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Linearly Homomorphic Signatures from Lattices Comput. J. (IF 1.077) Pub Date : 2020-11-27 Lin C, Xue R, Yang S, et al.
AbstractLinearly homomorphic signatures (LHSs) allow any entity to linearly combine a set of signatures and to provide authentication service for the corresponding (combined) data. The public key of the current known LHSs from lattices in the standard model requires $O(l)$ matrices and $O(k)$ vectors, where $l$ is the length of file identifier and $k$ is the maximum data set size that linear functions
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Detecting Cognitive Features of Videos Using EEG Signal Comput. J. (IF 1.077) Pub Date : 2021-01-11 Qasem Qananwah; Ali Mohammad Alqudah; Moh’d Alodat; Ahmad Dagamseh; Oliver Hayden
Electroencephalography (EEG) emerged as a highly relevant signal to human emotion, brain diagnosing and brain–computer interfaces (BCI) applications. In this paper, the EEG signal is used to evaluate the cognitive response of subjects during watching test video clips. The measurements are performed with 25 subjects using eight channels while simultaneously running the video clips. The β and γ waves
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Positioning and Categorizing Mass Media Using Reaction Emojis on Facebook Comput. J. (IF 1.077) Pub Date : 2020-12-26 Ming-Hung Wang
With the rapid growth of social network services, a paradigm shift in communication between media organizations and the audience has occurred. Numerous mass media agencies established fan pages on social platforms, such as Facebook, Twitter and Instagram, to disseminate breaking news, promote reports and interact with their audience. In this study, we leverage the reaction emojis delivered from users
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Improved File-injection Attacks on Searchable Encryption Using Finite Set Theory Comput. J. (IF 1.077) Pub Date : 2020-12-26 Gaoli Wang; Zhenfu Cao; Xiaolei Dong
Searchable encryption (SE) allows the cloud server to search over the encrypted data and leak information as little as possible. Most existing efficient SE schemes assume that the leakage of search pattern and access pattern is acceptable. A series of work was proposed, instructing malicious users to use this leakage to come up with attacks. Especially, with a devastating attack proposed by Zhang et
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Stable Communities Detection Method for Temporal Multiplex Graphs: Heterogeneous Social Network Case Study Comput. J. (IF 1.077) Pub Date : 2020-12-22 Wala Rebhi; Nesrine Ben Yahia; Narjès Bellamine Ben Saoud
Multiplex graphs have been recently proposed as a model to represent high-level complexity in real-world networks such as heterogeneous social networks where actors could be characterized by heterogeneous properties and could be linked with different types of social interactions. This has brought new challenges in community detection, which aims to identify pertinent groups of nodes in a complex graph
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Model-Driven Simulation of Elastic OCCI Cloud Resources Comput. J. (IF 1.077) Pub Date : 2020-12-22 Mehdi Ahmed-Nacer; Slim Kallel; Faiez Zalila; Philippe Merle; Walid Gaaloul
Deploying a cloud configuration in a real cloud platform is mostly cost- and time- consuming, as large number of cloud resources have to be rented for the time needed to run the configuration. Thereafter, cloud simulation tools are used as a cheap alternative to test cloud configuration. However, most of the existing cloud simulation tools require extensive technical skills and do not support simulation
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Salient Object Detection Based on Multiscale Segmentation and Fuzzy Broad Learning Comput. J. (IF 1.077) Pub Date : 2020-12-21 Xiao Lin; Zhi-Jie Wang; Lizhuang Ma; Renjie Li; Mei-E Fang
Saliency detection has been a hot topic in the field of computer vision. In this paper, we propose a novel approach that is based on multiscale segmentation and fuzzy broad learning. The core idea of our method is to segment the image into different scales, and then the extracted features are fed to the fuzzy broad learning system (FBLS) for training. More specifically, it first segments the image
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Detecting Spam Product Reviews in Roman Urdu Script Comput. J. (IF 1.077) Pub Date : 2020-12-21 Naveed Hussain; Hamid Turab Mirza; Faiza Iqbal; Ibrar Hussain; Mohammad Kaleem
In recent years, online customer reviews have become the main source to determine public opinion about offered products and services. Therefore, manufacturers and sellers are extremely concerned with customer reviews, as these can have a direct impact on their businesses. Unfortunately, there is an increasing trend to write spam reviews to promote or demote targeted products or services. This practice
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Improved Key Recovery Attacks on Simplified Version of K2 Stream Cipher Comput. J. (IF 1.077) Pub Date : 2020-12-21 Sudong Ma; Jie Guan
The K2 stream cipher, designed for 32-bit words, is an ISO/IEC 18033 standard and is listed as a recommended algorithm used by the Japanese government in the CRYPTREC project. The main feature of the K2 algorithm is the use of a dynamic feedback control mechanism between the two linear feedback shift registers, which makes the analysis of the K2 algorithm more difficult. In this paper, for its simplified
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The Notion of Transparency Order, Revisited Comput. J. (IF 1.077) Pub Date : 2020-07-03 Li H, Zhou Y, Ming J, et al.
