Similar Journals
|
International Journal of Information Technology and Web Engineering
Journal Prestige (SJR): 0.168  Citation Impact (citeScore): 1 Number of Followers: 2  Hybrid journal (It can contain Open Access articles)ISSN (Print) 1554-1045 - ISSN (Online) 1554-1053 Published by IGI Global  [147 journals]
|
- A Secure Data Transfer Approach with an Efficient Key Management over
Cloud-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: The growth in the number of cloud users who transfer their health data have enhanced the importance of cloud technology's services and capabilities. However, transferring patient health data to the cloud leaves researchers with several concerns and obstacles in privacy, storage, access, key-formation, and management. The proposed paper presents an efficient methodology for storing and accessing health information to and from the cloud. The symmetric key cryptography with the MD5 hash function is employed to enhance the framework’s efficiency. The proposed method also provides secure data sharing and removes the burden of an exhaustive re-encryption computation. In the paper, two different keys are computed: one key for each legitimate user among a group, and another key for the crypto-system, which is responsible to do all computations over the data. The method provides security against internal threats since only a single share of the key can be accessed. The efficiency of the model is measured by measuring the execution time for key formation, encryption, and decryption processes.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 0-0
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.306917
Issue No: Vol. 17, No. 1 (2022)
-
- Microclustering-based multi-class classification on imbalanced
multi-relational datasets-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: In a relational database, classification algorithms are used to look for patterns across several interconnected relations. Most of the methods for multi-relational classification algorithms implicitly assume that the classes in the target relation are equally represented. Thus, they tend to produce poor predictive performance over the imbalanced dataset. In this paper, we propose an algorithm level method MCMRC_IB for the classification of imbalanced multi-relational dataset. The proposed method extends MCMRC which is for balanced datasets. MCMRC_IB exploits the property of the imbalanced datasets that the minority class is represented by a smaller number of records usually 20-30% of the total records and is to be dealt accordingly by giving them weightages. The proposed method is able to handle multiple classes. Experimental results confirm the efficiency of the proposed method in terms of predictive accuracy, F-measure and G-mean.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 0-0
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.304053
Issue No: Vol. 17, No. 1 (2022)
-
- Autonomous Transaction Model for E-Commerce Management using
the BlockChain Technology-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: A Blockchain is an advanced technology that can power over a decentralized network. We bring it up to design the autonomous transaction system for E-commerce applications; because of the dramatic increase in IoT devices, communication between physical things is enabled. This brings more efficiency and accuracy, which benefits the outsiders while human interaction reduces. There is a big challenge in data storage after payment in the e-commerce application. Blockchain presents an appropriate platform for the distributed data storage; it also protects the data from outsiders. We create blocks that check and record each transaction that took place in the e-commerce application. Blockchain is going to prevent the user’s privacy from outsiders/banks that are being violated. We deliver this research in this paper in terms of the method with detailed design and full implementation. The system captures the user data, processes it and gives a visual representation of the processed data.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 0-0
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.304047
Issue No: Vol. 17, No. 1 (2022)
-
- Smart Contracts Security threats and Solutions
-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Blockchain-enabled smart contracts are subjected to several issues leading to vigorous attacks such as the Decentralized Autonomous Organization (DAO) and the ParitySig bug on the Ethereum platform with disastrous consequences. Several solutions have been proposed. However, new threats are identified as technology evolves and new solutions are produced, while some older threats remain unsolved. Thus, the need to fill the gap with a more comprehensive survey on existing issues and solutions for researchers and practitioners arises. The resulting updated database will become an essential means for choosing a particular solution for a specific subject. In this review, we embrace mainly codifying security privacy and performance issues and their respective solutions. Each problem is attached to its corresponding solutions when they exist. A summary of the threats and solutions is provided as well as the relationship between threats’ importance and the given answers. We finally enumerate some directives for future works.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 0-0
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.304048
Issue No: Vol. 17, No. 1 (2022)
-
- Social Network User Profiling with Multilayer Semantic Modeling using Ego
