Junyan Qian

A Ciphertext-Policy Attribute-Based Encryption Based on an Ordered Binary Decision Diagram

Ciphertext-policy attribute-based encryption (CP-ABE) is widely used in many cyber physical systems and the Internet of Things for guaranteeing information security. In order to improve the performance and efficiency of CP-ABE, this paper makes a change to the access structure of describing access polices in CP-ABE, and presents a new CP-ABE system based on the ordered binary decision diagram (OBDD). The new system makes full use of both the powerful description ability and the high calculating efficiency of OBDD. First, in the access structure, the new system allows multiple occurrences of the same attribute in a strategy, supports both positive attribute and negative attribute in the description of access polices, and can describe free-form access polices by using Boolean operations. Second, in the key generation stage, the size of secret keys generated by the new system is constant and not affected by the number of attributes; furthermore, time complexity of the key generation algorithm is O(1). Third, in the encryption stage, both the time complexity of the encryption algorithm and the size of generated ciphertext are determined by the number of valid paths contained in the OBDD instead of the number of attributes occurring in access polices. Finally, in the decryption stage, the new system supports fast decryption and the time complexity of the decryption algorithm is only O(1). As a result, compared with existing CP-ABE schemes, the new system has better performance and efficiency. It is proved that the new CP-ABE system can also resist collision attack and chosen-plaintext attack under the decisional bilinear Diffie Hellman assumption.

Using ASP for knowledge management with user authorization

Unlike conventional rule based knowledge bases (KBs) that support monotonic reasoning, a key correctness issue, i.e. the correctness of a sub-KB with respect to the full KB, arises when using a KB represented by non-monotonic reasoning languages such as Answer Set Programming (ASP). Since a user may have rights to access only a subset of a KB, the non-monotonic nature of ASP may cause the occurrence of consequences, which are erroneous in the sense that the consequences are not reasonable in the full KB. This paper proposes an approach dealing with the problem. The main idea is to let the usage of Closed World Assumptions (CWAs) for literals in a KB satisfy certain constraints. Two kinds of access right propositions are created, rule retrieval right propositions to control the access to rules, and CWA right propositions to control the usage of CWAs for literals. Based on these right propositions, this paper first defines an algorithm for translating an original KB into a KB tagged by right propositions, and then discusses the right dependency in a KB and proposes methods for checking and obtaining a set of rights that is closed under a set of dependency rules. Finally, several results on the correctness of a set of rights in a KB are presented, which serve as guidelines for the correct use of a KB. As an example, a KB of illness-related financial support for teachers of a university is presented to illustrate the application of our approach.

Model checking for timed statecharts

Timed Statecharts, which can efficiently specify explicit dense time, is an extension to the visual specification language Statecharts with real-time constructs. We give a definition of timed Statecharts that specifies explicit temporal behavior as timed automata does. It is very difficult to verify directly whether timed Statecharts satisfies the required properties. However, by compiling it into timed automata, timed Statecharts may be checked using Uppaal tool. In the paper, the state of timed Statecharts is represented by inductive term, and a step semantics of timed Statecharts is briefly described. The translation rules are shown by a compositional approach for formalizing the timed Statecharts semantics directly on sequences of micro steps. Timed automata corresponding to timed Statecharts was also discussed.

An integer programming method for constructing tightly coupled VLSI subarrays

Minimizing the interconnection length between the processing elements (PEs) of VLSI arrays is beneficial to reduce the capacitance, power dissipation and dynamic communication cost. In this paper, a novel method, based on integer programming, for constructing tightly-coupled subarrays from the degradable VLSI arrays is presented, such that the target array has the minimum interconnection length. Compared with the state-of-the-art algorithms, the proposed method can guarantee that the interconnection length of the target array is minimum in row and column directions simultaneously. The performances of the proposed method are compared with previous studies and it indicates that the proposed method achieves better results in terms of total interconnection length.

Optimal Reconfiguration of High-Performance VLSI Subarrays with Network Flow

A two-dimensional mesh-connected processor array is an extensively investigated architecture used in parallel processing. Massive studies have addressed the use of reconfiguration algorithms for the processor arrays with faults. However, the subarray generated by previous algorithms contains a large number of long interconnects, which in turn leads to more communication costs, capacitance and dynamic power dissipation. In this paper, we propose novel techniques, making use of the idea of network flow, to construct the high-performance subarray, which has the minimum number of long interconnects. First, we construct a network flow model according to the host array under a specific constraint. Second, we show that the reconfiguration problem of high-performance subarray can be optimally solved in polynomial time by using efficient minimum-cost flow algorithms. Finally, we prove that the geometric properties of the resulted subarray meet the system requirements. Simulations based on several random and clustered fault scenarios clearly reveal the advantage of the proposed technique for reducing the number of long interconnects. It is shown that, for a host array of size 512 × 512, the number of long interconnects in the subarray can be reduced by up to 70.05 percent for clustered faults and by up to 55.28 percent for random faults with density of 1 percent as compared to the-state-of-the-art.