AbstractWe revisit the definition of transparency order (TO) and that of modified transparency order (MTO) as well, which were proposed to measure the resistance of substitution boxes (S-boxes) against differential power analysis (DPA). We spot a definitional flaw in original TO, which is proved to significantly affect the soundness of TO. Regretfully, MTO overlooks this flaw, yet it happens to incur
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Improved Meet-in-the-Middle Attacks on Reduced-Round Deoxys-BC-256 Comput. J. (IF 1.077) Pub Date : 2020-06-22 Liu Y, Shi B, Gu D, et al.
AbstractIn ASIACRYPT 2014, Jean et al. proposed the authentication encryption scheme Deoxys, which is one of the third-round candidates in CAESAR competition. Its internal block cipher is called Deoxys-BC that adopts the tweakey frame. Deoxys-BC has two versions of the tweakey size that are 256 bits and 384 bits, denoted by Deoxys-BC-256 and Deoxys-BC-384, respectively. In this paper, we revaluate
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New Automatic Search Method for Truncated-Differential Characteristics Application to Midori, SKINNY and CRAFT Comput. J. (IF 1.077) Pub Date : 2020-06-15 Ebrahimi Moghaddam A, Ahmadian Z.
AbstractIn this paper, using Mixed-Integer Linear Programming, a new automatic search tool for truncated differential characteristic is presented. Our method models the problem of finding a maximal probability truncated differential characteristic, being able to distinguish the cipher from a pseudo-random permutation. Using this method, we analyze Midori64, SKINNY64/X and CRAFT block ciphers, for all
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A New Framework of IND-CCA Secure Public Key Encryption with Keyword Search Comput. J. (IF 1.077) Pub Date : 2020-06-10 Ma S, Huang Q.
AbstractIn the era of cloud computing, public key encryption with keyword search (PEKS) is an extremely useful cryptographic tool for searching on encryption data, whose strongest security notion is indistinguishability encryption against chosen ciphertext attack (ind-cca). Adballa et al. presented a transformation from identity based encryption (IBE) to PEKS in the Theory of Cryptography Conference
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Reusable Fuzzy Extractor Based on the LPN Assumption Comput. J. (IF 1.077) Pub Date : 2020-06-08 Li Y, Liu S, Gu D, et al.
AbstractA fuzzy extractor derives uniformly random strings from noisy sources that are neither reliably reproducible nor uniformly random. The basic definition of fuzzy extractor was first formally introduced by Dodis et al. and has achieved various applications in cryptographic systems. However, it has been proved that a fuzzy extractor could become totally insecure when the same noisy random source
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Public-Key Encryption In The Standard Model Against Strong Leakage Adversary Comput. J. (IF 1.077) Pub Date : 2020-06-03 Alawatugoda J.
