LEACH (Low-Encrgy Adaptive Clustering Hi-erarchy) protocol is a basic clustering-based routing protocol of sensor networks. In this paper, we present the design of SLEACH, asecure extension for the LEACH protocol. We ...LEACH (Low-Encrgy Adaptive Clustering Hi-erarchy) protocol is a basic clustering-based routing protocol of sensor networks. In this paper, we present the design of SLEACH, asecure extension for the LEACH protocol. We divide SLEACH into four phases and fit inexpensivecryplp-graphic operations to each part of the protocol functionality to create an efficient,practical protocol. Then we give security analyses of SLEACH. Our security analyses show that ourschemeis robust against any external attacker or compromised nodes in the sensor network.展开更多
How to share experience and resources among learners is becoming one of the hottest topics in the field of E-Learning collaborative techniques. An intuitive way to achieve this objective is to group learners which can...How to share experience and resources among learners is becoming one of the hottest topics in the field of E-Learning collaborative techniques. An intuitive way to achieve this objective is to group learners which can help each other into the same community and help them learn collaboratively. In this paper, we proposed a novel community self-organization model based on multi-agent mechanism, which can automatically group learners with similar preferences and capabilities. In particular, we proposed award and exchange schemas with evaluation and preference track records to raise the performance of this algorithm. The description of learner capability, the matchmaking process, the definition of evaluation and preference track records, the rules of award and exchange schemas and the self-organization algorithm are all discussed in this paper. Meanwhile, a prototype has been built to verify the validity and efficiency of the algorithm. Experiments based on real learner data showed that this mechanism can organize learner communities properly and efficiently; and that it has sustainable improved efficiency and scalability.展开更多
The authors discuss the concept of meta information which is the description of information system or its subsystems, and proposes algorithms for meta information generation. Meta information can be generated in paral...The authors discuss the concept of meta information which is the description of information system or its subsystems, and proposes algorithms for meta information generation. Meta information can be generated in parallel mode and network computation can be used to accelerate meta information generation. Most existing rough set methods assume information system to be centralized and cannot be applied directly in distributed information system. Data integration, which is costly, is necessary for such existing methods. However, meta information integration will eliminate the need of data integration in many cases, since many rough set operations can be done straightforward based on meta information, and many existing methods can be modified based on meta information.展开更多
Based on decisional Difiie-Hcllman problem, we propose a simpleproxy-protected signature scheme In the random oracle model, we also carry out the strict securityproof for the proposed scheme. The security of the propo...Based on decisional Difiie-Hcllman problem, we propose a simpleproxy-protected signature scheme In the random oracle model, we also carry out the strict securityproof for the proposed scheme. The security of the proposed scheme is not loosely related to thediscrete logarithm assumption hut tightly related to the decisional Diffie-Hellman assumption in therandom oracle model.展开更多
To solve the problem of the inadequacy of semantic processing in the intelligent question answering system, an integrated semantic similarity model which calculates the semantic similarity using the geometric distance...To solve the problem of the inadequacy of semantic processing in the intelligent question answering system, an integrated semantic similarity model which calculates the semantic similarity using the geometric distance and information content is presented in this paper. With the help of interrelationship between concepts, the information content of concepts and the strength of the edges in the ontology network, we can calculate the semantic similarity between two concepts and provide information for the further calculation of the semantic similarity between user’s question and answers in knowledge base. The results of the experiments on the prototype have shown that the semantic problem in natural language processing can also be solved with the help of the knowledge and the abundant semantic information in ontology. More than 90% accuracy with less than 50 ms average searching time in the intelligent question answering prototype system based on ontology has been reached. The result is very satisfied. Key words intelligent question answering system - ontology - semantic similarity - geometric distance - information content CLC number TP39 Foundation item: Supported by the important science and technology item of China of “The 10th Five-year Plan” (2001BA101A05-04)Biography: LIU Ya-jun (1953-), female, Associate professor, research direction: software engineering, information processing, data-base application.展开更多
