Journal of Electrical and Computer Engineering The latest articles from Hindawi Publishing Corporation © 2016 , Hindawi Publishing Corporation . All rights reserved. Iterative Forward-Backward Pursuit Algorithm for Compressed Sensing Thu, 26 May 2016 12:51:05 +0000 It has been shown that iterative reweighted strategies will often improve the performance of many sparse reconstruction algorithms. Iterative Framework for Sparse Reconstruction Algorithms (IFSRA) is a recently proposed method which iteratively enhances the performance of any given arbitrary sparse reconstruction algorithm. However, IFSRA assumes that the sparsity level is known. Forward-Backward Pursuit (FBP) algorithm is an iterative approach where each iteration consists of consecutive forward and backward stages. Based on the IFSRA, this paper proposes the Iterative Forward-Backward Pursuit (IFBP) algorithm, which applies the iterative reweighted strategies to FBP without the need for the sparsity level. By using an approximate iteration strategy, IFBP gradually iterates to approach the unknown signal. Finally, this paper demonstrates that IFBP significantly improves the reconstruction capability of the FBP algorithm, via simulations including recovery of random sparse signals with different nonzero coefficient distributions in addition to the recovery of a sparse image. Feng Wang, Jianping Zhang, Guiling Sun, and Tianyu Geng Copyright © 2016 Feng Wang et al. All rights reserved. Face Spoof Attack Recognition Using Discriminative Image Patches Sun, 22 May 2016 07:40:26 +0000 Face recognition systems are now being used in many applications such as border crossings, banks, and mobile payments. The wide scale deployment of facial recognition systems has attracted intensive attention to the reliability of face biometrics against spoof attacks, where a photo, a video, or a 3D mask of a genuine user’s face can be used to gain illegitimate access to facilities or services. Though several face antispoofing or liveness detection methods (which determine at the time of capture whether a face is live or spoof) have been proposed, the issue is still unsolved due to difficulty in finding discriminative and computationally inexpensive features and methods for spoof attacks. In addition, existing techniques use whole face image or complete video for liveness detection. However, often certain face regions (video frames) are redundant or correspond to the clutter in the image (video), thus leading generally to low performances. Therefore, we propose seven novel methods to find discriminative image patches, which we define as regions that are salient, instrumental, and class-specific. Four well-known classifiers, namely, support vector machine (SVM), Naive-Bayes, Quadratic Discriminant Analysis (QDA), and Ensemble, are then used to distinguish between genuine and spoof faces using a voting based scheme. Experimental analysis on two publicly available databases (Idiap REPLAY-ATTACK and CASIA-FASD) shows promising results compared to existing works. Zahid Akhtar and Gian Luca Foresti Copyright © 2016 Zahid Akhtar and Gian Luca Foresti. All rights reserved. A Four Quadrature Signals’ Generator with Precise Phase Adjustment Tue, 17 May 2016 07:48:37 +0000 A four-way quadrature signals generator with precise phase modulation is presented. It consists of a phase precision regulator and a frequency divider. The phase precision regulator generates two programmable currents by controlling the conduction of the tail current sources and then changes the currents into two bias voltages which are superimposed on the clock signals to adjust the phase difference of the four quadrature signals generated by the frequency divider, making the phase difference of 90 degrees. The four quadrature signals’ generator with precise phase modulation has been implemented in a 0.18 μm mixed-signal and RF 1P6M CMOS technology. The size of the chip including the pads is . The circuit uses a supply voltage of 1.8 V, a bias current of 7.2 μA, and the bits of phase-setting input level in the design. The measured results of the four orthogonal signals’ phase error can reach ±0.1°, and the phase modulation range can reach ±3.6°. Xiushan Wu, Yanzhi Wang, Siguang An, Jianqiang Han, and Ling Sun Copyright © 2016 Xiushan Wu et al. All rights reserved. Heuristic Data Placement for Data-Intensive Applications in Heterogeneous Cloud Thu, 12 May 2016 07:00:11 +0000 Data placement is an important issue which aims at reducing the cost of internode data transfers in cloud especially for data-intensive applications, in order to improve the performance of the entire cloud system. This paper proposes an improved data placement algorithm for heterogeneous cloud environments. In the initialization phase, a data clustering algorithm based on data dependency clustering and recursive partitioning has been presented, and both the factor of data size and fixed position are incorporated. And then a heuristic tree-to-tree data placement strategy is