AbstractOver the years, security against adaptively chosen-ciphertext attacks (CCA2) is considered as the strongest security definition for public-key encryption schemes. With the uprise of side-channel attacks, new security definitions are proposed, addressing leakage of secret keys together with the standard CCA2 definition. Among the new security definitions, security against continuous and after-the-fact
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Cost- and Time-Based Data Deployment for Improving Scheduling Efficiency in Distributed Clouds Comput. J. (IF 1.077) Pub Date : 2020-09-29 Chunlin Li; Yihan Zhang; Xiaomei Qu; Youlong Luo
In recent years, with the continuous development of internet of things and cloud computing technologies, data intensive applications have gotten more and more attention. In the distributed cloud environment, the access of massive data is often the bottleneck of its performance. It is very significant to propose a suitable data deployment algorithm for improving the utilization of cloud server and the
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A Blockchain-Based Framework for IoT Data Monetization Services Comput. J. (IF 1.077) Pub Date : 2020-09-24 Muhammad Salek Ali; Massimo Vecchio; Fabio Antonelli
Within internet of things (IoT) research, there is a growing interest in leveraging the decentralization properties of blockchains, towards developing IoT authentication and authorization mechanisms that do not inherently require centralized third-party intermediaries. This paper presents a framework for sharing IoT data in a decentralized and private-by-design manner in exchange for monetary services
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Efficient Group ID-Based Encryption With Equality Test Against Insider Attack Comput. J. (IF 1.077) Pub Date : 2020-09-23 Yunhao Ling; Sha Ma; Qiong Huang; Ximing Li; Yijian Zhong; Yunzhi Ling
ID-based encryption with equality test (IBEET) allows a tester to compare ciphertexts encrypted under different public keys for checking whether they contain the same message. In this paper, we first introduce group mechanism into IBEET and propose a new primitive, namely group ID-based encryption with equality test (G-IBEET). With the group mechanism: (1) group administrator can authorize a tester
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Corrigendum to: Multi-Swarm Cuckoo Search Algorithm with Q-Learning Model Comput. J. (IF 1.077) Pub Date : 2020-09-23 Juan Li; Dan-dan Xiao; Ting Zhang; Chun Liu; Yuan-xiang Li; Gai-ge Wang
AbstractFunctional encryption (FE) can provide a fine-grained access control on the encrypted message. Therefore, it has been applied widely in security business. The previous works about functional encryptions most focused on the deterministic functions. The randomized algorithm has wide application, such as securely encryption algorithms against chosen ciphertext attack, privacy-aware auditing. Based
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Transportation Index Computation: A Development Theme Mining-Based Approach Comput. J. (IF 1.077) Pub Date : 2020-09-15 Gang Han; Menggang Li; Yiduo Mei; Deming Li
In order to comprehensively evaluate the achievements of the 'Belt and Road' in integrated transportation, researchers need to optimize the method of generating evaluation indices and construct the framework structure of the 'Belt and Road' transportation index system. This paper used GDELT database as data source and obtained full text data of English news in 25 countries along ‘the Belt and Road’
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An Opinion Spread Prediction Model With Twitter Emotion Analysis During Algeria’s Hirak Comput. J. (IF 1.077) Pub Date : 2020-09-14 Ahlem Drif; Khalil Hadjoudj
Social media is believed to have played a central role in the mobilization of Algerian citizens to peaceful protest against their country’s corrupt regime. Since no one foresaw these protests (called ‘The Revolution of Smiles’ or ‘The Hirak Movement’), this research conducted social media analysis to elicit vital insights about both the intensity of sentiment and the influence of social media on this
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Retrieving Semantic Image Using Shape Descriptors and Latent-Dynamic Conditional Random Fields Comput. J. (IF 1.077) Pub Date : 2020-09-12 Mahmoud Elmezain; Hani M Ibrahem
This paper introduces a new approach to semantic image retrieval using shape descriptors as dispersion and moment in conjunction with discriminative classifier model of latent-dynamic conditional random fields (LDCRFs). The target region is firstly localized via the background subtraction model. Then the features of dispersion and moments are employed to k-means clustering to extract object’s feature
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The Conditional Reliability Evaluation of Data Center Network BCDC Comput. J. (IF 1.077) Pub Date : 2020-09-08 Mengjie Lv; Baolei Cheng; Jianxi Fan; Xi Wang; Jingya Zhou; Jia Yu
As the number of servers in a data center network (DCN) increases, the probability of server failures is significantly increased. Traditional connectivity is an important metric to measure the reliability of DCN. However, the traditional connectivity of a DCN based on the condition of arbitrary faulty servers is generally lower. Therefore, it is important to increase the connectivity of a DCN by adding