Ontology mapping is the bottleneck of handling conflicts among heterogeneous ontologies and of implementing reconfiguration or interoperability of legacy systems. We proposed an ontology mapping method by using machin...Ontology mapping is the bottleneck of handling conflicts among heterogeneous ontologies and of implementing reconfiguration or interoperability of legacy systems. We proposed an ontology mapping method by using machine learning, type constraints and logic mining techniques. This method is able to find concept correspondences through instances and the result is optimized by using an error function; it is able to find attribute correspondence between two equivalent concepts and the mapping accuracy is enhanced by combining together instances learning, type constraints and the logic relations that are imbedded in instances; moreover, it solves the most common kind of categorization conflicts. We then proposed a merging algorithm to generate the shared ontology and proposed a reconfigurable architecture for interoperation based on multi agents. The legacy systems are encapsulated as information agents to participate in the integration system. Finally we give a simplified case study.展开更多
The problem of how to efficiently store and query the clustering results was considered. Three different storage schemas for clustering results using relational database were proposed, namely, full schema (f-schema), ...The problem of how to efficiently store and query the clustering results was considered. Three different storage schemas for clustering results using relational database were proposed, namely, full schema (f-schema), partial schema (p-schema) and compressed schema (c-schema). At the same time, a classification for queries issued to the clustering results was also presented. Finally, we empirically studied the performance of proposed queries on different storage schemas. To our knowledge, this is the first work to address the problem.展开更多
It is nontrivial to maintain such discovered frequent query patterns in real XML-DBMS because the transaction database of queries may allow frequent updates and such updates may not only invalidate some existing frequ...It is nontrivial to maintain such discovered frequent query patterns in real XML-DBMS because the transaction database of queries may allow frequent updates and such updates may not only invalidate some existing frequent query patterns but also generate some new frequent query patterns. In this paper, two incremental updating algorithms, FUX-QMiner and FUXQMiner, are proposed for efficient maintenance of discovered frequent query patterns and generation the new frequent query patterns when new XMI, queries are added into the database. Experimental results from our implementation show that the proposed algorithms have good performance. Key words XML - frequent query pattern - incremental algorithm - data mining CLC number TP 311 Foudation item: Supported by the Youthful Foundation for Scientific Research of University of Shanghai for Science and TechnologyBiography: PENG Dun-lu (1974-), male, Associate professor, Ph.D, research direction: data mining, Web service and its application, peerto-peer computing.展开更多
On the basis of software testing tools we developed for programming languages, we firstly present a new control flowgraph model based on block. In view of the notion of block, we extend the traditional program\|based ...On the basis of software testing tools we developed for programming languages, we firstly present a new control flowgraph model based on block. In view of the notion of block, we extend the traditional program\|based software test data adequacy measurement criteria, and empirically analyze the subsume relation between these measurement criteria. Then, we define four test complexity metrics based on block. They are J\|complexity 0; J\|complexity 1; J\|complexity \{1+\}; J\|complexity 2. Finally, we show the Kiviat diagram that makes software quality visible.展开更多
This paper presents a "cluster" based search scheme in peer-to-peer network. The idea is based on the fact that data distribution in an information society has structured feature. We designed an algorithm to...This paper presents a "cluster" based search scheme in peer-to-peer network. The idea is based on the fact that data distribution in an information society has structured feature. We designed an algorithm to cluster peers that have similar interests. When receiving a query request, a peer will preferentially forward it to another peer which belongs to the same cluster and shares more similar interests. By this way search efficiency will be remarkably improved and at the same time good resilience against peer failure (the ability to withstand peer failure) is reserved.展开更多