advanced in order to make frequent data movements occur on high-bandwidth channels. Simulation results show that, compared with two classical strategies, this strategy can effectively reduce the amount of data transmission and its time consumption during execution. Qing Zhao, Congcong Xiong, and Peng Wang Copyright © 2016 Qing Zhao et al. All rights reserved. Microblog Sentiment Orientation Detection Using User Interactive Relationship Wed, 11 May 2016 14:04:25 +0000 The development and popularity of microblog have made sentiment analysis of tweets and Weibo an important research field. However, the characteristics of microblog message pose challenge for the sentiment analysis and mining. The existing approaches mostly focus on the message content and context information. In this paper, we propose a novel microblog sentiment analysis framework by incorporating the social interactive relationship factor in the content-based approach. By exploring the interactive relationship on social network based on posted messages, we build social interactive model to represent the opposition or acceptation behavior. Based on the interactive relationship model, the sentiment of microblog message with sparse emotion terms can be deduced and identified, and the sentiment uncertainty can be alleviated to some extent. Afterwards, we transform the classification problem into an optimization problem. Experimental results on Weibo data set indicate that the proposed method can outperform the baseline methods. Liang Wang, Mei Wang, Xinying Guo, and Xuebin Qin Copyright © 2016 Liang Wang et al. All rights reserved. Design of High Throughput and Cost-Efficient Data Center Networks Tue, 10 May 2016 13:30:42 +0000 Vincenzo Eramo, Xavier Hesselbach-Serra, Yan Luo, and Juan Felipe Botero Copyright © 2016 Vincenzo Eramo et al. All rights reserved. DPFFs: Direct Path Flip-Flops for Process-Resilient Ultradynamic Voltage Scaling Tue, 10 May 2016 12:06:58 +0000 We propose two master-slave flip-flops (FFs) that utilize the clocked CMOS () technique with an internal direct connection along the main signal propagation path between the master and slave latches and adopt an adaptive body bias technique to improve circuit robustness. structure improves the setup margin and robustness while providing full compatibility with the standard cell characterization flow. Further, the direct path shortens the logic depth and thus speeds up signal propagation, which can be optimized for less power and smaller area. Measurements from test circuits fabricated in 130 nm technology show that the proposed FF operates down to 60 mV, consuming 24.7 pW while improving the propagation delay, dynamic power, and leakage by 22%, 9%, and 13%, respectively, compared with conventional FFs at the iso-output-load condition. The proposed FFs are integrated into an FIR filter which successfully operates all the way down to 85 mV. Myeong-Eun Hwang and Sungoh Kwon Copyright © 2016 Myeong-Eun Hwang and Sungoh Kwon. All rights reserved. A Privacy-Preserving Outsourcing Data Storage Scheme with Fragile Digital Watermarking-Based Data Auditing Thu, 05 May 2016 16:32:10 +0000 Cloud storage has been recognized as the popular solution to solve the problems of the rising storage costs of IT enterprises for users. However, outsourcing data to the cloud service providers (CSPs) may leak some sensitive privacy information, as the data is out of user’s control. So how to ensure the integrity and privacy of outsourced data has become a big challenge. Encryption and data auditing provide a solution toward the challenge. In this paper, we propose a privacy-preserving and auditing-supporting outsourcing data storage scheme by using encryption and digital watermarking. Logistic map-based chaotic cryptography algorithm is used to preserve the privacy of outsourcing data, which has a fast operation speed and a good effect of encryption. Local histogram shifting digital watermark algorithm is used to protect the data integrity which has high payload and makes the original image restored losslessly if the data is verified to be integrated. Experiments show that our scheme is secure and feasible. Xinyue Cao, Zhangjie Fu, and Xingming Sun Copyright © 2016 Xinyue Cao et al. All rights reserved. Business Information Exchange System with Security, Privacy, and Anonymity Wed, 04 May 2016 10:00:50 +0000 Business Information Exchange is an Internet Secure Portal for secure management, distribution, sharing, and use of business e-mails, documents, and messages. It has three applications supporting three major types of information exchange systems: secure e-mail, secure instant messaging, and secure sharing of business documents. In addition to standard security services for e-mail letters, which are also applied to instant messages and documents, the system provides innovative features of privacy and full anonymity of users and their locations, actions, transactions, and exchanged resources. In this paper we describe design, implementation, and