2012 Vol. 21, No. 3

Display Method:
An ESD-Aware 2.4 GHz PA Design for WLAN Application
SHI Zitao, CHENG Yuhua, WANG Albert, WANG Yangyuan
2012, 21(3): 389-394.
Abstract(345) PDF(1830)
Electrostatic discharge (ESD) protection has become an emerging challenge for Radio frequency (RF) Integrated circuits (IC). This paper reports the design and optimization of an ESD-aware 2.4GHz Power amplifier (PA) circuit in a 0.18μm RFCMOS technology. A mixed-mode ESD simulation-design method and an RF ESD characterization technique are used to accurately characterize and minimize ESD-induced parasitic effects. Significant improvement can be observed by applying this ESD-aware design technique in several areas, such as gain, linearity, and power-added efficiency.
Context-Aware Task Allocation for Quick Collaborative Responses
SUN Yuqing, Matthias Farwick, Patrick C.K. Hung, Dickson K.W. Chiu, JI Guangjun
2012, 21(3): 395-402.
Abstract(363) PDF(1205)
Under some emergencies, persons are required to arrive quickly at the scene and collaborate on sensitive tasks. To ensure effective performance of these tasks and be compliant with business regulations, user context should be considered and security requirements are desired. In this paper, we tackle this challenging problem of quick collaborative response from the view of task allocation with user authorization. The considered Quickresponse task allocation problem (QTAP) answers how to find a user-task allocation solution, the group of qualified users who can fastest arrive at the scene to fulfill the collaborative processes and satisfy the required security constraints. We study the computational complexity of this problem and solve it by the reduction to the well-studied scheduling problem. We further discuss an important extension of QTAP that supports task dependencies and propose an algorithm to solve it.
Group Competitive Model of Optimal Node Selection Based on Service Evaluation
LIU Shufen, HU Changhong
2012, 21(3): 403-408.
Abstract(319) PDF(1155)
An optimal node competitive selection model is proposed to improve the accuracy and real-time of users’ optimal service selection. By analyzing hierarchical service model which is based on hierarchical data node, IP-domain based network users’ grouping model and time-sharing service evaluation based Region-users grouping model and definition are presented, a service evaluation based progressive grouping model is constructed, node competitive mechanism is introduced. On condition that load balancing is ensured, optimal node selection problem is solved, a selection model simulation is completed using MATLAB R2009a. Results show that, users can get optimal service through optimal node competitive selection model, compared to traditional models, users who can get optimal service grow linearly, the growth account for about 10% in all users. The efficiency of the model can satisfy users’ need.
Airport Bird-strike Risk Assessment Model with Grey Clustering Evaluation Method
WANG Jiakang, NING Huansheng, CHEN Weishi, LI Jing, WAN Jian, HE Wei
2012, 21(3): 409-413.
Abstract(334) PDF(1478)
Bird strike, a common aviation accident, endangers aircrafts. A real-time bird-strike risk assessment system is a guarantee for airport safe management. This paper adapts grey clustering evaluation into a new real-time method with expert experience, Bird-strike risk assessment model (BRAM). Timeliness is a characteristic and bird-strike expert experience improves the effectiveness of BRAM. Bird-strike experts are invited to grade the importance of different risk indices, which are essential in BRAM. The inputs of the model are bird information and aircraft information. Afterwards, BRAM outputs bird-strike risk level timely and dynamically. Meanwhile, bird-strike management advices are also outputted in accordance with the risk level, and delivered to air traffic control of the airport.
Compiler-Assisted Value Correlation for Indirect Branch Prediction
TAN Mingxing, LIU Xianhua, ZHANG Jiyu, TONG Dong, CHENG Xu
2012, 21(3): 414-418.
