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The formalisation of security properties for computer systems raises the problem of overcoming also in a formal setting the classical view according to which confidentiality is an absolute property stating the complete absence of ...
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The formalisation of security properties for computer systems raises the problem of overcoming also in a formal setting the classical view according to which confidentiality is an absolute property stating the complete absence of any unauthorised disclosure of information. In this paper, we present two formal models in which the notion of noninterference, which is at the basis of a large variety of security properties defined in the recent literature, is approximated. To this aim, the definition of indistinguishability of process behaviour is replaced by a similarity notion, which introduces a quantitative measure ε of the behavioural difference among processes. The first model relies on a programming paradigm called Probabilistic Concurrent Constraint Programming, while the second one is presented in the setting of a probabilistic process algebra. In both models, appropriate notions of distance provide information (the ε) on the security level of the system at hand, in terms of the capability of an external observer of identifying illegal interferences.
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The aims of these lecture notes are two-fold: (i) we inves tigate the relation between the operational semantics of probabilistic programming languages and Discrete Time Markov Chains (DTMCs), and (ii) we present a framework for p...
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The aims of these lecture notes are two-fold: (i) we inves tigate the relation between the operational semantics of probabilistic programming languages and Discrete Time Markov Chains (DTMCs), and (ii) we present a framework for probabilistic program analysis which is inspired by the classical Abstract Interpretation framework by Cousot & Cousot and which we introduced as Probabilistic Abstract Interpreta tion (PAI) in [1]. The link between programming languages and DTMCs is the construction of a so-called Linear Operator semantics (LOS) in a syntax-directed or compositional way. The main element in this construc tion is the use of tensor product to combine information about different aspects of a program. Although this inevitably results in a combinato rial explosion of the size of the semantics of program, the PAI approach allows us to keep some control and to obtain reasonably sized abstract models.
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The aims of these lecture notes are two-fold: (i) we investigate the relation between the operational semantics of probabilistic programming languages and Discrete Time Markov Chains (DTMCs), and (ii) we present a framework for pr...
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The aims of these lecture notes are two-fold: (i) we investigate the relation between the operational semantics of probabilistic programming languages and Discrete Time Markov Chains (DTMCs), and (ii) we present a framework for probabilistic program analysis which is inspired by the classical abstract Interpretation framework by Cousot & Cousot and which we introduced as Probabilistic abstract Interpretation (PAI) in [1]. The link between programming languages and DTMCs is the construction of a so-called Linear Operator semantics (LOS) in a syntax-directed or compositional way. The main element in this construction is the use of tensor product to combine information about different aspects of a program. Although this inevitably results in a combinatorial explosion of the size of the semantics of program, the PAI approach allows us to keep some control and to obtain reasonably sized abstract models.
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In this paper we investigate how to optimally invest in cybersecurity controls. We are particularly interested in examining cases where the organization suffers from an underinvestment problem or inefficient spending on cybersecur...
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In this paper we investigate how to optimally invest in cybersecurity controls. We are particularly interested in examining cases where the organization suffers from an underinvestment problem or inefficient spending on cybersecurity. To this end, we first model the cybersecurity environment of an organization. We then model non-cooperative cybersecurity control-games between the defender which abstracts all defense mechanisms of the organization and the attacker which can exploit different vulnerabilities at different network locations. To implement our methodology we use the SANS Top 20 Critical Security Controls and the 2011 CWE/SANS top 25 most dangerous software errors. Based on the profile of an organization, which forms its preferences in terms of indirect costs, its concerns about different kinds of threats and the importance of the assets given their associated risks we derive the Nash Equilibria of a series of control-games. These game solutions are then handled by optimization techniques, in particular multi-objective, multiple choice Knapsack to determine the optimal cybersecurity investment. Our methodology provides security effective and cost efficient solutions especially against commodity attacks. We believe our work can be used to advise security managers on how they should spend an available cybersecurity budget given their organization profile.
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Coordination languages are intended to simplify the development of complex software systems by separating the coordination aspects of an application from its computational aspects. Coordination refers to the ways the independent a...
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Coordination languages are intended to simplify the development of complex software systems by separating the coordination aspects of an application from its computational aspects. Coordination refers to the ways the independent active pieces of a program (e.g. a process, a task, a thread, etc.) communicate and synchronise with each other. We review various approaches to introducing probabilistic or stochastic features in coordination languages. The main objective of such a study is to develop a semantic basis for a quantitative analysis of systems of interconnected or interacting components, which allows us to address not only the functional (qualitative) aspects of a system behaviour but also its non-functional aspects, typically considered in the realm of performance modelling and evaluation.