use of the system. Sead Muftic, Nazri bin Abdullah, and Ioannis Kounelis Copyright © 2016 Sead Muftic et al. All rights reserved. An Efficient Electronic English Auction System with a Secure On-Shelf Mechanism and Privacy Preserving Wed, 04 May 2016 08:31:22 +0000 With the rapid development of the Internet, electronic commerce has become more and more popular. As an important element of e-commerce, many Internet companies such as Yahoo! and eBay have launched electronic auction systems. However, like most electronic commerce products, safety is an important issue that should be addressed. Many researchers have proposed secure electronic auction mechanisms, but we found that some of them do not exhibit the property of unlinkability, which leads to the leakage of users’ privacy. Considering the importance of privacy preservation, we have designed a new auction mechanism. Through symmetrical key establishment in the registration phase, all messages transmitted over the Internet would be protected and, meanwhile, achieve the property of unlinkability. The security analysis and performance analysis show that our protocol fulfills more security properties and is more efficient for implementation compared with recent works. Hong Zhong, Song Li, Ting-Fang Cheng, and Chin-Chen Chang Copyright © 2016 Hong Zhong et al. All rights reserved. Protecting Clock Synchronization: Adversary Detection through Network Monitoring Sat, 30 Apr 2016 11:12:48 +0000 Nowadays, industrial networks are often used for safety-critical applications with real-time requirements. Such applications usually have a time-triggered nature with message scheduling as a core property. Scheduling requires nodes to share the same notion of time, that is, to be synchronized. Therefore, clock synchronization is a fundamental asset in real-time networks. However, since typical standards for clock synchronization, for example, IEEE 1588, do not provide the required level of security, it raises the question of clock synchronization protection. In this paper, we identify a way to break synchronization based on the IEEE 1588 standard, by conducting a man-in-the-middle (MIM) attack followed by a delay attack. A MIM attack can be accomplished through, for example, Address Resolution Protocol (ARP) poisoning. Using the AVISPA tool, we evaluate the potential to perform a delay attack using ARP poisoning and analyze its consequences showing both that the attack can, indeed, break clock synchronization and that some design choices, such as a relaxed synchronization condition mode, delay bounding, and using knowledge of environmental conditions, can make the network more robust/resilient against these kinds of attacks. Lastly, a Configuration Agent is proposed to monitor and detect anomalies introduced by an adversary performing attacks targeting clock synchronization. Elena Lisova, Marina Gutiérrez, Wilfried Steiner, Elisabeth Uhlemann, Johan Åkerberg, Radu Dobrin, and Mats Björkman Copyright © 2016 Elena Lisova et al. All rights reserved. Virtual Networking Performance in OpenStack Platform for Network Function Virtualization Wed, 27 Apr 2016 12:29:45 +0000 The emerging Network Function Virtualization (NFV) paradigm, coupled with the highly flexible and programmatic control of network devices offered by Software Defined Networking solutions, enables unprecedented levels of network virtualization that will definitely change the shape of future network architectures, where legacy telco central offices will be replaced by cloud data centers located at the edge. On the one hand, this software-centric evolution of telecommunications will allow network operators to take advantage of the increased flexibility and reduced deployment costs typical of cloud computing. On the other hand, it will pose a number of challenges in terms of virtual network performance and customer isolation. This paper intends to provide some insights on how an open-source cloud computing platform such as OpenStack implements multitenant network virtualization and how it can be used to deploy NFV, focusing in particular on packet forwarding performance issues. To this purpose, a set of experiments is presented that refer to a number of scenarios inspired by the cloud computing and NFV paradigms, considering both single tenant and multitenant scenarios. From the results of the evaluation it is possible to highlight potentials and limitations of running NFV on OpenStack. Franco Callegati, Walter Cerroni, and Chiara Contoli Copyright © 2016 Franco Callegati et al. All rights reserved. High-Speed Transmission and Mass Data Storage Solutions for Large-Area and Arbitrarily Structured Fabrication through Maskless Lithography Tue, 26 Apr 2016 16:37:07 +0000 This paper presents the implementation aspects and design of high-speed data transmission in laser direct-writing lithography. With a single field programmable gate array (FPGA) chip, mass data storage management, transmission, and synchronization of each part in real-time were