Abstract(293) PDF(881)
Indirect branch prediction is important to boost instruction-level parallelism in modern processors. Previous indirect branch predictions usually cannot achieve high performance for the ineffectiveness of correlated information. This paper proposes the Compilerassisted value correlation (CVC), a hardware/software cooperative indirect branch prediction scheme. The key is to identify effective value correlation based on program substructures. A compiler algorithm is introduced to identify the effective value correlation based on three program substructures: virtual function calls, switch-case statements and function pointer calls. The compiler-identified value correlation is transferred to the dynamic predictor by extending the instruction set architecture. At runtime, the processor relies on a low-complexity Correlated value buffer (CVB) to maintain the compiler-identified value correlation and to guide the target address prediction for those indirect branch instructions. Our evaluations show that CVC prediction can significantly improve the performance with little extra hardware support over the traditional BTB predictor and the state-of-the-art VBBI prediction.
Degree of Spiking Neural P Systems Without Delay
JIANG Keqin, SHI Xiaolong
2012, 21(3): 419-424.
Abstract(265) PDF(965)
Spiking neural P systems are a class of distributed parallel computing models inspired from the way neurons communicate with each other by means of electrical impulses (called “spikes”). In this paper, we continue the research of normal forms for spiking neural P systems. Specifically, we prove that the degree of spiking neural P systems without delay can be decreased to two without losing the computational completeness (both in the generating and accepting modes).
Combining Control Structure and Composition Condition for Web Services Reliability Prediction
XIE Chunli, LI Bixin, LIAO Li, WANG Xifeng
2012, 21(3): 425-429.
Abstract(325) PDF(1216)
The different results of composition conditions make different impact on the reliability of composite services, in this paper, to improve the prediction accuracy of reliability for composite services, we proposed a reliability prediction model for composite services combining control-structure (e.g. sequence, if/switch, while, repeatuntil, foreach and flow) and composition condition. With this method, we firstly discussed the reliability of composition conditions and the influence of different control structure on composite services. And We presented an Extended reliability block diagram (ERBD) to describe the reliability of composite services. In the ERBD, composition conditions are regarded as atomic services and the reliability of composite services are evaluated according to their structures. Then, we designed an experiment to support our reliability model. The experimental results show that our model can obtain better reliability prediction accuracy than traditional model.
RNS-to-Binary Converter for New Four-Moduli Set {2n - 1, 2n, 2n+1 - 1, 2n+1 + 2n - 1}
QUAN Si, PANWeitao, XIE Yuanbin, HAO Yue
2012, 21(3): 430-434.
Abstract(278) PDF(1179)
In this paper, a new four-moduli set {2n - 1, 2n, 2n+1 - 1, 2n+1 + 2n - 1} is proposed. The new moduli set choice because of a fast modulo 2n+1 + 2n - 1 adder has been proposed in literature. In order to work out the reverse converter for this moduli set, we introduce the technique for modulo 2n+1+2n-1 of a negative number and modulo 2n+1+2n-1 multiplication of a residue number by 2 and design a multi-operand modulo 2n+1+2n-1 adder. The proposed reverse converter based on mixed radix conversion and does not require any ROM. The comparisons for conversion time as well as area requirements between our reverse converter and the reverse converters for several other four-moduli sets are presented.
A Novel Survivability Evaluation Model Facing Information System
ZHANG Lejun, GUO Lin, ZHANG Jianpei, YANG Jing
2012, 21(3): 435-438.
Abstract(262) PDF(926)
As a new direction in computer security, survivability evaluation provides us with a new way to conduct the research of the computer security. Traditional survivability formal model and analysis belong to expressions of the concept. If there is no future work to be developed, the model can not make quality and quantity analysis. This paper presents the modeling method of information system survivability evaluation based on stochastic Petri net which combine formal description of system working flow with survivability evaluation modeling, and respectively describes the SPN modeling method of service disabled, recovery, modules redundancy and survivability attributes. Experiments prove that the SPN modeling of survivability can provide theoretical basis and guide for designing a survivable information system.
HiSCA: Overcoming the Limitation of Clustered Unicore Processors Through Hardware/Software Codesign
CHEN Hu, CHEN Shuming, CHEN Xiaowen, LIU Sheng
2012, 21(3): 439-444.
