1,496 research outputs found
Markovian Processes for Quantitative Information Leakage
Quantification of information leakage is a successful approach for evaluating the security of a system. It models the system to be analyzed as a channel with the secret as the input and an output as observable by the attacker as the output, and applies information theory to quantify the amount of information transmitted through such channel, thus effectively quantifying how many bits of the secret can be inferred by the attacker by analyzing the system’s output.Channels are usually encoded as matrices of conditional probabilities, known as channel matrices. Such matrices grow exponentially in the size of the secret and observables, are cumbersome to compute and store, encode both the behavior of the system and assumptions about the attacker, and assume an input-output behavior of the system. For these reasons we propose to model the system-attacker scenario with Markovian models.We show that such models are more compact and treatable than channel matrices. Also, they clearly separate the behavior of the system from the assumptions about the attacker, and can represent even non-terminating behavior in a finite model. We provide techniques and algorithms to model and analyze both deterministic and randomized processes with Markovian models and to compute their informationleakage for a very general model of attacker. We present the QUAIL tool that automates such analysis and is able to compute the information leakage of an imperative WHILE language. Finally, we show how to use QUAIL to analyze some interesting cases of secret-dependent protocols
Markovian Processes for Quantitative Information Leakage
Quantification of information leakage is a successful approach for evaluating the security of a system. It models the system to be analyzed as a channel with the secret as the input and an output as observable by the attacker as the output, and applies information theory to quantify the amount of information transmitted through such channel, thus effectively quantifying how many bits of the secret can be inferred by the attacker by analyzing the system’s output.Channels are usually encoded as matrices of conditional probabilities, known as channel matrices. Such matrices grow exponentially in the size of the secret and observables, are cumbersome to compute and store, encode both the behavior of the system and assumptions about the attacker, and assume an input-output behavior of the system. For these reasons we propose to model the system-attacker scenario with Markovian models.We show that such models are more compact and treatable than channel matrices. Also, they clearly separate the behavior of the system from the assumptions about the attacker, and can represent even non-terminating behavior in a finite model. We provide techniques and algorithms to model and analyze both deterministic and randomized processes with Markovian models and to compute their informationleakage for a very general model of attacker. We present the QUAIL tool that automates such analysis and is able to compute the information leakage of an imperative WHILE language. Finally, we show how to use QUAIL to analyze some interesting cases of secret-dependent protocols
Quantifying Information Leakage of Randomized Protocols
International audienceThe quantification of information leakage provides a quantitative evaluation of the security of a system. We propose the usage of Markovian processes to model and analyze the information leakage of deterministic and probabilistic systems. We show that this method generalizes the lattice of information approach and is a natural framework for modeling refined attackers capable to observe the internal behavior of the system. We also use our method to obtain an algorithm for the computation of channel capacity from our Markovian models. Finally, we show how to use the method to analyze timed and non-timed attacks on the Onion Routing protocol
Subspace confinement : how good is your qubit?
The basic operating element of standard quantum computation is the qubit, an isolated two-level system that can be accurately controlled, initialized and measured. However, the majority of proposed physical architectures for quantum computation are built from systems that contain much more complicated Hilbert space structures. Hence, defining a qubit requires the identification of an appropriate controllable two-dimensional sub-system. This prompts the obvious question of how well a qubit, thus defined, is confined to this subspace, and whether we can experimentally quantify the potential leakage into states outside the qubit subspace. We demonstrate how subspace leakage can be characterized using minimal theoretical assumptions by examining the Fourier spectrum of the oscillation experiment
Optimal strategy for a single-qubit gate and trade-off between opposite types of decoherence
We study reliable quantum information processing (QIP) under two different
types of environment. First type is Markovian exponential decay, and the
appropriate elementary strategy of protection of qubit is to apply fast gates.
The second one is strongly non-Markovian and occurs solely during operations on
the qubit. The best strategy is then to work with slow gates. If the two types
are both present, one has to optimize the speed of gate. We show that such a
trade-off is present for a single-qubit operation in a semiconductor quantum
dot implementation of QIP, where recombination of exciton (qubit) is Markovian,
while phonon dressing gives rise to the non-Markovian contribution.Comment: 4 pages, 1 figure; final versio
Optimal Control for Open Quantum Systems: Qubits and Quantum Gates
This article provides a review of recent developments in the formulation and
execution of optimal control strategies for the dynamics of quantum systems. A
brief introduction to the concept of optimal control, the dynamics of of open
quantum systems, and quantum information processing is followed by a
presentation of recent developments regarding the two main tasks in this
context: state-specific and state-independent optimal control. For the former,
we present an extension of conventional theory (Pontryagin's principle) to
quantum systems which undergo a non-Markovian time-evolution. Owing to its
importance for the realization of quantum information processing, the main body
of the review, however, is devoted to state-independent optimal control. Here,
we address three different approaches: an approach which treats dissipative
effects from the environment in lowest-order perturbation theory, a general
method based on the time--evolution superoperator concept, as well as one based
on the Kraus representation of the time-evolution superoperator. Applications
which illustrate these new methods focus on single and double qubits (quantum
gates) whereby the environment is modeled either within the Lindblad equation
or a bath of bosons (spin-boson model). While these approaches are widely
applicable, we shall focus our attention to solid-state based physical
realizations, such as semiconductor- and superconductor-based systems. While an
attempt is made to reference relevant and representative work throughout the
community, the exposition will focus mainly on work which has emerged from our
own group.Comment: 27 pages, 18 figure
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