implemented. To store a massive amount of data and transmit data with high bandwidth, a serial advanced technology attachment (SATA) intellectual property (IP) was developed on Xilinx Virtex-6 FPGA. In addition, control of laser beam power, collection of status read back data of the lithography laser through an analog-to-digital converter, and synchronization of the positioning signal were implemented on the same FPGA. A data structure for each unit with a unique exposure dose and other necessary information was established. Results showed that the maximum read bandwidth (240 MB/s) and maximum write bandwidth (200 MB/s) of a single solid-state drive conform to the data transmission requirement. The total amount of data meets the requirement of a large-area diffractive element approximately 102 cm2. The throughput has been greatly improved at meters per second or square centimeter per second. And test results showed that data transmission meets the requirement of the experiment. Yu Lu, Wei Wu, and Ke-yi Wang Copyright © 2016 Yu Lu et al. All rights reserved. An Efficient Node Localization Approach with RSSI for Randomly Deployed Wireless Sensor Networks Tue, 26 Apr 2016 06:08:09 +0000 An efficient path planning approach in mobile beacon localization for the randomly deployed wireless sensor nodes is proposed in this paper. Firstly, in order to improve localization accuracy, the weighting function based on the distance between nodes is constructed. Moreover, an iterative multilateration algorithm is also presented to avoid decreasing the localization accuracy. Furthermore, a path planning algorithm based on grid scan which can traverse entirely in sensor field is described. At the same time, the start conditions of localization algorithm are also proposed to improve localization accuracy. To evaluate the proposed path planning algorithm, the localization results of beacon nodes randomly deployed in sensor field are also provided. The proposed approach can provide the deployment uniformly of virtual beacon nodes among the sensor fields and the lower computational complexity of path planning compared with method which utilizes only mobile beacons on the basis of a random movement. The performance evaluation shows that the proposed approach can reduce the beacon movement distance and the number of virtual mobile beacon nodes by comparison with other methods. Xihai Zhang, Junlong Fang, and Fanfeng Meng Copyright © 2016 Xihai Zhang et al. All rights reserved. Server Resource Dimensioning and Routing of Service Function Chain in NFV Network Architectures Sun, 24 Apr 2016 12:42:44 +0000 The Network Function Virtualization (NFV) technology aims at virtualizing the network service with the execution of the single service components in Virtual Machines activated on Commercial-off-the-shelf (COTS) servers. Any service is represented by the Service Function Chain (SFC) that is a set of VNFs to be executed according to a given order. The running of VNFs needs the instantiation of VNF instances (VNFI) that in general are software components executed on Virtual Machines. In this paper we cope with the routing and resource dimensioning problem in NFV architectures. We formulate the optimization problem and due to its NP-hard complexity, heuristics are proposed for both cases of offline and online traffic demand. We show how the heuristics works correctly by guaranteeing a uniform occupancy of the server processing capacity and the network link bandwidth. A consolidation algorithm for the power consumption minimization is also proposed. The application of the consolidation algorithm allows for a high power consumption saving that however is to be paid with an increase in SFC blocking probability. V. Eramo, A. Tosti, and E. Miucci Copyright © 2016 V. Eramo et al. All rights reserved. Strengthening MT6D Defenses with LXC-Based Honeypot Capabilities Wed, 20 Apr 2016 13:24:54 +0000 Moving Target IPv6 Defense (MT6D) imparts radio-frequency hopping behavior to IPv6 networks by having participating nodes periodically hop onto new addresses while giving up old addresses. Our previous research efforts implemented a solution to identify and acquire these old addresses that are being discarded by MT6D hosts on a local network besides being able to monitor and visualize the incoming traffic on these addresses. This was essentially equivalent to forming a darknet out of the discarded MT6D addresses, but the solution presented in the previous research effort did not include database integration for it to scale and be extended. This paper presents a solution with a new architecture that not only extends the previous solution in terms of automation and database integration but also demonstrates the ability to deploy a honeypot on a virtual LXC (Linux Container) on-demand based on any interesting traffic pattern observed on a discarded address. The proposed architecture also allows an MT6D host to query the solution database for network activity on its relinquished addresses as a