Abstract(301) PDF(1059)
The partitioning of resources such as pipelines and register files among clusters has been proven to be an effective way to improve performance and scalability. However, improvements are limited by traditional binary instruction encoding schemes and centralized instruction execution control mechanism. Meanwhile, clustered processors may come at the cost of performance degradation due to limited data locality resulted from a lack of available registers and functional units. This paper introduces a Highly scalable clustered architecture (HiSCA) to improve the scalability and performance of clustered processors. The hardware/software instruction encoding scheme of HiSCA splits the instruction stream into chains of instructions (packs) and encodes common information within the same packs in dedicated instruction words, thus reducing the amount of information encoded in instruction words. The pipeline of HiSCA, which features in-order issuing, out-of-order execution and parallel but in-order commitment, release instruction issuing from the heavy burden of dynamic scheduling, and allows functional units to fetch data and manage their own execution. HiSCA scales efficiently to 32 clusters with 1024 general purpose registers. Experimental results also show that, for a 4- cluster/8-issue configuration, HiSCA can achieve an average of 13.3% performance speedup and a 4.6% improvement in frequency with minimal hardware overhead, as compared to a traditional clustered processor with nearly the same hardware complexity.
Towards Efficient K-Dominant Skyline Computation in CSCW
2012, 21(3): 445-448.
Abstract(272) PDF(954)
Considering benefits of different collaborators, cooperative work usually faces the challenge to make a trade-off decision upon multiple criterions. K-dominant skyline, a novel database query technology, may return appropriate optimal choices and play as a solution. To reduce intensive comparisons between objects in skyline computation, we propose a novel sorting-based algorithm named Sorted cumulative algorithm. Furthermore, to meet the requirement of distributed collaborative environment, we also address Parallel SCA, which accelerates the computation based on some data partitioning techniques. Extensive experiments are conducted to confirm the superior efficiency of the proposed methods against existing ones, especially in the context of high dimensional datasets.
Quantum-Behaved Particle Swarm Optimization Algorithm with Adaptive Mutation Based on q-Gaussian Distribution
2012, 21(3): 449-452.
Abstract(330) PDF(1284)
Aiming at the drawback of being easily trapped into the local optima and premature convergence in quantum-behaved particle swarm optimization algorithm, quantum-behaved particle swarm optimization algorithm with adaptive mutation based on q-Gaussian distribution is proposed. q-Gaussian mutation operator is applied to the mean best position of particles to overcome the drawback of premature convergence caused by loss of diversity in the population. In the evolution of population, adaptive adjustment of the nonextensive entropic index q balances exploration and exploitation. The simulation results of testing four standard benchmark functions and traveling salesman problem show that quantum-behaved particle swarm optimization algorithm with adaptive mutation based on q-Gaussian distribution has best optimization performance and robustness.
A Formal Model of Collaborative Discussion for Problem-Solving
LIU Xiaoping, TANG Yiming, SHEN Guanting, CHEN Xin
2012, 21(3): 453-459.
Abstract(373) PDF(1178)
The efficiency and quality of current collaborative discussion for problem-solving can hardly satisfy the practical demands. To solve this problem, a formal model of collaborative discussion for problem-solving is established. First, to express thinking transformation in the process of collaborative discussion, the model of PTMM (Participant-driven two-directional mind map) is proposed, and then the formal definitions and operations for PTMM are provided. Second, the solutionspace theory of PTMM is investigated. To let the solution be clearer, the concept and generation process of STMM (Solution-driven two-directional mind map) are given, which are derived from the PTMM. Third, inspired by the rhombus thought in extension theory, the RSM (Rhombus sequence model) based on PTMMand STMMis obtained and shown dynamically by visual means. Lastly, a practical example of collaborative discussion is shown, demonstrating that the RSM is able to effectively enlighten the thinking and promote the efficiency together with quality of collaborative discussion.