ABC95 array computer is a multi-function network computer based on FPGA technology. A notable feature of ABC95 array computer is the support of complex interconnection, which determines that the computer must have eno...ABC95 array computer is a multi-function network computer based on FPGA technology. A notable feature of ABC95 array computer is the support of complex interconnection, which determines that the computer must have enough I/O band and flexible communications between Pes. The authors designed the interconnecting network chips of ABC95 and realized a form of multi-function interconnection. The multi-function interconnecting network supports conflict-free access from processors to memory matrix and the MESH network of enhanced processors to processor communications. The design scheme has been proved feasible by experiment.展开更多
This paper presents an efficient way to preserve the volume of implicit surfaces generated by skeletons. Recursive subdivision is used to efficiently calculate the volume. The criterion for subdivision is obtained by ...This paper presents an efficient way to preserve the volume of implicit surfaces generated by skeletons. Recursive subdivision is used to efficiently calculate the volume. The criterion for subdivision is obtained by using the property of density functions and treating different types of skeletons respectively to get accurate minimum and maximum distances from a cube to a skeleton. Compared with the criterion generated by other ways such as using traditional Interval Analysis, Affine Arithmetic, or Lipschitz condition, our approach is much better both in speed and accuracy.展开更多
Clustering in high-dimensional space is an important domain in data mining. It is the process of discovering groups in a high-dimensional dataset, in such way, that the similarity between the elements of the same clus...Clustering in high-dimensional space is an important domain in data mining. It is the process of discovering groups in a high-dimensional dataset, in such way, that the similarity between the elements of the same cluster is maximum and between different clusters is minimal. Many clustering algorithms are not applicable to high-dimensional space for its sparseness and decline properties. Dimensionality reduction is an effective method to solve this problem. The paper proposes a novel clustering algorithm CFSBC based on closed frequent itemsets derived from association rule mining, which can get the clustering attributes with high efficiency. The algorithm has several advantages. First, it deals effectively with the problem of dimensionality reduction. Second, it is applicable to different kinds of attributes. Third, it is suitable for very large data sets. Experiment shows that the proposed algorithm is effective and efficient. Key words clustering - closed frequent itemsets - association rule - clustering attributes CLC number TP 311 Foundation item: Supported by the National Natural Science Foundation of China (70371015)Biography: NI Wei-wei (1979-), male, Ph. D candidate, research direction: data mining and knowledge discovery.展开更多
Indirect association is a high level relationship between items and frequent itemsets in data. Current research approaches on indirect association mining are limited to indirect association between itempairs, which wi...Indirect association is a high level relationship between items and frequent itemsets in data. Current research approaches on indirect association mining are limited to indirect association between itempairs, which will discovertoo many rules from dataset. A formal definition of indirect association between multiple items is presented, along with an algorithm, SET-NIA,for mining this kind of indirect associations based on anti-monotonicity of indirect associations and frequent itempair support matrix. While the found rules contain same information as compared to the rules found by indirect association between itempairs mining algorithms, this notion brings space-saving in storage ofthe rules as well as superiority for human to understand and apply the rules. Experiments conducted on two real-word datasets show that SET-NIA can effectively find fewer rules than existing algorithms which mine indirect association between itempairs, the experimental results also prove that SET-NIA has better performance than existing algorithms.展开更多
To prevent active attack, we propose a new threshold signature scheme usingself-certified public keys, which makes use of hash function and discrete logarithm problem. Thescheme has less commutnication and computation...To prevent active attack, we propose a new threshold signature scheme usingself-certified public keys, which makes use of hash function and discrete logarithm problem. Thescheme has less commutnication and computation cost than previous schemes. Furthermore, the signatmeprocess of the proposed scheme is non-interactive.展开更多