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Coordination languages are intended to simplify the development of complex software systems by separating the coordination aspects of an application from its computational aspects. Coordination refers to the ways the independent a...
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Coordination languages are intended to simplify the development of complex software systems by separating the coordination aspects of an application from its computational aspects. Coordination refers to the ways the independent active pieces of a program (e.g. a process, a task, a thread, etc.) communicate and synchronise with each other. We review various approaches to introducing probabilistic or stochastic features in coordination languages. The main objective of such a study is to develop a semantic basis for a quantitative analysis of systems of interconnected or interacting components, which allows us to address not only the functional (qualitative) aspects of a system behaviour but also its non-functional aspects, typically considered in the realm of performance modelling and evaluation.
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The Chemical Abstract Machine (CHAM) of Berry and Boudol provides a commonly accepted, uniform framework for describing the operational semantics of various process calculi and languages, such as for example CCS, the π calculus a...
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The Chemical Abstract Machine (CHAM) of Berry and Boudol provides a commonly accepted, uniform framework for describing the operational semantics of various process calculi and languages, such as for example CCS, the π calculus and coordination languages like Linda. In its original form the CHAM is purely non-deterministic and thus only describes what reactions are possible but not how long it will take (in the average) before a certain reaction takes place or its probability. Such quantitative information is however often vital for “real world” applications such as systems biology or performance analysis. We propose a probabilistic version of the CHAM. We then define a linear operator semantics for the probabilistic CHAM which exploits a tensor product representation for distributions over possible solutions. Based on this we propose a novel approach towards comparing the expressive power of different calculi via their encoding in the probabilistic CHAM. We illustrate our approach by comparing the expressiveness of various Linda Languages.
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摘要 :
The Chemical Abstract Machine (CHAM) of Berry and Boudol provides a commonly accepted, uniform framework for describing the operational semantics of various process calculi and languages, such as for example CCS, the π calculus a...
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The Chemical Abstract Machine (CHAM) of Berry and Boudol provides a commonly accepted, uniform framework for describing the operational semantics of various process calculi and languages, such as for example CCS, the π calculus and coordination languages like Linda. In its original form the CHAM is purely non-deterministic and thus only describes what reactions are possible but not how long it will take (in the average) before a certain reaction takes place or its probability. Such quantitative information is however often vital for "real world" applications such as systems biology or performance analysis. We propose a probabilistic version of the CHAM. We then define a linear operator semantics for the probabilistic CHAM which exploits a tensor product representation for distributions over possible solutions. Based on this we propose a novel approach towards comparing the expressive power of different calculi via their encoding in the probabilistic CHAM. We illustrate our approach by comparing the expressiveness of various Linda Languages.
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A safe abstraction is presented for a restricted form of term graph rewriting. This abstraction can be seen as a formalisation of the rewrite system employed by the strictness analyser in the Concurrent Clean compiler. Programs wr...
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A safe abstraction is presented for a restricted form of term graph rewriting. This abstraction can be seen as a formalisation of the rewrite system employed by the strictness analyser in the Concurrent Clean compiler. Programs written in a core functional language are interpreted as graph rewriting systems using a form of equational term graph rewriting due to Ariola and Arvind. Abstract graphs are defined by extending the signature of ordinary graphs and it is shown how to extend a rewriting system on ordinary graphs to one on abstract graphs. An abstraction relation between abstract graphs is used to define a notion of safety with respect to a variant of Ariola and Arvind's direct approximation semantics, and this notion of safety is shown to be adequate for strictness analysis. Abstract reduction is defined as the union of the extended rewrite system with additional 'heuristic' reductions and shown to be safe.
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We address the challenges arising from enforcing security policies in an imperfect world - in a system involving humans, a determined attacker always has a chance of circumventing any security. We motivate our approach by two exam...
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We address the challenges arising from enforcing security policies in an imperfect world - in a system involving humans, a determined attacker always has a chance of circumventing any security. We motivate our approach by two examples: an on-line auction house; and a airport security system. In our work, security policies are enforced using a probabilistic aspect-oriented approach; policies are combined using a rich set of policy composition operators. We present the examples using a process-based language in which processes and local data are distributed across a number of locations (network addresses). The formal definition of the language gives rise to Markov Decision Processes.
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