A Global K-modes Algorithm for Clustering Categorical Data
BAI Tian, C.A. Kulikowski, GONG Leiguang, YANG Bin, HUANG Lan, ZHOU Chunguang
2012, 21(3): 460-465.
Abstract(467) PDF(4728)
In this paper, a new Global k-modes (GKM) algorithm is proposed for clustering categorical data. The new method randomly selects a sufficiently large number of initial modes to account for the global distribution of the data set, and then progressively eliminates the redundant modes using an iterative optimization process with an elimination criterion function. Systematic experiments were carried out with data from the UCI Machine learning repository. The results and a comparative evaluation show a high performance and consistency of the proposed method, which achieves significant improvement compared to other well-known k-modes-type algorithms in terms of clustering accuracy.
An Adaptive Fuzzy Markov Random Field Model for Change Detection
GAO Fei, CHEN Bona, SUN Jinping
2012, 21(3): 466-470.
Abstract(280) PDF(1084)
This paper proposes a change detection algorithm based on a novel adaptive fuzzy Markov random field model. The purpose is to improve the adaptability and accuracy of change detection algorithm through a nonparametric adaptive framework. We formulate the change detection problem as a constraint optimization problem according to maximum a posterior probability criterion, and then design a non-parametric energy function which can adaptively adjust contributions of contextual information and observed data to labeling decision making. Finally, the gradient projection optimization method is applied to the scheme to obtain optimal change detection result. Theoretical analysis and experimental results show the validity of the proposed algorithm.
An Extended Multi-scale Principal Component Analysis Method and Application in Anomaly Detection
WEN Chenglin, ZHOU Funa, WEN Chuanbo, CHEN Zhiguo
2012, 21(3): 471-476.
Abstract(366) PDF(1189)
Multi-scale principal component analysis (MSPCA) can well implement multivariate information extracting on different scales, but theory foundation of MSPCA is still an open question. Using spectral decomposition of a matrix and multi-scale representation of spectral as well as multi-scale transform of a signal, an Extended multi-scale PCA (EMSPCA) method is proposed to analyze the reason why multi-scale detection method does well than single scale method. Under the uniform projection frame of EMSPCA, the relation between multi-scale detection model and those on each scale is established. Thus multi-scale anomaly detection can be implemented without establishing another new PCA model of the reconstructed data. Simulation shows the efficiency of EMSPCA anomaly detection algorithm.
A Non-Statistical Reinstatement Algorithm for Orientation Field of Incomplete Fingerprint
JING Xiaojun, ZHANG Bo, LIU Xinjing, WANG Dong
2012, 21(3): 477-480.
Abstract(315) PDF(1119)
Fingerprint orientation is the key information in fingerprint enhancement and matching. According to the problem of incomplete fingerprint orientation, a novel algorithm of fingerprint orientation reinstatement is proposed based on Local binary pattern (LBP) and mutual information function. Firstly, mutual information of fingerprint orientation is computed. Secondly, the feature vector is defined for incomplete area classification by Support vector machines (SVM). Then, the fingerprint orientation field of the incomplete area is re-computed and measured by LBP and mutual information function. For orientation reinstatement, LBP is used to measure the similarity of incomplete and complete area, while the mutual information function is used to measure correlation and competition of the neighborhood. Additionally, fuzzy criterion is proposed to assign different weights for neighborhood block and incomplete block for modifying orientation. As a result, the modified fingerprint orientation is used for post-processing. And the performance is shown in the experimental and proves the efficiency and reliability of our algorithm.
Accelerometer-based Gait Authentication via Neural Network
SUN Hu, YUAN Tao, LI Xiaopeng, HU Yu
2012, 21(3): 481-484.
Abstract(289) PDF(1184)
Gait authentication based on accelerometers is a nonintrusive biometric measurement. It is a novel and feasible way to enhance the security of portable electronic devices. To boost authentication performances, a decision-level data fusion algorithm via neural network is proposed in this paper. The proposed algorithm fuses acceleration signals in different directions and classical approaches for matching gait patterns such as correlation, Euclidean distance etc. In our experiments, data sets for training and test consist of 17, 20 subjects separately. The Equal error rate (EER) is cut to 0.82%, which is much lower than other proposed approaches so far.
