We revisit the notion of deniability in quantum key exchange (QKE), a topic that remains largely unexplored. In the only work on this subject by Donald Beaver, it is argued that QKE is not necessarily deniable due to an eavesdropping attack that limits key equivocation. We provide more insight into the nature of this attack and how it extends to other constructions such as QKE obtained from uncloneable encryption. We then adopt the framework for quantum authenticated key exchange, developed by , and extend it to introduce the notion of coercer-deniable QKE, formalized in terms of the indistinguishability of real and fake coercer views. Next, we apply results from a recent work by Arrazola and Scarani on covert quantum communication to establish a connection between covert QKE and deniability. We propose DC-QKE, a simple deniable covert QKE protocol, and prove its deniability via a reduction to the security of covert QKE. Finally, we consider how entanglement distillation can be used to enable information-theoretically deniable protocols for QKE and tasks beyond key exchange.
To the best of our knowledge, the only work related to deniability in QKE is a single paper by Beaver @cite_32 , in which the author suggests a negative result arguing that existing QKE schemes are not necessarily deniable.
@cite_32
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We show that claims of perfect security for keys produced by quantum key exchange (QKE) are limited to privacy and integrity. Unlike a one-time pad, QKE does not necessarily enable Sender and Receiver to pretend later to have established a different key. This result is puzzling in light of Mayers' No-Go theorem showing the impossibility of quantum bit commitment. But even though a simple and intuitive application of Mayers' protocol transformation appears sufficient to provide deniability (else QBC would be possible), we show several reasons why such conclusions are ill-founded. Mayers' transformation arguments, while sound for QBC, are insufficient to establish deniability in QKE. Having shed light on several unadvertised pitfalls, we then provide a candidate deniable QKE protocol. This itself indicates further shortfalls in current proof techniques, including reductions that preserve privacy but fail to preserve deniability. In sum, purchasing undeniability with an off-the-shelf QKE protocol is significantly more expensive and dangerous than the mere optic fiber for which perfect security is advertised. We extend the definitional work of Dwork,Naor and Sahai from deniable authentication to deniable key-exchange protocols. We then use these definitions to prove the deniability features of SKEME and SIGMA, two natural and efficient protocols which serve as basis for the Internet Key Exchange (IKE)protocol.SKEME is an encryption-based protocol for which we prove full deniability based on the plaintext awareness of the underlying encryption scheme. Interestingly SKEME's deniability is possibly the first "natural" application which essentially requires plaintext awareness (until now this notion has been mainly used as a tool for proving chosen-ciphertext security).SIGMA, on the other hand,uses non-repudiable signatures for authentication and hence cannot be proven to be fully deniable. Yet we are able to prove a weaker, but meaningful, "partial deniability" property: a party may not be able to deny that it was "alive" at some point in time but can fully deny the contents of its communications and the identity of its interlocutors.We remark that the deniability of SKEME and SIGMA holds in a concurrent setting and does not essentially rely on the random oracle model. We consider most of the known classes of valid inequalities for the graphical travelling salesman polyhedron and compute the worst-case improvement resulting from their addition to the subtour polyhedron. For example, we show that the comb inequalities cannot improve the subtour bound by a factor greater than 10 9. The corresponding factor for the class of clique tree inequalities is 8 7, while it is 4 3 for the path configuration inequalities. In the wake of recent revelations of mass government surveillance, secure messaging protocols have come under renewed scrutiny. A widespread weakness of existing solutions is the lack of strong deniability properties that allow users to plausibly deny sending messages or participating in conversations if the security of their communications is later compromised. Deniable authenticated key exchanges (DAKEs), the cryptographic protocols responsible for providing deniability in secure messaging applications, cannot currently provide all desirable properties simultaneously. We introduce two new DAKEs with provable security and deniability properties in the Generalized Universal Composability framework. Our primary contribution is the introduction of Spawn, the first non-interactive DAKE that offers forward secrecy and achieves deniability against both offline and online judges; Spawn can be used to improve the deniability properties of the popular TextSecure secure messaging application. We also introduce an interactive dual-receiver cryptosystem that can improve the performance of the only existing interactive DAKE with competitive security properties. To encourage adoption, we implement and evaluate the performance