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Detection of 2D and 3D Video Transitions Based on EEG Power Comput. J. (IF 1.077) Pub Date : 2020-09-07 Negin Manshouri; Mesut Melek; Temel Kayıkcıoglu
Despite the long and extensive history of 3D technology, it has recently attracted the attention of researchers. This technology has become the center of interest of young people because of the real feelings and sensations it creates. People see their environment as 3D because of their eye structure. In this study, it is hypothesized that people lose their perception of depth during sleepy moments
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A Machine Learning-Based Model to Evaluate Readability and Assess Grade Level for the Web Pages Comput. J. (IF 1.077) Pub Date : 2020-09-07 Muralidhar Pantula; K S Kuppusamy
Evaluating readability of web documents has gained attention due to several factors such as improving the effectiveness of writing and to reach a wider spectrum of audience. Current practices in this direction follow several statistical measures in evaluating readability of the document. In this paper, we have proposed a machine learning-based model to compute readability of web pages. The minimum
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Related Blogs’ Summarization With Natural Language Processing Comput. J. (IF 1.077) Pub Date : 2020-09-05 Niyati Baliyan; Aarti Sharma
There is plethora of information present on the web, on a given topic, in different forms i.e. blogs, articles, websites, etc. However, not all of the information is useful. Perusing and going through all of the information to get the understanding of the topic is a very tiresome and time-consuming task. Most of the time we end up investing in reading content that we later understand was not of importance
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Querying Tenuous Group in Attributed Networks Comput. J. (IF 1.077) Pub Date : 2020-08-29 Yang Li; Heli Sun; Liang He; Jianbin Huang; Jiyin Chen; Hui He; Xiaolin Jia
Finding groups in networks is very common in many practical applications, and most work mainly focus on dense groups. However, in scenarios like reviewer selection or weak social friends recommendation, we need to emphasize the privacy of individuals or minimize the possibility of information dissemination. So the internal relationship between individuals should be as tenuous as possible, but existing
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S-DolLion-MSVNN: A Hybrid Model for Developing the Super-Resolution Image From the Multispectral Satellite Image Comput. J. (IF 1.077) Pub Date : 2020-08-28 Anil B Gavade; Vijay S Rajpurohit
Super-resolution offers a new image with high resolution from the low-resolution (LR) image that is highly employed for the numerous remote sensing applications. Most of the existing techniques for formation of the super-resolution image exhibit the loss of quality and deviation from the original multi-spectral LR image. Thus, this paper aims at proposing an efficient super-resolution method using
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Machine Learning Model for Multi-View Visualization of Medical Images Comput. J. (IF 1.077) Pub Date : 2020-08-27 Nitesh Pradhan; Vijaypal Singh Dhaka; Geeta Rani; Himanshu Chaudhary
Imaging techniques such as X-ray, computerized tomography scan and magnetic resonance imaging are useful in the correct diagnosis of a disease or deformity in the organ. Two-dimensional imaging techniques such as X-ray give a clear picture of simple bone deformity but fail in visualizing multiple fractures in a bone. Moreover, these lack in providing a multi-angle view of a bone. Three-dimensional
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A Modern View on Forward Security Comput. J. (IF 1.077) Pub Date : 2020-08-24 Colin Boyd; Kai Gellert
Forward security ensures that compromise of entities today does not impact the security of cryptographic primitives employed in the past. Such a form of security is regarded as increasingly important in the modern world due to the existence of adversaries with mass storage capabilities and powerful infiltration abilities. Although the idea of forward security has been known for over 30 years, current
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Work-Efficient Parallel Non-Maximum Suppression Kernels Comput. J. (IF 1.077) Pub Date : 2020-08-21 David Oro; Carles Fernández; Xavier Martorell; Javier Hernando
In the context of object detection, sliding-window classifiers and single-shot convolutional neural network (CNN) meta-architectures typically yield multiple overlapping candidate windows with similar high scores around the true location of a particular object. Non-maximum suppression (NMS) is the process of selecting a single representative candidate within this cluster of detections, so as to obtain
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Multichannel Ordered Contention MAC Protocol For Underwater Wireless Sensor Networks Comput. J. (IF 1.077) Pub Date : 2020-08-20 Alak Roy; Nityananda Sarma