The Heuristic Algorithms for Selecting the Parameters of Support Vector Machine for Classification
LANG Rongling, DENG Xiaole, GAO Fei
2012, 21(3): 485-488.
Abstract(365) PDF(1146)
The performance of Gaussian kernel Support vector machine (SVM) for classification is determined by scale parameter σ of Gaussian kernel function and error penalty parameter C. A heuristic approach is proposed to tune the parameters of SVM in this paper. We firstly select σ, and then search the optimal value of C with given σ. By viewing selection of σ as a recognition problem, we determine the reasonable range of σ using Fisher statistical expression. In selection of C, the search interval is chosen according to the Sequential minimal optimization (SMO) procedure, and the searching procedure is terminated with considering the balance between generalization capability and approximation capability of SVM. The proposed approach is evaluated with a series of real-world data sets.
Parallel Length-based Matching Architecture for High Throughput Multi-Pattern Matching
WANG Xiaofei, HU Chengchen, TANG Yi, ZHANG Ting, WU Chunming, LIU Bin, WANG Xiaojun
2012, 21(3): 489-494.
Abstract(411) PDF(1423)
Multi-pattern matching is a key technique for network security applications such as Network intrusion detection/protection systems (NIDS/NIPS). Deterministic finite automaton (DFA) is widely used for multipattern matching, while the link bandwidth and the traffic of the Internet are rapidly increasing, high performance and low storage cost DFA-based NIDS is strongly required. In this paper, we propose a parallel Length-based matching (LBM) architecture to increase the throughput without extra memory cost. The basic idea is to process multiple characters between some specific tags in parallel. We propose a multiple hash functions solution to reduce the possibility of false positive. The evaluation shows that our parallel architecture can reduce nearly 55% processing time with less memory consumption than the traditional DFA.
Reaction-Diffusion Equation Based Image Denoising Algorithm
ZHAO Xueqing, WANG Xiaoming, ZHANG Lichen
2012, 21(3): 495-499.
Abstract(335) PDF(1949)
A Reaction-diffusion equation based image denoising algorithm (RDEID) is proposed for the removal of noises in corrupted images. By exploiting reactiondiffusion equation, the isotropic diffusion is performed to noisy pixels, the processed image is quantized and denoised. As a result, the details of image are effectively preserved during removing noises. Extensive experimental results show that the proposed algorithm has better performance in terms of evaluation metrics, such as Peak signal-to-noise ratio (PSNR), Image fidelity (IF) and Mean square error of noise suppression (MSENS).
Dynamic Reliability Analysis Model for Fault-tolerant Network Routing
WANG Bin, WU Chunming, YANG Qiang, QIAN Yaguan, WANG Xiaonan
2012, 21(3): 500-504.
Abstract(359) PDF(1081)
The appropriate selection of redundant routing paths to promote fault-tolerant capability is a key issue for enhancing reliability of routing algorithms. In this paper it is a dynamic reliability analysis model that presented for fault-tolerant routing algorithms. Through theoretical analysis, the direct relationship between routing and its dynamic reliability is established. Through this model it can effectively assess the performance of existing fault-tolerant routing algorithms which provides an efficient model for the routing algorithm design.
Automatic Pairing 2-D Direction Estimation Using Uniformly but Sparsely Spaced Electromagnetic Vector Sensor
LIU Zhaoting, LIU Zhong
2012, 21(3): 505-509.