Recently machine learning-based intrusion detection approaches have been subjected to extensive researches because they can detect both misuse and anomaly. In this paper, rough set classification (RSC), a modern learn...Recently machine learning-based intrusion detection approaches have been subjected to extensive researches because they can detect both misuse and anomaly. In this paper, rough set classification (RSC), a modern learning algorithm, is used to rank the features extracted for detecting intrusions and generate intrusion detection models. Feature ranking is a very critical step when building the model. RSC performs feature ranking before generating rules, and converts the feature ranking to minimal hitting set problem addressed by using genetic algorithm (GA). This is done in classical approaches using Support Vector Machine (SVM) by executing many iterations, each of which removes one useless feature. Compared with those methods, our method can avoid many iterations. In addition, a hybrid genetic algorithm is proposed to increase the convergence speed and decrease the training time of RSC. The models generated by RSC take the form of'IF-THEN' rules, which have the advantage of explication. Tests and comparison of RSC with SVM on DARPA benchmark data showed that for Probe and DoS attacks both RSC and SVM yielded highly accurate results (greater than 99% accuracy on testing set).展开更多
Web information extraction is viewed as a classification process and a competing classification method is presented to extract Web information directly through classification. Web fragments are represented with three ...Web information extraction is viewed as a classification process and a competing classification method is presented to extract Web information directly through classification. Web fragments are represented with three general features and the similarities between fragments are then defined on the bases of these features. Through competitions of fragments for different slots in information templates, the method classifies fragments into slot classes and filters out noise information. Far less annotated samples are needed as compared with rule-based methods and therefore it has a strong portability. Experiments show that the method has good performance and is superior to DOM-based method in information extraction. Key words information extraction - competing classification - feature extraction - wrapper induction CLC number TP 311 Foundation item: Supported by the National Natural Science Foundation of China (60303024)Biography: LI Xiang-yang (1974-), male, Ph. D. Candidate, research direction: information extraction, natural language processing.展开更多
This paper proposes a dynamic Web service trust (WS Trust) model, and somecorresponding trust metric evaluation algorithms. The main goal is to evaluate the trustworthinessand predict the future bchaxiors of entities ...This paper proposes a dynamic Web service trust (WS Trust) model, and somecorresponding trust metric evaluation algorithms. The main goal is to evaluate the trustworthinessand predict the future bchaxiors of entities in oeder to help users find trustworthy Web serviceproviders and prevent users from providing unfair ratings against service providers.展开更多
We demonstrate the flaws of Mao's method, which is an augmentation ofprotocol idealization in BAN-like logics, and then offer some new idealization rules based on Mao'smethod. Furthermore, we give some theoret...We demonstrate the flaws of Mao's method, which is an augmentation ofprotocol idealization in BAN-like logics, and then offer some new idealization rules based on Mao'smethod. Furthermore, we give some theoretical analysis of our rules using the strand spaceformalism, and show the soundness of our idealization rules under strand spaces Some examples onusing the new rules to analyze security protocols are also concerned. Our idealization method ismore effective than Mao's method towards many protocol instances, and is supported by a formalmodel.展开更多
Transient fault detection mechanism is added to simultaneous multithreading architecture. By exploiting both ILP (Instruction Level Parallelism) and TLP (Thread Level Parallelism), Simultaneous Multithreading (SMT) Fa...Transient fault detection mechanism is added to simultaneous multithreading architecture. By exploiting both ILP (Instruction Level Parallelism) and TLP (Thread Level Parallelism), Simultaneous Multithreading (SMT) Fault Tolerance Processor can be expected to achieve better tradeoff between performance and hardware cost than traditional Fault Tolerance Processors. Detailed simulations of 3 of SPEC95 benchmarks show that executing two redundant programs on the fault-tolerant microarchitecture takes only 40%–61%longer than running a single version of the program. The new instruction fetch algorithm enhances the performance by 0.4%~1%to most of the benchmarks we choose randomly.展开更多
摘要LEACH (Low-Encrgy Adaptive Clustering Hi-erarchy) protocol is a basic clustering-based routing protocol of sensor networks. In this paper, we present the design of SLEACH, asecure extension for the LEACH protocol. We divide SLEACH into four phases and fit inexpensivecryplp-graphic operations to each part of the protocol functionality to create an efficient,practical protocol. Then we give security analyses of SLEACH. Our security analyses show that ourschemeis robust against any external attacker or compromised nodes in the sensor network.