Recent advancement in hardware and the availability of bandwidth open scope for multichannel communication in underwater wireless sensor networks. Utilizing multiple channels for data and control packets in bursty traffic networks can reduce collisions due to several contending nodes. The paper presents a synchronous reservation-based multichannel ordered contention MAC protocol for deep underwater
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Breast Cancer Diagnosis Using Multi-Stage Weight Adjustment In The MLP Neural Network Comput. J. (IF 1.077) Pub Date : 2020-08-19 Amin Rezaeipanah; Gholamreza Ahmadi
Breast cancer is the most common kind of cancer, which is the cause of death among the women worldwide. There is evidence that shows that the early detection and treatment can increase the survival rate of patients who suffered this disease. Therefore, this paper proposes an automatic breast cancer diagnosis technique using a genetic algorithm for simultaneous feature selection and parameter optimization
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Wrapper-Enabled Feature Selection and CPLM-Based NARX Model for Stock Market Prediction Comput. J. (IF 1.077) Pub Date : 2020-08-19 Dattatray P Gandhmal; K Kumar
The prices in the stock market are dynamic in nature, thereby pretend as a hectic challenge to the sellers and buyers in predicting the trending stocks for the future. To ensure effective prediction of the stock market, the chronological penguin Levenberg–Marquardt-based nonlinear autoregressive network (CPLM-based NARX) is employed, and the prediction is devised on the basis of past and the recent
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Similarity of Sentences With Contradiction Using Semantic Similarity Measures Comput. J. (IF 1.077) Pub Date : 2020-08-19 M Krishna Siva Prasad; Poonam Sharma
Short text or sentence similarity is crucial in various natural language processing activities. Traditional measures for sentence similarity consider word order, semantic features and role annotations of text to derive the similarity. These measures do not suit short texts or sentences with negation. Hence, this paper proposes an approach to determine the semantic similarity of sentences and also presents
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A Genetically Based Combination of Visual Saliency and Roughness for FR 3D Mesh Quality Assessment: A Statistical Study Comput. J. (IF 1.077) Pub Date : 2020-08-17 Anass Nouri; Christophe Charrier; Olivier Lézoray
In this paper, we present a full-reference quality assessment metric based on the information of visual saliency. The saliency information is provided under the form of degrees associated to each vertex of the surface mesh. From these degrees, statistical attributes reflecting the structures of the reference and distorted meshes are computed. These are used by four comparisons functions genetically
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An Adaptively Secure Functional Encryption for Randomized Functions Comput. J. (IF 1.077) Pub Date : 2020-08-08 Muhua Liu; Ping Zhang
Functional encryption (FE) can provide a fine-grained access control on the encrypted message. Therefore, it has been applied widely in security business. The previous works about functional encryptions most focused on the deterministic functions. The randomized algorithm has wide application, such as securely encryption algorithms against chosen ciphertext attack, privacy-aware auditing. Based on
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KORGAN: An Efficient PKI Architecture Based on PBFT Through Dynamic Threshold Signatures Comput. J. (IF 1.077) Pub Date : 2020-08-12 Murat Yasin Kubilay; Mehmet Sabir Kiraz; Haci Ali Mantar
During the past decade, several misbehaving certificate authorities (CAs) have issued fraudulent TLS certificates allowing man-in-the-middle (MITM) kinds of attacks that result in serious security incidents. In order to avoid such incidents, Yakubov et al. ((2018) A blockchain-based PKI management framework. NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium, Taipei, Taiwan, April
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Lost In Translation: Exposing Hidden Compiler Optimization Opportunities Comput. J. (IF 1.077) Pub Date : 2020-08-07 Kyriakos Georgiou; Zbigniew Chamski; Andres Amaya Garcia; David May; Kerstin Eder
Existing iterative compilation and machine learning-based optimization techniques have been proven very successful in achieving better optimizations than the standard optimization levels of a compiler. However, they were not engineered to support the tuning of a compiler’s optimizer as part of the compiler’s daily development cycle. In this paper, we first establish the required properties that a technique
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Security Analysis of the First Certificateless Proxy Signature Scheme Against Malicious-But-Passive KGC Attacks Comput. J. (IF 1.077) Pub Date : 2020-08-05 Xi-Jun Lin; Qihui Wang; Lin Sun; Zhen Yan; Peishun Liu
Recently, Yang et al. proposed the first certificateless proxy signature scheme against malicious-but-passive key generation center (MKGC) attacks. They proved that their scheme can resist the MKGC attacks in the standard model. In this paper, we point out that their scheme cannot achieve this security because the adversary can forge valid signatures.
