In Eurocrypt 2003, Gentry introduced a new public key encryption paradigm called certificate-based encryption (CBE) to overcome the drawbacks of the conventional PKI and the identity based encryption (IBE). CBE provides an efficient implicit certification mechanism and allows a periodical update of certificate status while eliminating third-party queries for the certificate status. In addition, it also solves the key escrow problem and key distribution problem in IBE. In this paper, we propose a method to achieve generic CBE constructions from PKE and IBE, which are provably CCA-secure in the random oracle model. Compared to previous generic constructions, the security requirement of the primitive encryption schemes in our method is much weaker.
It is important to choose good parameters in support vector regression (SVR) modeling. Choosing different parameters will influence the accuracy of SVR models. This paper proposes a parameter choosing method of SVR models for time series prediction. In the light of data features of time series, the paper improves the traditional cross-validation method, and combines the improved cross-validation with epsilon-weighed SVR in order to get good parameters of models. The experiments show that the method is effective for time series prediction.
A dynamic trustiness authentication framework based on the integrity of softwarepsilas behavior is proposed in this paper. The method to extract SIBDS (Software Intended Behaviors Describing Sets) and SBAC (Software Behavior Authentication Code) from the binary executable is introduced. In the framework, when the software begin to run, it should be monitored by SBMC (Software Behavior Monitoring Center), then the real API function invoking sequence will be acquired. The framework uses the software behavior comparison algorithm to verify whether the API invoking sequence gotten from the actual behavior is in accordance with SBAC; thereby the softwarepsilas dynamic trustiness can be detected and guaranteed. The experiment results demonstrate the efficacy of the dynamic trustiness authentication framework.
Software Transactional Memory (STM) is a generic synchronization construct that enables automatic conversion of correct sequential objects into correct nonblocking concurrent objects. We investigate a novel Lightweight Snapshot-based Validation and Conflict Detection (LSVCD) algorithm for STM that provide scaling and strong consistency. In LSVCD, each transaction maintains a local snapshot version variable used to indicate the snapshot state it views. Whether the snapshot of memory observed by a transaction is consistent or not can be verified quickly by comparing lsv with Global Version Number. LSVCD can greatly reduce the cost of read and write operations, conflict detection and validation of STM. Transactions proceed without interference or contention unless they access overlapping data sets. Experimental results show that LSVCD is simple and quite competitive, and gains a notably improvements of performance over existing STM implementation.
Aiming at the product demand series with multi-dimension, small samples, nonlinearity and multi-apex in manufacturing enterprise, chaos theory is combined with support vector machine, and a kind of chaotic support vector machine named Cv-SVM is proposed. And then, a product demand forecasting method and its relevant parameter-choosing algorithm are put forward. The results of application in car demand forecasting show that the forecasting method based on Cv-SVM is effective and feasible.
The minimum error correction (MEC) model is one of the widely accepted computational model for single individual haplotype reconstruction problem, and it has been proved to be NP-complete by Lippert et al.. Qian et al. presented a particle swarm optimization (PSO) algorithm to solve the model, and the length of a particle code is equal to the number of fragments. However, there are hundreds and thousands of fragments in practical applications, the PSO algorithm based on this kind of long particle code can not obtain high reconstruction rate efficiently. In this paper, a practical heuristic algorithm based on genetic algorithm (GA) is presented to solve the problem. A kind of short chromosome code and an effective climb operator are designed for the algorithm. Experimental results indicate that the algorithm designed in this paper can get higher reconstruction rate than the PSO algorithm.
An algorithm for computing 4M-point DFT based on 4-point DFT block is developed. The new algorithm, in comparison to radix-4 FFT algorithm, requires the same number of additions and multiplications, but employs a dissimilar flow-graph. In the flow-graph of the new algorithm, the 4-point DFT blocks replace the accustomed butterfly computational networks. The new algorithm permits one 4M-point DFT to be computed using a 4-point DFT block, and the block requirements is Mtimes4M-1. Because the total number of computational requirements of directly computing a 4-point DFT is only 16 real additions, a command block and hardware block for computing 4-point DFT may be obtained. When using a processor which integrates with a fast 4-point DFT block to compute 4M-point DFT, the speed of DFT will be faster than that of radix-4 FFT. The algorithm based on 4-point DFT block will be helpful to improve the DSP technology and speed.
Query translation is an important task for cross-language information retrieval (CLIR), which aims at translating the query described in source language into target language. The approach to query translation based on bilingual dictionary is becoming the mainstream thinking because of its simplicity and the increasing availability of machine readable bilingual dictionary. However, this kind of approach faces two necessary problems that is ambiguity in translation and the incompleteness of the dictionary. This paper focuses on the first problem, and it presents three statistical models based on HowNet to resolve query translation ambiguity of CLIR: query translation selection based on semantic relation; bilingual decaying co-occurrence model and semantic decaying co-occurrence model. Through test and summarizing this paper gets the best algorithm to integrate the traits of the three models, which gradually filters and optimizes the translation.
Any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at the modest communication cost.