摘要How to share experience and resources among learners is becoming one of the hottest topics in the field of E-Learning collaborative techniques. An intuitive way to achieve this objective is to group learners which can help each other into the same community and help them learn collaboratively. In this paper, we proposed a novel community self-organization model based on multi-agent mechanism, which can automatically group learners with similar preferences and capabilities. In particular, we proposed award and exchange schemas with evaluation and preference track records to raise the performance of this algorithm. The description of learner capability, the matchmaking process, the definition of evaluation and preference track records, the rules of award and exchange schemas and the self-organization algorithm are all discussed in this paper. Meanwhile, a prototype has been built to verify the validity and efficiency of the algorithm. Experiments based on real learner data showed that this mechanism can organize learner communities properly and efficiently; and that it has sustainable improved efficiency and scalability.
摘要The authors discuss the concept of meta information which is the description of information system or its subsystems, and proposes algorithms for meta information generation. Meta information can be generated in parallel mode and network computation can be used to accelerate meta information generation. Most existing rough set methods assume information system to be centralized and cannot be applied directly in distributed information system. Data integration, which is costly, is necessary for such existing methods. However, meta information integration will eliminate the need of data integration in many cases, since many rough set operations can be done straightforward based on meta information, and many existing methods can be modified based on meta information.
摘要Based on decisional Difiie-Hcllman problem, we propose a simpleproxy-protected signature scheme In the random oracle model, we also carry out the strict securityproof for the proposed scheme. The security of the proposed scheme is not loosely related to thediscrete logarithm assumption hut tightly related to the decisional Diffie-Hellman assumption in therandom oracle model.
摘要To solve the problem of the inadequacy of semantic processing in the intelligent question answering system, an integrated semantic similarity model which calculates the semantic similarity using the geometric distance and information content is presented in this paper. With the help of interrelationship between concepts, the information content of concepts and the strength of the edges in the ontology network, we can calculate the semantic similarity between two concepts and provide information for the further calculation of the semantic similarity between user’s question and answers in knowledge base. The results of the experiments on the prototype have shown that the semantic problem in natural language processing can also be solved with the help of the knowledge and the abundant semantic information in ontology. More than 90% accuracy with less than 50 ms average searching time in the intelligent question answering prototype system based on ontology has been reached. The result is very satisfied. Key words intelligent question answering system - ontology - semantic similarity - geometric distance - information content CLC number TP39 Foundation item: Supported by the important science and technology item of China of “The 10th Five-year Plan” (2001BA101A05-04)Biography: LIU Ya-jun (1953-), female, Associate professor, research direction: software engineering, information processing, data-base application.
基金国家高技术研究发展计划(863计划),国家自然科学基金,Shanghai Commission of Science and Technology Key Project
摘要Ontology mapping is the bottleneck of handling conflicts among heterogeneous ontologies and of implementing reconfiguration or interoperability of legacy systems. We proposed an ontology mapping method by using machine learning, type constraints and logic mining techniques. This method is able to find concept correspondences through instances and the result is optimized by using an error function; it is able to find attribute correspondence between two equivalent concepts and the mapping accuracy is enhanced by combining together instances learning, type constraints and the logic relations that are imbedded in instances; moreover, it solves the most common kind of categorization conflicts. We then proposed a merging algorithm to generate the shared ontology and proposed a reconfigurable architecture for interoperation based on multi agents. The legacy systems are encapsulated as information agents to participate in the integration system. Finally we give a simplified case study.
摘要The problem of how to efficiently store and query the clustering results was considered. Three different storage schemas for clustering results using relational database were proposed, namely, full schema (f-schema), partial schema (p-schema) and compressed schema (c-schema). At the same time, a classification for queries issued to the clustering results was also presented. Finally, we empirically studied the performance of proposed queries on different storage schemas. To our knowledge, this is the first work to address the problem.