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Improved Tactile Perception of 3D Geometric Bumps Using Coupled Electrovibration and Mechanical Vibration Stimuli Comput. J. (IF 1.077) Pub Date : 2020-08-05 Xiaoying Sun; Chen Zhang; Guohong Liu
At present, the tactile perception of 3D geometric bumps (such as sinusoidal bumps, Gaussian bumps, triangular bumps, etc.) on touchscreens is mainly realized by mapping the local gradients of rendered virtual surfaces to lateral electrostatic friction, while maintaining the constant normal feedback force. The latest study has shown that the recognition rate of 3D visual objects with electrovibration
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Interpolation Attacks on Round-Reduced Elephant, Kravatte and Xoofff Comput. J. (IF 1.077) Pub Date : 2020-08-05 Haibo Zhou; Rui Zong; Xiaoyang Dong; Keting Jia; Willi Meier
We introduce an interpolation attack using the Moebius Transform. This can reduce the time complexity to get a linear system of equations for specified intermediate state bits, which is general to cryptanalysis of some ciphers with update function of low algebraic degree. Along this line, we perform an interpolation attack against Elephant-Delirium, a round 2 submission of the ongoing national institute
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A Cotton Disease Diagnosis Method Using a Combined Algorithm of Case-Based Reasoning and Fuzzy Logic Comput. J. (IF 1.077) Pub Date : 2020-08-05 Yuhong Dong; Zetian Fu; Stevan Stankovski; Yaoqi Peng; Xinxing Li
In this study, a cotton disease diagnosis method that uses a combined algorithm of case-based reasoning (CBR) and fuzzy logic was designed and implemented. It focuses on the prevention, diagnosis and control of diseases affecting cotton production in China. Conventional methods of disease diagnosis are primarily based on CBR with reference to user-provided symptoms; however, in most cases, user-provided
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Subgraph Reliability of Alternating Group Graph With Uniform and Nonuniform Vertex Fault-Free Probabilities Comput. J. (IF 1.077) Pub Date : 2020-08-05 Yanze Huang; Limei Lin; Li Xu
As the size of a multiprocessor system grows, the probability that faults occur in this system increases. One measure of the reliability of a multiprocessor system is the probability that a fault-free subsystem of a certain size still exists with the presence of individual faults. In this paper, we use the probabilistic fault model to establish the subgraph reliability for |$AG_n$|, the |$n$|-dimensional
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An Energy-Efficient Step-Counting Algorithm for Smartphones Comput. J. (IF 1.077) Pub Date : 2020-08-04 Runze Yang; Jian Song; Baoqi Huang; Wuyungerile Li; Guodong Qi
Step counting is not only the key component of pedometers (which is a fundamental service on smartphones), but is also closely related to a range of applications, including motion monitoring, behavior recognition, indoor positioning and navigation. Due to the limited battery capacity of current smartphones, it is of great value to reduce the energy consumption of such a popular service. Therefore,
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Improving Matsui’s Search Algorithm For The Best Differential/Linear Trails And Its Applications For DES, DESL And GIFT Comput. J. (IF 1.077) Pub Date : 2020-08-04 Fulei Ji; Wentao Zhang; Tianyou Ding
Automatic search methods have been widely used for cryptanalysis of block ciphers, especially for the most classic cryptanalysis methods—differential and linear cryptanalysis. However, the automatic search methods, no matter based on MILP, SMT/SAT or CP techniques, can be inefficient when the search space is too large. In this paper, we propose three new methods to improve Matsui’s branch-and-bound
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Considering Fine-Grained and Coarse-Grained Information for Context-Aware Recommendations Comput. J. (IF 1.077) Pub Date : 2020-08-04 Yiqin Luo; Yanpeng Sun; Liang Chang; Tianlong Gu; Chenzhong Bin; Long Li