A novel localization algorithm for moving target in sensor networks is proposed, which is based on overlap area boundary of sensor detection. The algorithm inherits the advantage of binary sensing model that sensor nodes only need provide 0 or 1 information to represent whether detect a target or not, and improves the location precision compares to traditional centroid localization algorithm that can only locate a target position between intersection area of sensor nodes. According to the spatio-temporal continuity of the trajectory of a moving target, the algorithm determines a dynamic queue of sensor nodes those have detected the target in order, and shrinks the possible location of a target into a boundary of intersection area of all nodes in the queue. In this way, the algorithm achieves better location precision than traditional centroid localization algorithm. Results of simulation experiments prove the truth of better location precision of this algorithm. Moreover, the algorithm has the features of good expansibility and robustness by avoiding whole net time synchronization instead of local communication between nodes.
A novel approach to multi-robot cooperative map-building in complex environments is presented in this paper. The approach lets all robots operate individually and then tries to merge the different local grid maps into a single global one. Without using any pose information of the robots, the process of map merging is performed by measuring the similarity between grid maps. A distance transform and an improved genetic algorithm are used to effectively search the maximum overlap at which the local maps can be joined together. Experimental results show the feasibility and effectiveness of our approach in complex environments.
Boolean satisfiability is a NP-hard problem in computer theoretic science. There are two types of SAT solvers, random local solver and DPLL-based complete solver. Some people have proposed hybrid SAT solvers that combined the advantage of them both. They have successfully applied them to solve large or hard random SAT problems and circuit related problems. However, these solvers often find over-satisfying assignments when solving some circuit related problems. In this paper, circuit observability is considered in hybrid SAT solver, which helps reduce the overhead caused by over-satisfying and prune the searching space. The experimental results show that our hybrid SAT solver is more efficient than other solvers for large and hard circuits.
SIP-based systems inherently have NAT traversal and QoS problems because of the limited IPV4 addresses and the best-effort service on the Internet. Using relay server to relay media stream can solve NAT traversal in SIP systems, but have less scalability. In this paper, we propose a SIP+P2P architecture for SIP-based systems to solve the above problems. In this novel architecture, light weighted SIP signaling is still client/server based, but media stream is transmitted through P2P network. We embed relay service into some SIP UAs who can be peers, design a P2P overlay network to organize those peer nodes, and provide a fast and efficient relay nodes retrieving mechanism. We also present a detouring technology to select multi good performance paths in P2P overlay and switch real transmitting path between them according to the path performance. We implemented the whole design, and preliminary experiments show that our approach enhanced path reliability and QoS performance of end-to-end communications significantly.
This paper presents the design principle for integrating quality management on Web service registry developed in UDDI specification and Web service quality management system (WSQMS). WSQMS, developed by NIA can measure and collect the quality information of Web services by its agency system installed on the Web service system. Web service registry is core system for registering and searching WSDL (Web service description language). On the registry, there are no methods that users search Web services on the basis of quality information because the registry is operating without any relationship of WSQMS. So, it is required an integration method where WSQMS and registries share the quality data on the basis of classified quality data. For representing Web service quality information, we adopted the WSQDL (Web service quality description language), which published by WSQM technical committee in OASIS. In more detail, this paper also presents the scheme to compose the classification scheme for quality data and to modify the necessary data structure of the registry.
Undergraduate education quality serves as a major issue in the development of higher education. In this new era, the actual condition requires a university to construct an effective system to objectively evaluate the education quality, and therefore sustainable development can be achieved. By analyzing the connotation and characteristics of school-based evaluation, this article proposes an undergraduate education quality evaluation system constructed from school-based evaluation, aiming at making education quality evaluation become an inborn mechanism of universities and providing an applicable new method for China to carry out undergraduate education quality evaluation.
Dynamic voltage and frequency scaling (DVFS) technique is emerging in various battery-operated embedded systems to reduce the energy consumption and prolong the working life of the system. However, DVFS technology has been proved to have some direct and negative effects on the reliability of the system. Most existing schedulers of real-time tasks based on DVFS only focus on minimizing energy consumption without taking the fault-tolerant into account. To solve this problem, in this study, we developed a novel Energy-Aware Fault-Tolerant (EAFT) technique that was tailored for the real-time periodic tasks. The heuristic EAFT balances the allocation of slacks used for reducing energy consumption and used for re-executing the failed tasks. The simulation results showed that the proposed reliability-aware schemes could guarantee the system reliability and significantly save energy comparing to the existing allocating schemes.
In object-oriented software testing, a class is considered to be a basic unit of testing. The state of the objects may cause faults that cannot be easily revealed with traditional testing techniques. In this paper, we propose a new technique for class testing by using event-driven Petri nets (EDPN), which is an extended version of Petri Nets, one of techniques having the ability to analyze and test the behavior for the interaction between data members and member functions in class. We demonstrate how to specify a class specification by EDPNs and a given fault model by mutant of EDPNs, which is a theoretical model to describe the dynamic behaviors of EDPNs. A test case generation technique is presented to detect the given faults by analyzing the differences of test scenario in the dynamic behaviors of both EDPNs. The presented algorithm can select a test case that detects errors described in the fault models.