JavaScript Object Notation (JSON) object. This allows an MT6D host to identify suspicious activity on its discarded addresses and strengthen the MT6D scheme parameters accordingly. We have built a proof-of-concept for the proposed solution and analyzed the solution’s feasibility and scalability. Dileep Basam, J. Scot Ransbottom, Randy Marchany, and Joseph G. Tront Copyright © 2016 Dileep Basam et al. All rights reserved. A Fusion Face Recognition Approach Based on 7-Layer Deep Learning Neural Network Wed, 20 Apr 2016 13:10:47 +0000 This paper presents a method for recognizing human faces with facial expression. In the proposed approach, a motion history image (MHI) is employed to get the features in an expressive face. The face can be seen as a kind of physiological characteristic of a human and the expressions are behavioral characteristics. We fused the 2D images of a face and MHIs which were generated from the same face’s image sequences with expression. Then the fusion features were used to feed a 7-layer deep learning neural network. The previous 6 layers of the whole network can be seen as an autoencoder network which can reduce the dimension of the fusion features. The last layer of the network can be seen as a softmax regression; we used it to get the identification decision. Experimental results demonstrated that our proposed method performs favorably against several state-of-the-art methods. Jianzheng Liu, Chunlin Fang, and Chao Wu Copyright © 2016 Jianzheng Liu et al. All rights reserved. Spatial Circular Granulation Method Based on Multimodal Finger Feature Wed, 13 Apr 2016 07:00:15 +0000 Finger-based personal identification has become an active research topic in recent years because of its high user acceptance and convenience. How to reliably and effectively fuse the multimodal finger features together, however, has still been a challenging problem in practice. In this paper, viewing the finger trait as the combination of a fingerprint, finger vein, and finger-knuckle-print, a new multimodal finger feature recognition scheme is proposed based on granular computing. First, the ridge texture features of FP, FV, and FKP are extracted using Gabor Ordinal Measures (GOM). Second, combining the three-modal GOM feature maps in a color-based manner, we then constitute the original feature object set of a finger. To represent finger features effectively, they are granulated at three levels of feature granules (FGs) in a bottom-up manner based on spatial circular granulation. In order to test the performance of the multilevel FGs, a top-down matching method is proposed. Experimental results show that the proposed method achieves higher accuracy recognition rate in finger feature recognition. Jinfeng Yang, Zhen Zhong, Guimin Jia, and Yanan Li Copyright © 2016 Jinfeng Yang et al. All rights reserved. Cloud Multidomain Access Control Model Based on Role and Trust-Degree Tue, 12 Apr 2016 11:18:04 +0000 In order to solve the problem of access control among different security domains in cloud networks, this paper presents an access control model based on role and trust-degree. The model combines role-based access control and trust-based access control. The role assessment weights are defined based on the user’s role classes, and the trust-degree is calculated according to the role assessment weights and the role’s behavior. In order to increase the accuracy of access control, the model gives the concept and calculation methods of feedback trust-degree. To achieve fine-grained access control, the model introduces direct trust-degree, recommendation trust-degree, and feedback trust-degree, all of which participate in comprehensive trust-degree by adjusting their weights. A simulation experiment was conducted in the LAN environment, and a web system was used to construct an access control model with multisecurity domains in the experiment. The experimental results demonstrate that our model has higher security, expansibility, and flexibility. Lixia Xie and Chong Wang Copyright © 2016 Lixia Xie and Chong Wang. All rights reserved. Power Consumption Based Android Malware Detection Wed, 06 Apr 2016 06:52:15 +0000 In order to solve the problem that Android platform’s sand-box mechanism prevents security protection software from accessing effective information to detect malware, this paper proposes a malicious software detection method based on power consumption. Firstly, the mobile battery consumption status information was obtained, and the Gaussian mixture model (GMM) was built by using Mel frequency cepstral coefficients (MFCC). Then, the GMM was used to analyze power consumption; malicious software can be classified and detected through classification processing. Experiment results demonstrate that the function of an application and its power consumption have a close relationship, and our method can detect some typical malicious application software accurately. Hongyu Yang and Ruiwen Tang Copyright © 2016 Hongyu Yang and Ruiwen Tang. All rights