Abstract(259) PDF(1169)
A new polynomial-rooting-based algorithm with two parallel uniform linear arrays of dipole-triads is proposed for estimating two dimensional (2-D) Directions of arrival (DOAs) of multiple source signals. The proposed algorithm derives the direction cosine estimates along xaxis and y-axis, successively, from polynomial roots and eigenvectors associated with the roots. When the intervector sensor spacing exceeds a half-wavelength, the derived direction cosine estimates are ambiguous. Fortunately, the eigenvectors can also be straightforwardly used to yield dipole-triad's manifold estimates, thus the ambiguities can be resolved using the manifold estimates. Unlike other existing ESPRIT-based algorithm, our algorithm can achieve automatic pairing without any additional processing. Numerical examples are presented to verify the effectiveness of the proposed method.
A Dynamically Reconfigurable VLSI Architecture for H.264 Integer Transforms
HONG Qi, CAO Wei, TONG Jiarong
2012, 21(3): 510-514.
Abstract(269) PDF(1168)
The 4 × 4 integer transforms have been adopted in the MPEG-4 AVC /H.264 standard. In this paper, two novel signal flow graphs of the 4 × 4 forward and inverse transforms for H.264 are deduced. A new dynamically reconfigurable architecture without transpose memory for the integer transforms is proposed on the basis of the new SFGs. In comparison with the existing designs, the number of computing elements can be cut down through dynamically reconfiguration in our design. Our design is implemented with 0.18μm CMOS technology. Under a clock frequency of 200 MHz, this architecture allows the real-time processing of 4096×2048 at 30 fps with the area cost of 5140 gates and the power dissipation of 15.64mW.
3-D Medical Image Interpolation via Multi-Resolution Directional Correspondence
WANG Lingfeng, YU Zeyun, PAN Chunhong
2012, 21(3): 515-518.
Abstract(294) PDF(874)
In this paper, we present a novel 3-D image interpolation method with high-quality feature preservation and low computational cost. The optimal direction of each voxel on the slices to be inserted is found by minimizing the smoothed directional correspondence using the Markov random field optimization approach. A multi-resolution scheme is employed to further reduce the memory consumption and computational costs as well as improve the interpolation accuracy. Extensive experiments are performed on medical image slices to evaluate the proposed approach, showing significant improvements in both accuracy and efficiency, as compared with the traditional interpolation techniques.
Improving the Lower Bound on Linear Complexity of the Sequences Generated by Nonlinear Filtering
ZHANG Yin, LIN Dongdai, LIU Meicheng
2012, 21(3): 519-522.
Abstract(284) PDF(1230)
Linear complexity is an important property for secure keystream sequences. In this paper, we study binary sequences generated by nonlinear filters on m-sequences with the method of Discrete Fourier transform (DFT). We focus on the certain class of equidistant filters and give an improved lower bound on the linear complexity of the filtered sequences.
A Pruning Based Continuous RkNN Query Algorithm for Large k
WANG Shengsheng, CHAI Sheng, LV Qiannan
2012, 21(3): 523-527.
Abstract(263) PDF(1083)
Reverse k-nearest neighbor (RkNN) query is a hot-spot in spatio-temporal database. With the developing of mobile devices, continuous RkNN query becomes more and more important. Most of the previous methods use the two-step (filter-refinement) processing. However, for large k, the amount of calculation becomes very heavy, especially in the filter step. This is not acceptable for most mobile devices. This paper presents a novel algorithm for continuous RkNN queries based on pruning heuristics. The experiments show that the processing time of our method is still acceptable for most mobile devices when k is large.
A Service-centric Networking Scheme for Wireless Sensor Networks
LUO Hong, LIN Jieqiong, SUN Yan
2012, 21(3): 528-534.
Abstract(300) PDF(1094)
Many networking schemes in Wireless sensor networks (WSNs) directly dependent on physical network topology and hence result in hot-spot and service flexibility problems. In this paper, we propose a novel service-centric networking scheme. With a number of brokers placed in the sensing domain, we first establish an energy-efficient and service-centric network structure through a networking algorithm based on routing distance, and then maintain it via events management approaches. This service network consists of multi-level recursive subnets, and it is distributed and self-organized. Rather than normal clustering network, in this network, service is regarded as the unit of node data and is forwarded within the service network level by level through the extended publish/subscribe communication model. Further more, through the use of high-performance brokers, we have enhanced the in-network processing ability to reduce redundant data. Simulation results show that the scheme can efficiently locally process the services, balance energy consumption, and thus extend the lifetime of network and expand the applicability of system.