of our schemes while relying solely on standard-model assumptions. We identify a trade-off between robustness and accuracy that serves as a guiding principle in the design of defenses against adversarial examples. Although this problem has been widely studied empirically, much remains unknown concerning the theory underlying this trade-off. In this work, we decompose the prediction error for adversarial examples (robust error) as the sum of the natural (classification) error and boundary error, and provide a differentiable upper bound using the theory of classification-calibrated loss, which is shown to be the tightest possible upper bound uniform over all probability distributions and measurable predictors. Inspired by our theoretical analysis, we also design a new defense method, TRADES, to trade adversarial robustness off against accuracy. Our proposed algorithm performs well experimentally in real-world datasets. The methodology is the foundation of our entry to the NeurIPS 2018 Adversarial Vision Challenge in which we won the 1st place out of 2,000 submissions, surpassing the runner-up approach by @math in terms of mean @math perturbation distance. Prior work has established that all problems in NP admit classical zero-knowledge proof systems, and under reasonable hardness assumptions for quantum computations, these proof systems can be made secure against quantum attacks. We prove a result representing a further quantum generalization of this fact, which is that every problem in the complexity class QMA has a quantum zero-knowledge proof system. More specifically, assuming the existence of an unconditionally binding and quantum computationally concealing commitment scheme, we prove that every problem in the complexity class QMA has a quantum interactive proof system that is zero-knowledge with respect to efficient quantum computations. Our QMA proof system is sound against arbitrary quantum provers, but only requires an honest prover to perform polynomial-time quantum computations, provided that it holds a quantum witness for a given instance of the QMA problem under consideration. We present a technique for proving the security of quantum-key-distribution (QKD) protocols. It is based on direct information-theoretic arguments and thus also applies if no equivalent entanglement purification scheme can be found. Using this technique, we investigate a general class of QKD protocols with one-way classical post-processing. We show that, in order to analyze the full security of these protocols, it suffices to consider collective attacks. Indeed, we give new lower and upper bounds on the secret-key rate which only involve entropies of two-qubit density operators and which are thus easy to compute. As an illustration of our results, we analyze the Bennett-Brassard 1984, the six-state, and the Bennett 1992 protocols with one-way error correction and privacy amplification. Surprisingly, the performance of these protocols is increased if one of the parties adds noise to the measurement data before the error correction. In particular, this additional noise makes the protocols more robust against noise in the quantum channel. This paper is concerned with the problem of recovering a finite, deterministic time series from observations that are corrupted by additive, independent noise. A distinctive feature of this problem is that the available data exhibit long-range dependence and, as a consequence, existing statistical theory and methods are not readily applicable. This paper gives an analysis of the denoising problem that extends recent work of Lalley, but begins from first principles. Both positive and negative results are established. The positive results show that denoising is possible under somewhat restrictive conditions on the additive noise. The negative results show that, under more general conditions on the noise, no procedure can recover the underlying deterministic series. This paper proposes a new mechanism for combinatorial assignment—for example, assigning schedules of courses to students—based on an approximation to competitive equilibrium from equal incomes (CEEI) in which incomes are unequal but arbitrarily close together. The main technical result is an existence theorem for approximate CEEI. The mechanism is approximately efficient, satisfies two new criteria of outcome fairness, and is strategyproof in large markets. Its performance is explored on real data, and it is compared to alternatives from theory and practice: all other known mechanisms are either unfair ex post or manipulable even in large markets, and most are both manipulable and unfair. Previous investigations into the validity of acceptability judgment data have focused almost exclusively on type I errors (or false positives) because of the consequences of such errors for syntactic theories (Sprouse & Almeida 2012; 2013). The current study complements these previous studies by systematically investigating the type II error rate (false negatives), or equivalently, the statistical power , of a wide cross-section of possible acceptability judgment experiments. Though type II errors have historically been assumed to be less costly than type I errors, the dynamics of scientific publishing mean that high type II error rates (i.e., studies with low statistical power) can lead to increases in