reserved. Finger Vein Recognition Using Optimal Partitioning Uniform Rotation Invariant LBP Descriptor Wed, 06 Apr 2016 06:51:22 +0000 As a promising biometric system, finger vein identification has been studied widely and many relevant researches have been proposed. However, it is hard to extract a satisfied finger vein pattern due to the various vein thickness, illumination, low contrast region, and noise existing. And most of the feature extraction algorithms rely on high-quality finger vein database and take a long time for a large dimensional feature vector. In this paper, we proposed two block selection methods which are based on the estimate of the amount of information in each block and the contribution of block location by looking at recognition rate of each block position to reduce feature extraction time and matching time. The specific approach is to find out some local finger vein areas with low-quality and noise, which will be useless for feature description. Local binary pattern (LBP) descriptors are proposed to extract the finger vein pattern feature. Two finger vein databases are taken to test our algorithm performance. Experimental results show that proposed block selection algorithms can reduce the feature vector dimensionality in a large extent. Bang Chao Liu, Shan Juan Xie, and Dong Sun Park Copyright © 2016 Bang Chao Liu et al. All rights reserved. Hybrid Intrusion Detection System for DDoS Attacks Sun, 03 Apr 2016 14:25:13 +0000 Distributed denial-of-service (DDoS) attacks are one of the major threats and possibly the hardest security problem for today’s Internet. In this paper we propose a hybrid detection system, referred to as hybrid intrusion detection system (H-IDS), for detection of DDoS attacks. Our proposed detection system makes use of both anomaly-based and signature-based detection methods separately but in an integrated fashion and combines the outcomes of both detectors to enhance the overall detection accuracy. We apply two distinct datasets to our proposed system in order to test the detection performance of H-IDS and conclude that the proposed hybrid system gives better results than the systems based on nonhybrid detection. Özge Cepheli, Saliha Büyükçorak, and Güneş Karabulut Kurt Copyright © 2016 Özge Cepheli et al. All rights reserved. SVM Intrusion Detection Model Based on Compressed Sampling Mon, 28 Mar 2016 06:31:45 +0000 Intrusion detection needs to deal with a large amount of data; particularly, the technology of network intrusion detection has to detect all of network data. Massive data processing is the bottleneck of network software and hardware equipment in intrusion detection. If we can reduce the data dimension in the stage of data sampling and directly obtain the feature information of network data, efficiency of detection can be improved greatly. In the paper, we present a SVM intrusion detection model based on compressive sampling. We use compressed sampling method in the compressed sensing theory to implement feature compression for network data flow so that we can gain refined sparse representation. After that SVM is used to classify the compression results. This method can realize detection of network anomaly behavior quickly without reducing the classification accuracy. Shanxiong Chen, Maoling Peng, Hailing Xiong, and Xianping Yu Copyright © 2016 Shanxiong Chen et al. All rights reserved. Cognition Cloud Model for Next Generation Mobile Internet: Communication, Control, and Application Mon, 28 Mar 2016 06:10:56 +0000 Yong Jin, Chaobo Yan, and James Nightingale Copyright © 2016 Yong Jin et al. All rights reserved. Subsurface Geobody Imaging Using CMY Color Blending with Seismic Attributes Thu, 24 Mar 2016 11:39:39 +0000 Recently, ideas of color blending have brought the enlightenment for subsurface geobody imaging in petroleum engineering. In this paper, we present this approach of CMY color blending and its application in subsurface geobody characterization by using seismic attributes data. The first step is to calculate three types of seismic attributes based on the Hilbert transform algorithm, including envelop, instantaneous phase, and instantaneous frequency. Then scale the three attributes and combine them together using CMY color model in three-dimensional environment, with each attribute corresponding to one primary color channel. Adjust the scale and offset for each color component and then mix them optimally to create one color-blended volume. The blended volume in CMY mode has plenty of geological information coming from the three input attributes, resulting in high resolution and accurate image for subsurface geobodies. Applications show good performances in buried channels, caves, and faults imaging. Based on the blended slice, the geological targets can be easily but accurately interpreted and depicted. Jianhua Cao, Xiankun Zhang, Yan Wang, and Qi Zhao Copyright © 2016 Jianhua Cao et al. All rights reserved. Analysis and Improvement of Key Distribution Scheme for Secure Group