An accountable authority attribute-based encryption (A-ABE) scheme is presented in this paper. The notion of accountable authority identity-based encryption (A-IBE) was first introduced by Goyal at Crypto'07. It ...
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An accountable authority attribute-based encryption (A-ABE) scheme is presented in this paper. The notion of accountable authority identity-based encryption (A-IBE) was first introduced by Goyal at Crypto'07. It is a novel approach to mitigate the (inherent) key escrow problem in identity-based cryptosystems. In this work, the concept of accountable authority to attribute-based encryption (ABE) setting is generalized for the first time, and then a construction is given. The scheme non-trivially integrates an A-IBE scheme proposed by Libert et al. with an ABE scheme. In our construction, a user will be identified by a pair ( id, o~), where id denotes the user' s identity and ω denotes the set of attributes associated to the user. In addition, our construction is shown to be secure under some reasonable assumptions.
Occupants' comfort is the primary target in a building operation. However their efforts are often neglected and ruled out from traditional control strategies of energy-efficient building management systems. Occupa...
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作者:
尹强龙环Laboratory of Basic Study in Computing Science
MOE-MS Key Laboratory for Intelligent Computing and Intelligent SystemsDepartment of Computer Science and EngineeringShanghai Jiaotong University
In the context of process calculi, higher order π calculus (A calculus) is prominent and popular due to its ability to transfer processes. Motivated by the attempt to study the process theory in an integrated way, ...
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In the context of process calculi, higher order π calculus (A calculus) is prominent and popular due to its ability to transfer processes. Motivated by the attempt to study the process theory in an integrated way, we give a system study of A calculus with respect to the model independent framework. We show the coincidence of the context bisimulation to the absolute equality. We also build a subbisimilarity relation from A calculus to the π calculus.
In this study, we present a novel tree based index scheme for efficient indexing and serving large datasets in the cloud. It incorporates and extends the functionality of Hadoop to create a fully parallel index system...
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This paper presents a novel framework of human activity recognition with time series collected from inertial sensors. We model each action sequence with a collection of Linear Dynamic systems (LDSs), each LDS describi...
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This paper presents a novel framework of human activity recognition with time series collected from inertial sensors. We model each action sequence with a collection of Linear Dynamic systems (LDSs), each LDS describing a small patch of the sequence. A codebook is formed by using the K-medoids clustering algorithm and a Bag-of-systems (BoS) is developed to represent the time series. A great advantage of this method is that the complicated feature design procedure is avoided and the LDSs can well capture the dynamics of the time series. Our experiment validation on public dataset shows the promising results.
The creation of value-added services by automatic composition of existing ones is gaining a significant momentum as the potential silver bullet in service-oriented architecture. However, service composition faces two ...
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The creation of value-added services by automatic composition of existing ones is gaining a significant momentum as the potential silver bullet in service-oriented architecture. However, service composition faces two aspects of difficulties. First, users' needs present such characteristics as diversity, uncertainty and personalisation; second, the existing services run in a real-world environment that is highly complex and dynamically changing. These difficulties may cause the emergence of nondeterministic choices in the process of service composition, which has gone beyond what the existing automated service composition techniques can handle. According to most of the existing methods, the process model of composite service includes sequence constructs only. This article presents a method to introduce conditional branch structures into the process model of composite service when needed, in order to satisfy users' diverse and personalised needs and adapt to the dynamic changes of real-world environment. UML activity diagrams are used to represent dependencies in composite service. Two types of user preferences are considered in this article, which have been ignored by the previous work and a simple programming language style expression is adopted to describe them. Two different algorithms are presented to deal with different situations. A real-life case is provided to illustrate the proposed concepts and methods. [ABSTRACT FROM AUTHOR]
In this paper we present a new process calculus VPCΣ and an interpretation for core Erlang. VPCΣ is at least as expressive as VPC and it is more effective for verification with some built-in functions. The wellestab...
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A Bayesian optimization algorithm (BOA) belongs to estimation of distribution algorithms (EDAs). It is characterized by combining a Bayesian network and evolutionary algorithms to solve nearly decomposable optimizatio...
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ISBN:
(纸本)9781479938414
A Bayesian optimization algorithm (BOA) belongs to estimation of distribution algorithms (EDAs). It is characterized by combining a Bayesian network and evolutionary algorithms to solve nearly decomposable optimization problems. BOA is less popularly applied to solve high dimensionality complex optimization problems. A key reason is that the cost of training all dimensions by BOA becomes expensive with the increase of problem dimensionality. Since data are relatively sparse in a high dimensional space, even though BOA can train all dimensions simultaneously, the interdependent relations between different dimensions are difficult to learn. Its search ability is thus significantly reduced. In this paper, we propose a team of Bayesian optimization algorithms (TBOA) to search and learn dimensionality. TBOA consists of multiple BOAs, in which each BOA corresponds to a dimension of the solution domain and it is responsible for the search of this dimension's value region. The proposed TBOA is used to solve the real problem of task assignment in heterogeneous computingsystems. Extensive experiments demonstrate that the computational cost of the overall training in TBOA is decreased very significantly while keeping high solution accuracy.
Socio-technical systems (STSs) consist of human, hardware and software agents that work in tandem to fulfill stakeholder requirements. A specification for an STS consists of a set of (social) commitments among partici...
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Socio-technical systems (STSs) consist of human, hardware and software agents that work in tandem to fulfill stakeholder requirements. A specification for an STS consists of a set of (social) commitments among participating agents that serve as a contract among them. However, by their very nature, STSs are open, dynamic and continuously evolving along with their environments. To ensure that such systems continue to satisfy their requirements, the agents that comprise an STS must continuously adapt their behaviors to take into account risks and opportunities that arise at runtime. This paper presents a decision-theoretic self-adaptation framework that proposes candidate adaptation strategies for participating agents. These strategies are implementable by reconfiguration of plans or even changes in contractual commitments among agents. The adaptation procedure involves negotiating commitment changes and possible compensations to/from creditor agents. To evaluate the proposal, the paper also presents the results of an experimental study with a simulated STS, which confirms that success rates for achieving stakeholder goals and overall trade off utility can be improved significantly by incorporating evolving commitments to support STS adaptation.
Recently code transformations or tailored fitness functions are adopted to achieve coverage (structural or logical criterion) driven testing to ensure software reliability. However, some internal threats like negative...
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Recently code transformations or tailored fitness functions are adopted to achieve coverage (structural or logical criterion) driven testing to ensure software reliability. However, some internal threats like negative impacts on underlying search strategies or local maximum exist. So we propose a dynamic symbolic execution (DSE) based framework combined with a path filtering algorithm and a new heuristic path search strategy, i.e., predictive path search, to achieve faster coverage-driven testing with lower testing cost. The empirical experiments (three open source projects and two industrial projects) show that our approach is effective and efficient. For the open source projects w.r.t branch coverage, our approach in average reduces 25.5% generated test cases and 36.3% solved constraints than the traditional DSE-based approach without path filtering. And the presented heuristic strategy, on the same testing budget, improves the branch coverage by 26.4% and 35.4% than some novel search strategies adopted in KLEE and CREST.
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