type I error rates in a given field of study. We present a set of experiments and resampling simulations to estimate statistical power for four tasks (forced-choice, Likert scale, magnitude estimation, and yes-no), 50 effect sizes instantiated by real phenomena, sample sizes from 5 to 100 participants, and two approaches to statistical analysis (null hypothesis and Bayesian). Our goals are twofold (i) to provide a fuller picture of the status of acceptability judgment data in syntax, and (ii) to provide detailed information that syntacticians can use to design and evaluate the sensitivity of acceptability judgment experiments in their own research. Many KDD systems incorporate an implicit or explicit preference for simpler models, but this use of “Occam‘s razor” has been strongly criticized by several authors (e.g., Schaffer, 1993s Webb, 1996). This controversy arises partly because Occam‘s razor has been interpreted in two quite different ways. The first interpretation (simplicity is a goal in itself) is essentially correct, but is at heart a preference for more comprehensible models. The second interpretation (simplicity leads to greater accuracy) is much more problematic. A critical review of the theoretical arguments for and against it shows that it is unfounded as a universal principle, and demonstrably false. A review of empirical evidence shows that it also fails as a practical heuristic. This article argues that its continued use in KDD risks causing significant opportunities to be missed, and should therefore be restricted to the comparatively few applications where it is appropriate. The article proposes and reviews the use of domain constraints as an alternative for avoiding overfitting, and examines possible methods for handling the accuracy–comprehensibility trade-off. We revisit the definitions of zero-knowledge in the Common Reference String (CRS) model and the Random Oracle (RO) model. We argue that even though these definitions syntactically mimic the standard zero-knowledge definition, they loose some of its spirit. In particular, we show that there exist a specific natural security property that is not captured by these definitions. This is the property of deniability. We formally define the notion of deniable zero-knowledge in these models and investigate the possibility of achieving it. Our results are different for the two models: In this paper we give a new sufficient condition for a general stability of Kronecker coefficients, which we call it additive stability. It was motivated by a recent talk of J. Stembridge at the conference in honor of Richard P. Stanley's 70th birthday, and it is based on work of the author on discrete tomography along the years. The main contribution of this paper is the discovery of the connection between additivity of integer matrices and stability of Kronecker coefficients. Additivity, in our context, is a concept from discrete tomography. Its advantage is that it is very easy to produce lots of examples of additive matrices and therefore of new instances of stability properties. We also show that Stembridge's hypothesis and additivity are closely related, and prove that all stability properties of Kronecker coefficients discovered before fit into additive stability. Incorporating encoding-decoding nets with adversarial nets has been widely adopted in image generation tasks. We observe that the state-of-the-art achievements were obtained by carefully balancing the reconstruction loss and adversarial loss, and such balance shifts with different network structures, datasets, and training strategies. Empirical studies have demonstrated that an inappropriate weight between the two losses may cause instability, and it is tricky to search for the optimal setting, especially when lacking prior knowledge on the data and network. This paper gives the first attempt to relax the need of manual balancing by proposing the concept of , where a novel network structure is designed that explicitly disentangles the backpropagation paths of the two losses. Experimental results demonstrate the effectiveness, robustness, and generality of the proposed method. The other contribution of the paper is the design of a new evaluation metric to measure the image quality of generative models. We propose the so-called (NRDS), which introduces the idea of relative comparison, rather than providing absolute estimates like existing metrics. Forty years ago, Wiesner proposed using quantum states to create money that is physically impossible to counterfeit, something that cannot be done in the classical world. However, Wiesner's scheme required a central bank to verify the money, and the question of whether there can be unclonable quantum money that anyone can verify has remained open since. One can also ask a related question, which seems to be new: can quantum states be used as copy-protected programs, which let the user evaluate some function f, but not create more programs for f? This paper tackles both questions using the arsenal of modern computational complexity. Our main result is that there exist quantum oracles relative to which publicly-verifiable quantum money is possible, and any family of functions that cannot be efficiently learned from its input-output behavior can be quantumly copy-protected. This provides the first formal evidence