摘要It is nontrivial to maintain such discovered frequent query patterns in real XML-DBMS because the transaction database of queries may allow frequent updates and such updates may not only invalidate some existing frequent query patterns but also generate some new frequent query patterns. In this paper, two incremental updating algorithms, FUX-QMiner and FUXQMiner, are proposed for efficient maintenance of discovered frequent query patterns and generation the new frequent query patterns when new XMI, queries are added into the database. Experimental results from our implementation show that the proposed algorithms have good performance. Key words XML - frequent query pattern - incremental algorithm - data mining CLC number TP 311 Foudation item: Supported by the Youthful Foundation for Scientific Research of University of Shanghai for Science and TechnologyBiography: PENG Dun-lu (1974-), male, Associate professor, Ph.D, research direction: data mining, Web service and its application, peerto-peer computing.
摘要On the basis of software testing tools we developed for programming languages, we firstly present a new control flowgraph model based on block. In view of the notion of block, we extend the traditional program\|based software test data adequacy measurement criteria, and empirically analyze the subsume relation between these measurement criteria. Then, we define four test complexity metrics based on block. They are J\|complexity 0; J\|complexity 1; J\|complexity \{1+\}; J\|complexity 2. Finally, we show the Kiviat diagram that makes software quality visible.
摘要This paper presents a "cluster" based search scheme in peer-to-peer network. The idea is based on the fact that data distribution in an information society has structured feature. We designed an algorithm to cluster peers that have similar interests. When receiving a query request, a peer will preferentially forward it to another peer which belongs to the same cluster and shares more similar interests. By this way search efficiency will be remarkably improved and at the same time good resilience against peer failure (the ability to withstand peer failure) is reserved.
摘要ABC95 array computer is a multi-function network computer based on FPGA technology. A notable feature of ABC95 array computer is the support of complex interconnection, which determines that the computer must have enough I/O band and flexible communications between Pes. The authors designed the interconnecting network chips of ABC95 and realized a form of multi-function interconnection. The multi-function interconnecting network supports conflict-free access from processors to memory matrix and the MESH network of enhanced processors to processor communications. The design scheme has been proved feasible by experiment.
摘要This paper presents an efficient way to preserve the volume of implicit surfaces generated by skeletons. Recursive subdivision is used to efficiently calculate the volume. The criterion for subdivision is obtained by using the property of density functions and treating different types of skeletons respectively to get accurate minimum and maximum distances from a cube to a skeleton. Compared with the criterion generated by other ways such as using traditional Interval Analysis, Affine Arithmetic, or Lipschitz condition, our approach is much better both in speed and accuracy.
摘要Clustering in high-dimensional space is an important domain in data mining. It is the process of discovering groups in a high-dimensional dataset, in such way, that the similarity between the elements of the same cluster is maximum and between different clusters is minimal. Many clustering algorithms are not applicable to high-dimensional space for its sparseness and decline properties. Dimensionality reduction is an effective method to solve this problem. The paper proposes a novel clustering algorithm CFSBC based on closed frequent itemsets derived from association rule mining, which can get the clustering attributes with high efficiency. The algorithm has several advantages. First, it deals effectively with the problem of dimensionality reduction. Second, it is applicable to different kinds of attributes. Third, it is suitable for very large data sets. Experiment shows that the proposed algorithm is effective and efficient. Key words clustering - closed frequent itemsets - association rule - clustering attributes CLC number TP 311 Foundation item: Supported by the National Natural Science Foundation of China (70371015)Biography: NI Wei-wei (1979-), male, Ph. D candidate, research direction: data mining and knowledge discovery.
