A Verified Information-Flow Architecture

SAFE is a clean-slate design for a highly secure computer system, with pervasive mechanisms for tracking and limiting information flows. At the lowest level, the SAFE hardware supports fine-grained programmable tags, with efficient and flexible propagation and combination of tags as instructions are executed. The operating system virtualizes these generic facilities to present an information-flow abstract machine that allows user programs to label sensitive data with rich confidentiality policies. We present a formal, machine-checked model of the key hardware and software mechanisms used to dynamically control information flow in SAFE and an end-to-end proof of noninterference for this model. We use a refinement proof methodology to propagate the noninterference property of the abstract machine down to the concrete machine level. We use an intermediate layer in the refinement chain that factors out the details of the information-flow control policy and devise a code generator for compiling such information-flow policies into low-level monitor code. Finally, we verify the correctness of this generator using a dedicated Hoare logic that abstracts from low-level machine instructions into a reusable set of verified structured code generators

Cloud Computing in the Quantum Era

Cloud computing has become the prominent technology of this era. Its elasticity, dynamicity, availability, heterogeneity, and pay as you go pricing model has attracted several companies to migrate their businesses' services into the cloud. This gives them more time to focus solely on their businesses and reduces the management and backup overhead leveraging the flexibility of cloud computing. On the other hand, quantum technology is developing very rapidly. Experts are expecting to get an efficient quantum computer within the next decade. This has a significant impact on several sciences including cryptography, medical research, and other fields. This paper analyses the reciprocal impact of quantum technology on cloud computing and vice versa

Almost universal codes for fading wiretap channels

We consider a fading wiretap channel model where the transmitter has only statistical channel state information, and the legitimate receiver and eavesdropper have perfect channel state information. We propose a sequence of non-random lattice codes which achieve strong secrecy and semantic security over ergodic fading channels. The construction is almost universal in the sense that it achieves the same constant gap to secrecy capacity over Gaussian and ergodic fading models.Comment: 5 pages, to be submitted to IEEE International Symposium on Information Theory (ISIT) 201

Billiard Dynamics: An Updated Survey with the Emphasis on Open Problems

This is an updated and expanded version of our earlier survey article \cite{Gut5}. Section $\S 1$ introduces the subject matter. Sections $\S 2 - \S 4$ expose the basic material following the paradigm of elliptic, hyperbolic and parabolic billiard dynamics. In section $\S 5$ we report on the recent work pertaining to the problems and conjectures exposed in the survey \cite{Gut5}. Besides, in section $\S 5$ we formulate a few additional problems and conjectures. The bibliography has been updated and considerably expanded

Statically checking confidentiality via dynamic labels

This paper presents a new approach for verifying confidentiality for programs, based on abstract interpretation. The framework is formally developed and proved correct in the theorem prover PVS. We use dynamic labeling functions to abstractly interpret a simple programming language via modification of security levels of variables. Our approach is sound and compositional and results in an algorithm for statically checking confidentiality

Mean Field Equilibrium in Dynamic Games with Complementarities

We study a class of stochastic dynamic games that exhibit strategic complementarities between players; formally, in the games we consider, the payoff of a player has increasing differences between her own state and the empirical distribution of the states of other players. Such games can be used to model a diverse set of applications, including network security models, recommender systems, and dynamic search in markets. Stochastic games are generally difficult to analyze, and these difficulties are only exacerbated when the number of players is large (as might be the case in the preceding examples). We consider an approximation methodology called mean field equilibrium to study these games. In such an equilibrium, each player reacts to only the long run average state of other players. We find necessary conditions for the existence of a mean field equilibrium in such games. Furthermore, as a simple consequence of this existence theorem, we obtain several natural monotonicity properties. We show that there exist a "largest" and a "smallest" equilibrium among all those where the equilibrium strategy used by a player is nondecreasing, and we also show that players converge to each of these equilibria via natural myopic learning dynamics; as we argue, these dynamics are more reasonable than the standard best response dynamics. We also provide sensitivity results, where we quantify how the equilibria of such games move in response to changes in parameters of the game (e.g., the introduction of incentives to players).Comment: 56 pages, 5 figure