Communication Wed, 23 Mar 2016 09:56:28 +0000 In a secure group communication, messages between a group coordinator and members are protected by session keys. If a group’s membership changes, the session keys should be updated to insure forward secrecy and backward secrecy. Zhou and Huang proposed a key-updated scheme based on ciphertext-policy attribute encryption algorithm to improve the security of key-update mechanism, but their scheme is vulnerable: a malicious group member may send forged key-update messages to control the group. In this paper, we analyze the vulnerability in Zhou and Huang’s scheme and propose an enhanced scheme. In our scheme, only the group initiator can update group keys and the verification of key-update mechanism is improved to prevent malicious insiders from controlling the group. We also give a security and performance analysis of our scheme. Jia Ning Luo and Ming Hour Yang Copyright © 2016 Jia Ning Luo and Ming Hour Yang. All rights reserved. Plant Leaf Recognition through Local Discriminative Tangent Space Alignment Wed, 16 Mar 2016 12:48:12 +0000 Manifold learning based dimensionality reduction algorithms have been payed much attention in plant leaf recognition as the algorithms can select a subset of effective and efficient discriminative features in the leaf images. In this paper, a dimensionality reduction method based on local discriminative tangent space alignment (LDTSA) is introduced for plant leaf recognition based on leaf images. The proposed method can embrace part optimization and whole alignment and encapsulate the geometric and discriminative information into a local patch. The experiments on two plant leaf databases, ICL and Swedish plant leaf datasets, demonstrate the effectiveness and feasibility of the proposed method. Chuanlei Zhang, Shanwen Zhang, and Weidong Fang Copyright © 2016 Chuanlei Zhang et al. All rights reserved. Detection and Visualization of Android Malware Behavior Mon, 14 Mar 2016 13:21:12 +0000 Malware analysts still need to manually inspect malware samples that are considered suspicious by heuristic rules. They dissect software pieces and look for malware evidence in the code. The increasing number of malicious applications targeting Android devices raises the demand for analyzing them to find where the malcode is triggered when user interacts with them. In this paper a framework to monitor and visualize Android applications’ anomalous function calls is described. Our approach includes platform-independent application instrumentation, introducing hooks in order to trace restricted API functions used at runtime of the application. These function calls are collected at a central server where the application behavior filtering and a visualization take place. This can help Android malware analysts in visually inspecting what the application under study does, easily identifying such malicious functions. Oscar Somarriba, Urko Zurutuza, Roberto Uribeetxeberria, Laurent Delosières, and Simin Nadjm-Tehrani Copyright © 2016 Oscar Somarriba et al. All rights reserved. Accurate Load Modeling Based on Analytic Hierarchy Process Mon, 14 Mar 2016 06:37:14 +0000 Establishing an accurate load model is a critical problem in power system modeling. That has significant meaning in power system digital simulation and dynamic security analysis. The synthesis load model (SLM) considers the impact of power distribution network and compensation capacitor, while randomness of power load is more precisely described by traction power system load model (TPSLM). On the basis of these two load models, a load modeling method that combines synthesis load with traction power load is proposed in this paper. This method uses analytic hierarchy process (AHP) to interact with two load models. Weight coefficients of two models can be calculated after formulating criteria and judgment matrixes and then establishing a synthesis model by weight coefficients. The effectiveness of the proposed method was examined through simulation. The results show that accurate load modeling based on AHP can effectively improve the accuracy of load model and prove the validity of this method. Zhenshu Wang, Xiaohui Jiang, Shaorun Bian, Yangyang Ma, and Bowen Fan Copyright © 2016 Zhenshu Wang et al. All rights reserved. Performance Analysis of a DEKF for Available Bandwidth Measurement Sun, 28 Feb 2016 16:26:48 +0000 The paper presents a characterisation analysis of a measurement algorithm based on a Discrete-time Extended Kalman Filter (DEKF), which has recently been proposed for the estimation and tracking of end-to-end available bandwidth. The analysis is carried out by means of simulations for different rates of variations of the available bandwidth and permits assessing the performance of the measurement algorithm for different values of the filter parameters, that is, the covariance matrixes of the measurement and process noise. Diego Santoro and Michele Vadursi Copyright © 2016 Diego Santoro and Michele Vadursi. All rights reserved.