摘要Indirect association is a high level relationship between items and frequent itemsets in data. Current research approaches on indirect association mining are limited to indirect association between itempairs, which will discovertoo many rules from dataset. A formal definition of indirect association between multiple items is presented, along with an algorithm, SET-NIA,for mining this kind of indirect associations based on anti-monotonicity of indirect associations and frequent itempair support matrix. While the found rules contain same information as compared to the rules found by indirect association between itempairs mining algorithms, this notion brings space-saving in storage ofthe rules as well as superiority for human to understand and apply the rules. Experiments conducted on two real-word datasets show that SET-NIA can effectively find fewer rules than existing algorithms which mine indirect association between itempairs, the experimental results also prove that SET-NIA has better performance than existing algorithms.
摘要To prevent active attack, we propose a new threshold signature scheme usingself-certified public keys, which makes use of hash function and discrete logarithm problem. Thescheme has less commutnication and computation cost than previous schemes. Furthermore, the signatmeprocess of the proposed scheme is non-interactive.
摘要Recently machine learning-based intrusion detection approaches have been subjected to extensive researches because they can detect both misuse and anomaly. In this paper, rough set classification (RSC), a modern learning algorithm, is used to rank the features extracted for detecting intrusions and generate intrusion detection models. Feature ranking is a very critical step when building the model. RSC performs feature ranking before generating rules, and converts the feature ranking to minimal hitting set problem addressed by using genetic algorithm (GA). This is done in classical approaches using Support Vector Machine (SVM) by executing many iterations, each of which removes one useless feature. Compared with those methods, our method can avoid many iterations. In addition, a hybrid genetic algorithm is proposed to increase the convergence speed and decrease the training time of RSC. The models generated by RSC take the form of'IF-THEN' rules, which have the advantage of explication. Tests and comparison of RSC with SVM on DARPA benchmark data showed that for Probe and DoS attacks both RSC and SVM yielded highly accurate results (greater than 99% accuracy on testing set).
摘要Web information extraction is viewed as a classification process and a competing classification method is presented to extract Web information directly through classification. Web fragments are represented with three general features and the similarities between fragments are then defined on the bases of these features. Through competitions of fragments for different slots in information templates, the method classifies fragments into slot classes and filters out noise information. Far less annotated samples are needed as compared with rule-based methods and therefore it has a strong portability. Experiments show that the method has good performance and is superior to DOM-based method in information extraction. Key words information extraction - competing classification - feature extraction - wrapper induction CLC number TP 311 Foundation item: Supported by the National Natural Science Foundation of China (60303024)Biography: LI Xiang-yang (1974-), male, Ph. D. Candidate, research direction: information extraction, natural language processing.
基金Supported by the National Key Basic Research andDevelopment Program (973 Program G20000263)
摘要This paper proposes a dynamic Web service trust (WS Trust) model, and somecorresponding trust metric evaluation algorithms. The main goal is to evaluate the trustworthinessand predict the future bchaxiors of entities in oeder to help users find trustworthy Web serviceproviders and prevent users from providing unfair ratings against service providers.
摘要We demonstrate the flaws of Mao's method, which is an augmentation ofprotocol idealization in BAN-like logics, and then offer some new idealization rules based on Mao'smethod. Furthermore, we give some theoretical analysis of our rules using the strand spaceformalism, and show the soundness of our idealization rules under strand spaces Some examples onusing the new rules to analyze security protocols are also concerned. Our idealization method ismore effective than Mao's method towards many protocol instances, and is supported by a formalmodel.
基金Supported by the National Natural Science Funda tion of China (60103002)
摘要Transient fault detection mechanism is added to simultaneous multithreading architecture. By exploiting both ILP (Instruction Level Parallelism) and TLP (Thread Level Parallelism), Simultaneous Multithreading (SMT) Fault Tolerance Processor can be expected to achieve better tradeoff between performance and hardware cost than traditional Fault Tolerance Processors. Detailed simulations of 3 of SPEC95 benchmarks show that executing two redundant programs on the fault-tolerant microarchitecture takes only 40%–61%longer than running a single version of the program. The new instruction fetch algorithm enhances the performance by 0.4%~1%to most of the benchmarks we choose randomly.