Single-channel Speech Separation by l0 Optimization Using Quasi-KLT Bases
GUO Haiyan, YANG Zhen, ZHU Weiping, YE Lei
2012, 21(3): 535-540.
Abstract(246) PDF(1095)
This paper deals with single-channel speech separation. First, it is proved that when the sparse bases of the signal sources satisfy certain conditions, all the sources can be perfectly separated from a single mixture by l0 optimization. Then, a special case where the single mixture is generated by two independent speech sources is studied in more detail. It is revealed that the ideal quasi- KLT bases constructed from the original sources satisfy the sufficient conditions for perfect separation of mixed signals. Considering the fact that the ideal quasi-KLT bases cannot be obtained in practice, template-matching based quasi- KLT bases generated from the single mixture are also proposed to perform single-channel speech separation. Finally, simulation results demonstrating the effective performance of single-channel separation of two speech sources by l0 optimization using the template-matching based quasi-KLT bases are presented.
End-to-end Congestion Control for TCP-friendly Flows with Variable Data Rates
JIANG Ming, YANG Qiang, WU Chunming, LI Ziqiang, MIAO Yuting
2012, 21(3): 541-546.
Abstract(464) PDF(1041)
This paper presents recent new findings on the network resource utilization bias phenomenon in the context of TCP-friendly rate control (TFRC) protocol based data flows. It has been found that data flows with lower data rate could yield more than twice of the link utilization than flows with higher data rates under the circumstance that multiple dta flows compete network resource in a shared bottleneck link, e.g. the access link bandwidth is greater than the bottleneck bandwidth. The study is carried out through extensive numerical experiments and a set of key results are presented. In this paper, we highlight and analysis the underlying reasons of the obtained results, and proposed a solution and assessed its performance through simulations. The aspects which could be further improved in the proposed solution have also been discussed.
Generic Side-channel Distinguisher Based on Kolmogorov-Smirnov Test: Explicit Construction and Practical Evaluation
LIU Jiye, ZHOU Yongbin, YANG Shuguo, FENG Dengguo
2012, 21(3): 547-553.
Abstract(297) PDF(1285)
Construction and evaluation of efficient distinguishers with broad generality is one fundamental problem in the area of side-channel cryptanalysis. Due to their capabilities to deal with general correlations, MIA-like distinguishers have received wide attention from academia. In this paper, we conduct a comprehensive comparison investigation of existing MIA-like distinguishers, and then propose a new generic side-channel distinguisher based on partial Kolmogorov-Smirnov test, namely PKS distinguisher. Theoretical analysis and experimental attacks unanimously justify that PKS distinguisher works remarkably well with both linear and non-linear leakage models. Specifically, PKS distinguisher has obvious advantages over existing MIA-like distinguishers in terms of both success rate and guessing entropy. Additionally, lower computational complexity of PKS distinguisher further shows its better applicability than MIA-like distinguishers.
Secure Verifiable Active Access Control for Medical Sensor Networks
ZHANG Lichen, WANG Xiaoming, DOU Wenyang, ZHAO Xueqing
2012, 21(3): 554-558.
Abstract(287) PDF(1041)
Active access control is important yet difficult to implement in Medical sensor networks (MSNs). In this paper, a Secure verifiable active access control (SVAAC) scheme is proposed to enhance activeness and security of access control for MSNs. In the SVAAC scheme, based on event triggeration mechanism, access control policies can change adaptively, and active authorization and access control can be guaranteed??and the confidentiality and integrity of authorizations are also ensured.
Characteristics of Electric Charges Carried by Dust Particles and Their Effects on Connector Contact Failure
GAO Jinchun, XIE Gang
2012, 21(3): 559-565.