that these tasks are achievable. The technical core of our result is a "Complexity-Theoretic No-Cloning Theorem," which generalizes both the standard No-Cloning Theorem and the optimality of Grover search, and might be of independent interest. Our security argument also requires explicit constructions of quantum t-designs. Moving beyond the oracle world, we also present an explicit candidate scheme for publicly-verifiable quantum money, based on random stabilizer states; as well as two explicit schemes for copy-protecting the family of point functions. We do not know how to base the security of these schemes on any existing cryptographic assumption. (Note that without an oracle, we can only hope for security under some computational assumption.) We investigate a general class of quantum key distribution (QKD) protocols using one-way classical communication. We show that full security can be proven by considering only collective attacks. We derive computable lower and upper bounds on the secret-key rate of those QKD protocols involving only entropies of two-qubit density operators. As an illustration of our results, we determine new bounds for the Bennett-Brassard 1984, the 6-state, and the Bennett 1992 protocols. We show that in all these cases the first classical processing that the legitimate partners should apply consists in adding noise. Authorship analysis by means of textual features is an important task in linguistic studies. We employ complex networks theory to tackle this disputed problem. In this work, we focus on some measurable quantities of word co-occurrence network of each book for authorship characterization. Based on the network features, attribution probability is defined for authorship identification. Furthermore, two scaling exponents, q-parameter and α-exponent, are combined to classify personal writing style with acceptable high resolution power. The q-parameter, generally known as the nonextensivity measure, is calculated for degree distribution and the α-exponent comes from a power law relationship between number of links and number of nodes in the co-occurrence network constructed for different books written by each author. The applicability of the presented method is evaluated in an experiment with thirty six books of five Persian litterateurs. Our results show high accuracy rate in authorship attribution. Many real-world knowledge-based systems must deal with information coming from different sources that invariably leads to incompleteness, overspecification, or inherently uncertain content. The presence of these varying levels of uncertainty doesn't mean that the information is worthless --- rather, these are hurdles that the knowledge engineer must learn to work with. In this paper, we continue work on an argumentation-based framework that extends the well-known Defeasible Logic Programming (DeLP) language with probabilistic uncertainty, giving rise to the Defeasible Logic Programming with Presumptions and Probabilistic Environments (DeLP3E) model. Our prior work focused on the problem of belief revision in DeLP3E, where we proposed a non-prioritized class of revision operators called AFO (Annotation Function-based Operators) to solve this problem. In this paper, we further study this class and argue that in some cases it may be desirable to define revision operators that take quantitative aspects into account, such as how the probabilities of certain literals or formulas of interest change after the revision takes place. To the best of our knowledge, this problem has not been addressed in the argumentation literature to date. We propose the QAFO (Quantitative Annotation Function-based Operators) class of operators, a subclass of AFO, and then go on to study the complexity of several problems related to their specification and application in revising knowledge bases. Finally, we present an algorithm for computing the probability that a literal is warranted in a DeLP3E knowledge base, and discuss how it could be applied towards implementing QAFO-style operators that compute approximations rather than exact operations. Complementarity restricts the accuracy with which incompatible quantum observables can be jointly measured. Despite popular conception, the Heisenberg uncertainty relation does not quantify this principle. We report the experimental verification of universally valid complementarity relations, including an improved relation derived here. We exploit Einstein-Poldolsky-Rosen correlations between two photonic qubits to jointly measure incompatible observables of one. The product of our measurement inaccuracies is low enough to violate the widely used, but not universally valid, Arthurs-Kelly relation. Abstract In this paper, we aim at analyzing the approximation abilities of shallow networks in reproducing kernel Hilbert spaces (RKHSs). We prove that there is a probability measure such that the achievable lower bound for approximating by shallow nets can be realized for all functions in balls of reproducing kernel Hilbert space with high probability, which is different with the classical minimax approximation error estimates. This result together with the existing approximation results for deep nets shows the limitations for shallow nets and provides a theoretical explanation on why deep nets perform better than shallow nets.