In context-aware recommendation systems, most existing methods encode users’ preferences by mapping item and category information into the same space, which is just a stack of information. The item and category information contained in the interaction behaviours is not fully utilized. Moreover, since users’ preferences for a candidate item are influenced by the changes in temporal and historical behaviours
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Dynamic Frequency Scaling of a Single-Core Processor Using Machine Learning Paradigms Comput. J. (IF 1.077) Pub Date : 2020-08-04 Sukhmani K Thethi; Ravi Kumar
Dynamic frequency scaling (DFS) is one of the most important approaches for on-the-fly power optimization in modern-day processors. Owing to the trend of chip size shrinkage and increasing the complexity of system design, the problem of achieving an efficient DFS depends upon multi-parametric, non-linear optimization. Hence, it becomes extremely important to identify an optimal underclocking frequency
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Thermal Image-Based Object Classification for Guiding the Visually Impaired Comput. J. (IF 1.077) Pub Date : 2020-08-04 V Nancy; G Balakrishnan
Thermal sensors are now being an emerging technology in image processing applications such as face recognition, fault detection, object detection and classification, navigation, etc. Owing to its versatility, it has been an influential concern for many researchers recently. Thermal sensors have proficiency of sensing the object heedless of the lighting conditions. Due to this added leverage of thermal
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Determining Exact Solutions for Structural Parameters on Hierarchical Networks With Density Feature Comput. J. (IF 1.077) Pub Date : 2020-07-30 Fei Ma; Ping Wang
The problem of determining closed-form solutions for some structural parameters of great interest on networked models is meaningful and intriguing. In this paper, we propose a family of networked models |$\mathcal{G}_{n}(t)$| with hierarchical structure where |$t$| represents time step and |$n$| is copy number. And then, we study some structural parameters on the proposed models |$\mathcal{G}_{n}(t)$|
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Lemuria: A Novel Future Crop Prediction Algorithm Using Data Mining Comput. J. (IF 1.077) Pub Date : 2020-07-30 M Tamil Selvi; B Jaison
Agriculture exhibitions an important role in the progression and enlargement of the economy of any country. Prediction of crop yield will be useful for farmers, but it is difficult to predict crop yield because of the climatic factors such as rainfall, soil factors and so on. To tackle these issues, we are implementing a novel algorithm called Lemuria by applying data mining in agriculture especially
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On Performance Improvement Of Reversible Data Hiding With Contrast Enhancement Comput. J. (IF 1.077) Pub Date : 2020-07-25 Haishan Chen; Junying Yuan; Wien Hong; Jiangqun Ni; Tung-Shou Chen
Reversible data hiding (RDH) with contrast enhancement (RDH-CE) is a special type of RDH in improving the subjective visual perception by enhancing the image contrast during the process of data embedding. In RDH-CE, data hiding is achieved via pairwise histogram expansion, and the embedding rate can be increased by performing multiple cycles of histogram expansions. However, when embedding rate gets
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Effective Link Prediction with Topological and Temporal Information using Wavelet Neural Network Embedding Comput. J. (IF 1.077) Pub Date : 2020-07-23 Xian Mo; Jun Pang; Zhiming Liu
Temporal networks are networks that edges evolve over time, hence link prediction in temporal networks aims at inferring new edges based on a sequence of network snapshots. In this paper, we propose a graph wavelet neural network (TT-GWNN) framework using topological and temporal features for link prediction in temporal networks. To capture topological and temporal features, we develope a second-order
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On Enabling Attribute-Based Encryption to Be Traceable Against Traitors Comput. J. (IF 1.077) Pub Date : 2020-07-23 Zhen Liu; Qiong Huang; Duncan S Wong