Abstract(276) PDF(2754)
Dust contamination is one of the major causes of electrical contact failure in the electronic system. This paper describes the characteristics of electric charges carried by dust particles and their effects on connector failure. A Millikan testing method was used for measuring the electric charges. The results show that the variation of electric charges carried by dust particles is located in a band region, and the trend of charges can be expressed as a third order equation. The morphology and surface seem to be the major factors which influence the electric charge. It is found that dust particles carry negative charges or positive charges, these particles will be attracted to both electric contact surfaces in connector respectively, and thereby increasing the probability of connector failure. The selective deposition of particles was found on electric contact surface. The failed connectors were investigated by using SEM/EDS (Scanning electron microscope and Energy dispersive X-ray spectroscopy) and protection from dust particles was recommended.
On the Security of Double-Block-Length Hash Functions with Rate 1
GONG Zheng, LUO Yiyuan, LAI Xuejia, CHEN Kefei
2012, 21(3): 566-570.
Abstract(243) PDF(930)
The security of double-block-length hash functions with rate 1, which are based on a block cipher with a block length of n bits and a key length of 2n bits, was analyzed by Satoh et al. and Hirose. In this paper, we reconsider the security of this general class of hash functions (named FDBL-II for brevity). The new counter-examples and attacks are presented on FDBL-II, which reveal some flaws in the necessary conditions proposed by Satoh et al. and Hirose. Moreover, our analysis shows that all rate-1 hash functions in FDBL-II fail to be optimally (second) preimage resistant. Finally, the necessary conditions are revised for ensuring that a subclass of hash functions in FDBL-II can be optimally secure against collision attacks.
Lifetime Optimization for Multi-Source Multi-Relay Cooperative OFDM Systems
PANG Lihua, LI Jiandong, ZHANG Yang
2012, 21(3): 571-574.
Abstract(287) PDF(1162)
This communication presents a resource allocation strategy for maximizing the lifetime of Amplifyand- forward (AF) dual-hop cooperative OFDM networks. The high computational complexity for optimization necessitates our study of suboptimal approaches. Our centralized scheme is implemented in two steps. Specifically, during each transmission interval, source-relay selection and subcarrier pairing can be decided according to channel state information of the relay links and residual energy information at each terminal. Next, energy-aware power loading can be solved by employing standard Lagrange techniques. Numerical examples verify the effectiveness of our proposal.
QoS-Oriented Scalable Video Transmission Using Cooperative Relay
XIAO Hongjiang, JI Xiangyang, DAI Qionghai
2012, 21(3): 575-578.
Abstract(231) PDF(1085)
For single-antenna video communications, the potential unreliability of direct link and the delay constraints of video are two primary factors that influence the reconstructed video quality. A novel cooperative transmission scheme is thus proposed to tackle this problem. Specifically, the source and relay jointly retransmit the corrupted packets by suitable Space-time block codes (STBCs), which raises the capacity utilization of random channel. Additionally, a Quality-of-service (QoS) mapping strategy smartly loads the scalable video to the underlying STBCs, and guarantees that more important video packets obtain higher transmission priorities and stronger protections. Simulation results demonstrate the effectiveness of our proposed scheme.
Network Traffic Anomaly Detection Based on Maximum Entropy Model
QIAN Yaguan, WU Chunming, YANG Qiang, WANG Bin
2012, 21(3): 579-582.
Abstract(412) PDF(1946)
In this paper, a novel network traffic anomaly detection approach by adopting the Machine learning (ML) method based on Maximum entropy (ME) principle has been exploited. The final feature set is generated by extracting features from 1% of a public released dataset KDD 99 with Correlation-based feature selection (CFS) algorithm. The Bound-constrained limited memory variable metric (BLMVM) algorithm is employed to estimate the parameters to obtain an exponential model. The model is further studied in comparison with other ML methods. The proposed approach is assessed through a set of numerical experiments and the result demonstrates that the ME model exhibits enhanced classification efficiency for network traffic anomaly, even under the condition of training data with limited size.