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...The first one is called animpersonation attack, in which the opponent sendsW ′ to the destination before the source sends anything....
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TL;DR: Given two discrete memoryless channels (DMC's) with a common input, a single-letter characterization is given of the achievable triples where R_{e} is the equivocation rate and the related source-channel matching problem is settled.
Abstract: Given two discrete memoryless channels (DMC's) with a common input, it is desired to transmit private messages to receiver 1 rate R_{1} and common messages to both receivers at rate R_{o} , while keeping receiver 2 as ignorant of the private messages as possible. Measuring ignorance by equivocation, a single-letter characterization is given of the achievable triples (R_{1},R_{e},R_{o}) where R_{e} is the equivocation rate. Based on this channel coding result, the related source-channel matching problem is also settled. These results generalize those of Wyner on the wiretap channel and of Korner-Marton on the broadcast Channel.
3,570 citations
"Authentication over Noisy Channels" refers background in this paper
...We denote the success probability of this attack byPS ....
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...We can see that the perfect secrecy capacity is nonzero unless th wiretapper channel is less noisy than the main channel....
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01 Jan 2011
2,065 citations