Attribute-based encryption (ABE) is a versatile one-to-many encryption primitive, which enables fine-grained access control over encrypted data. Due to its promising applications in practice, ABE schemes with high efficiency, security and expressivity have been continuously emerging. On the other hand, due to the nature of ABE, a malicious user may abuse its decryption privilege. Therefore, being able
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SkySlide: A Hybrid Method for Landslide Susceptibility Assessment based on Landslide-Occurring Data Only Comput. J. (IF 1.077) Pub Date : 2020-07-21 Alev Mutlu; Furkan Goz
Landslide susceptibility assessment is the problem of determining the likelihood of a landslide occurrence in a particular area with respect to the geographical and morphological properties of the area. This paper presents a hybrid method, namely SkySlide, that incorporates clustering, skyline operator, classification and majority voting principle for region-scale landslide susceptibility assessment
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Algorithms Based on Path Contraction Carrying Weights for Enumerating Subtrees of Tricyclic Graphs Comput. J. (IF 1.077) Pub Date : 2020-07-17 Yu Yang; Beifang Chen; Guoping Zhang; Yongming Li; Daoqiang Sun; Hongbo Liu
The subtree number index of a graph, defined as the number of subtrees, attracts much attention recently. Finding a proper algorithm to compute this index is an important but difficult problem for a general graph. Even for unicyclic and bicyclic graphs, it is not completely trivial, though it can be figured out by try and error. However, it is complicated for tricyclic graphs. This paper proposes path
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Large Universe CCA2 CP-ABE With Equality and Validity Test in the Standard Model Comput. J. (IF 1.077) Pub Date : 2020-07-17 Cong Li; Qingni Shen; Zhikang Xie; Xinyu Feng; Yuejian Fang; Zhonghai Wu
Attribute-based encryption with equality test (ABEET) simultaneously supports fine-grained access control on the encrypted data and plaintext message equality comparison without decrypting the ciphertexts. Recently, there have been several literatures about ABEET proposed. Nevertheless, most of them explore the ABEET schemes in the random oracle model, which has been pointed out to have many defects
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Reliability Analysis of Alternating Group Graphs and Split-Stars Comput. J. (IF 1.077) Pub Date : 2020-07-16 Mei-Mei Gu; Rong-Xia Hao; Jou-Ming Chang
Given a connected graph |$G$| and a positive integer |$\ell $|, the |$\ell $|-extra (resp. |$\ell $|-component) edge connectivity of |$G$|, denoted by |$\lambda ^{(\ell )}(G)$| (resp. |$\lambda _{\ell }(G)$|), is the minimum number of edges whose removal from |$G$| results in a disconnected graph so that every component has more than |$\ell $| vertices (resp. so that it contains at least |$\ell
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Persistence of Hybrid Diagnosability of Regular Networks Under Testing Diagnostic Model Comput. J. (IF 1.077) Pub Date : 2020-07-16 Guanqin Lian; Shuming Zhou; Eddie Cheng; Jiafei Liu; Gaolin Chen
Diagnosability is an important metric to fault tolerance and reliability for multiprocessor systems. However, plenty of research on fault diagnosability focuses on node failure. In practical scenario, not only node failures take place but also link malfunctions may arise. In this work, we investigate the diagnosability of general regular networks with failing nodes as well as missing malfunctional
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Interference and Coverage Modeling for Indoor Terahertz Communications with Beamforming Antennas Comput. J. (IF 1.077) Pub Date : 2020-07-16 Chao-Chao Wang; Wan-Liang Wang; Xin-Wei Yao
A general framework to investigate the interference and coverage probability is proposed in this paper for indoor terahertz (THz) communications with beamforming antennas. Due to the multipath effects of THz band (0.1–10 THz), the line of sight and non-line of sight interference from users and access points (APs) (both equipped with beamforming antennas) are separately analyzed based on distance-dependent
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