The Experts below are selected from a list of 18 Experts worldwide ranked by ideXlab platform
Roberta Gori - One of the best experts on this subject based on the ideXlab platform.
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Code obfuscation against Abstraction refinement attacks
Formal Aspects of Computing, 2018Co-Authors: Roberto Bruni, Roberto Giacobazzi, Roberta GoriAbstract:Code protection technologies require anti reverse engineering transformations to obfuscate programs in such a way that tools and methods for program analysis become ineffective. We introduce the concept of model deformation inducing an effective code obfuscation against attacks performed by abstract model checking. This means complicating the model in such a way a high number of spurious traces are generated in any formal verification of the property to disclose about the system under attack.We transform the program model in order to make the removal of spurious counterexamples by Abstraction refinement maximally inefficient. Because our approach is intended to defeat the Fundamental Abstraction refinement strategy, we are independent from the specific attack carried out by abstract model checking. A measure of the quality of the obfuscation obtained by model deformation is given together with a corresponding best obfuscation strategy for abstract model checking based on partition refinement.
Roberto Bruni - One of the best experts on this subject based on the ideXlab platform.
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Code obfuscation against Abstraction refinement attacks
Formal Aspects of Computing, 2018Co-Authors: Roberto Bruni, Roberto Giacobazzi, Roberta GoriAbstract:Code protection technologies require anti reverse engineering transformations to obfuscate programs in such a way that tools and methods for program analysis become ineffective. We introduce the concept of model deformation inducing an effective code obfuscation against attacks performed by abstract model checking. This means complicating the model in such a way a high number of spurious traces are generated in any formal verification of the property to disclose about the system under attack.We transform the program model in order to make the removal of spurious counterexamples by Abstraction refinement maximally inefficient. Because our approach is intended to defeat the Fundamental Abstraction refinement strategy, we are independent from the specific attack carried out by abstract model checking. A measure of the quality of the obfuscation obtained by model deformation is given together with a corresponding best obfuscation strategy for abstract model checking based on partition refinement.
Marco Aiello - One of the best experts on this subject based on the ideXlab platform.
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interoperation composition and simulation of services at home
International Conference on Service Oriented Computing, 2010Co-Authors: Eirini Kaldeli, Ehsan Ullah Warriach, Jaap Bresser, Alexander Lazovik, Marco AielloAbstract:Pervasive computing environments such as our future homes are the prototypical example of a dynamic, complex system where Service-Oriented Computing techniques will play an important role. A home equipped with heterogeneous devices, whose services and location constantly change, needs to behave as a coherent system supporting its inhabitants. In this paper, we present a fully implemented architecture for domotic applications which uses the concept of a service as its Fundamental Abstraction. The architecture distinguishes between a pervasive layer where devices and their basic internetworking live, and a composition layer where services can be dynamically composed as a reaction to user desires or home events. Next to the architecture, we also illustrate a visualization and simulation environment to test home coordination scenarios. From the technical point of view, the implementation uses UPnP as the basic device connection protocol and techniques from Artificial Intelligence planning for composing services at runtime.
Zhendong Su - One of the best experts on this subject based on the ideXlab platform.
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context sensitive data dependence analysis via linear conjunctive language reachability
Symposium on Principles of Programming Languages, 2017Co-Authors: Qirun Zhang, Zhendong SuAbstract:Many program analysis problems can be formulated as graph reachability problems. In the literature, context-free language (CFL) reachability has been the most popular formulation and can be computed in subcubic time. The context-sensitive data-dependence analysis is a Fundamental Abstraction that can express a broad range of program analysis problems. It essentially describes an interleaved matched-parenthesis language reachability problem. The language is not context-free, and the problem is well-known to be undecidable. In practice, many program analyses adopt CFL-reachability to exactly model the matched parentheses for either context-sensitivity or structure-transmitted data-dependence, but not both. Thus, the CFL-reachability formulation for context-sensitive data-dependence analysis is inherently an approximation. To support more precise and scalable analyses, this paper introduces linear conjunctive language (LCL) reachability, a new, expressive class of graph reachability. LCL not only contains the interleaved matched-parenthesis language, but is also closed under all set-theoretic operations. Given a graph with n nodes and m edges, we propose an O(mn) time approximation algorithm for solving all-pairs LCL-reachability, which is asymptotically better than known CFL-reachability algorithms. Our formulation and algorithm offer a new perspective on attacking the aforementioned undecidable problem - the LCL-reachability formulation is exact, while the LCL-reachability algorithm yields a sound approximation. We have applied the LCL-reachability framework to two existing client analyses. The experimental results show that the LCL-reachability framework is both more precise and scalable than the traditional CFL-reachability framework. This paper opens up the opportunity to exploit LCL-reachability in program analysis.
Roberto Giacobazzi - One of the best experts on this subject based on the ideXlab platform.
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Code obfuscation against Abstraction refinement attacks
Formal Aspects of Computing, 2018Co-Authors: Roberto Bruni, Roberto Giacobazzi, Roberta GoriAbstract:Code protection technologies require anti reverse engineering transformations to obfuscate programs in such a way that tools and methods for program analysis become ineffective. We introduce the concept of model deformation inducing an effective code obfuscation against attacks performed by abstract model checking. This means complicating the model in such a way a high number of spurious traces are generated in any formal verification of the property to disclose about the system under attack.We transform the program model in order to make the removal of spurious counterexamples by Abstraction refinement maximally inefficient. Because our approach is intended to defeat the Fundamental Abstraction refinement strategy, we are independent from the specific attack carried out by abstract model checking. A measure of the quality of the obfuscation obtained by model deformation is given together with a corresponding best obfuscation strategy for abstract model checking based on partition refinement.