Automatic Construction of Complete Abstraction by Abstract Interpretation

Abstraction plays a fundamental role in combating state-space explosion in model checking. Firstly, we study how to abstract models of mu-calculus and derive abstractions that are sound, and apply them to abstracting Kripke structures. However, a lack of completeness in the abstract interpretation leads to spurious counterexamples in the abstract model checking. In order to eliminate spurious counterexamples, the paper describes a method for minimally making abstract interpretations complete, and this refined complete abstract domain always exists.

A novel test case generation method for prolog programs based on call patterns semantics

A natural way to generate test cases for a Prolog program is to view the call patterns of the procedures in the program as an implicit representation of the control flow graph (CFG) of the program. This paper explores the idea by proposing a call patterns-based test case generation method, where a set of call patterns or computed answers is used to describe the paths in a CFG. With a constraint-based call patterns semantics, this method is formalized. Through the use of a proper constraints solver, we can generate test cases automatically from the sets of constraints. This method can be based on any approximation of the call patterns semantics. So compared with traditional CFG-based test case generation, the method is more flexible and can be easily adapted to meet the requirements of a tester expressed by the approximation of the call patterns semantics we use.

A game-theoretic approach to advertisement dissemination in ephemeral networks

In ephemeral networks, disseminating advertisements faces two dilemmatic problems: on the one hand, disseminators own the limited resources and have privacy concerns, thus, often preferring to avoid disseminating advertisements without enough incentives; Even if advertisements are disseminated, their dissemination accuracy is lower. On the other hand, false advertisements may flood in ephemeral networks if too many incentives but no punishments are given. Thus, it is a challenge to design an effective scheme to guarantee rational disseminators have sufficient impetus to forward true advertisements to the interested consumers and report false advertisements, despite facing the limitation of resources and the risk of privacy leakage. To solve this problem, in this paper, a bargaining-based scheme is proposed to motive disseminators to forward the true advertisements to the interested node and a semi-grim policy is designed for punishing the disseminators who releases and disseminates false advertisements. Acknowledging the assumption of incomplete information, a repeated dissemination game is proposed to help disseminators to decide whether to forward advertisements or report false advertisements. Simulation results demonstrate that our scheme not only provides disseminators a strong impetus to disseminate the advertisements with higher dissemination accuracy, but also effectively prevents disseminators from forwarding false advertisements.

Knowledge Graph Embedding by Dynamic Translation

Knowledge graph embedding aims at representing entities and relations in a knowledge graph as dense, low-dimensional and real-valued vectors. It can efficiently measure semantic correlations of entities and relations in knowledge graphs, and improve the performance of knowledge acquisition, fusion and inference. Among various embedding models appeared in recent years, the translation-based models such as TransE, TransH, TransR and TranSparse achieve state-of-the-art performance. However, the translation principle applied in these models is too strict and can not deal with complex entities and relations very well. In this paper, by introducing parameter vectors into the translation principle which treats each relation as a translation from the head entity to the tail entity, we propose a novel dynamic translation principle which supports flexible translation between the embeddings of entities and relations. We use this principle to improve the TransE, TransR and TranSparse models respectively and build new models named TransE-DT, TransR-DT and TranSparse-DT correspondingly. Experimental results show that our dynamic translation principle achieves great improvement in both the link prediction task and the triple classification task.

A Behavioral Similarity Metric for Semantic Workflows Based on Semantic Task Adjacency Relations With Importance

For modern enterprises and organizations, new business workflow can be constructed by reusing already available similar workflows in the repository. Workflow reuse is an important method for implementing business workflow management. Semantic workflows contain control-flow, data-flow, and semantic information relevant to a domain, which facilitates workflow reuse and adaptation. A similarity metric for semantic workflows is important for achieving workflow reuse. However, the existing similarity metrics for semantic workflows focus on workflow structures while ignoring their behaviours, which affect the quality of retrieved similar semantic workflows. Therefore, this paper proposes a behavioral similarity metric for semantic workflows based on semantic task adjacency relations with importance (ISTARs) that incorporate domain knowledge. First, ISTARs that involve semantic tasks and importance of semantic task adjacency relations are defined, and the ISTARs set is used to express the behaviour of the semantic workflow. The ISTAR similarity proposal is based on the similarity between two ISTARs sets and represents the similarity between semantic workflows. The ISTAR distance deduced from ISTAR similarity satisfies the properties of distance metrics. An experimental evaluation revealed that the proposed ISTAR similarity resulted in more effective retrieval of similar semantic workflows than did existing popular behavioral similarity measures.