Network-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Social and information networks undermines the real relationship between the individuals (ego) and the friends (alters) they are connected on the social media and their impact on relationships. The structure of individual network is highlighted by the ego network. Egocentric approach is popular due to its focus on individual, group or communities. Size, structure and composition directly impact the ego networks. Moreover analysis includes strength of ego –alter ties degree and strength of ties. Degree gives the first overview of network. Social support in the network is explored with the ”gap” between the degree and average strength. These outcomes firmly propose that, regardless of whether the approaches to convey and to keep up social connections are evolving because of the dispersion of Online Social Networks, the way individuals sort out their social connections appears to stay unaltered. As online social networks evolves it helps in receiving more diverse information.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 0-0
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.304049
Issue No: Vol. 17, No. 1 (2022)
-
- Social Network Analysis for Precise Friend Suggestion for Twitter by
Associating Multiple Networks using ML-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Our main aim in this paper is to create a friend suggestion algorithm that can be used to recommend new friends to a user on Twitter when their existing friends and other details are given. The information gathered to make these predictions includes the user’s friends, tags, tweets, language spoken, id, etc. Based on these features, we trained our models using supervised learning methods. The machine learning-based approach used for this purpose is the K-Nearest neighbors approach. This approach is by and large used to decrease the dimensionality of the information alongside its feature space. K-nearest neighbor classifier is normally utilized in arrangement-based situations to recognize and distinguish between a few parameters. By using this, the features of the central user’s non-friends were compared. The friends and communities of a user are likely to be very different from any other user. Due to this, we select a single user and compare the results obtained for that user to suggest friends.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 0-0
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.304050
Issue No: Vol. 17, No. 1 (2022)
-
- Malware Threat Affecting Financial Organization Analysis Using Machine
Learning Approach-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors: Rawat; Romil, Rimal, Yagya Nath, William, P., Dahima, Snehil, Gupta, Sonali, Sankaran, K. Sakthidasan
Pages: 1 - 20
Abstract: Since 2014, Emotet has been using Man-in-the-Browsers (MITB) attacks to target companies in the finance industry and their clients. Its key aim is to steal victims' online money-lending records and vital credentials as they go to their banks' websites. Without analyzing network packet payload computing (PPC), IP address labels, port number traces, or protocol knowledge, we have used Machine Learning (ML) modeling to detect Emotet malware infections and recognize Emotet related congestion flows in this work. To classify emotet associated flows and detect emotet infections, the output outcome values are compared by four separate popular ML algorithms: RF (Random Forest), MLP (Multi-Layer Perceptron), SMO (Sequential Minimal Optimization Technique), and the LRM (Logistic Regression Model). The suggested classifier is then improved by determining the right hyperparameter and attribute set range. Using network packet (computation) identifiers, the Random Forest classifier detects emotet-based flows with 99.9726 percent precision and a 92.3 percent true positive rating.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 1-20
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.304051
Issue No: Vol. 17, No. 1 (2022)
-
- Research on System Risks of “Internet + Supply Chain Finance” Based on
SNA, Dynamic Evolutionary Game, and Bayesian Learning Principle Simulation
-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors: Liu; Ji Lu, Hu, Ni, Zhang, Cheng
Pages: 1 - 16
Abstract: Under the background of "Internet +", the supply chain financial model and process have undergone profound changes. Firstly, through the social network analysis, the correlation between the participants in the Internet + supply chain finance is directly visualized. Secondly, the dynamic risk evolution model of the system is constructed based on the different functions between the participants. Unstable solution and saddle points of the system be calculated ; on this basis, Bayesian learning principles are used to build an Internet + supply chain financial credit default risk simulation model, and the simulation model is encapsulated. Finally, a numerical example is used to verify the simulation model operation Convenience, efficiency and reliability.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 1-16
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.308465
Issue No: Vol. 17, No. 1 (2022)
-
- Time Effective Cloud Resource Scheduling Method for Data-Intensive Smart
Systems-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors: Duan; Jiguang, Li, Yan, Duan, Liying, Sharma, Amit
Pages: 1 - 15
Abstract: The cloud computing platforms are being deployed nowadays for resource scheduling of real time data intensive applications. Cloud computing still deals with the challenge of time oriented effective scheduling for resource allocation, while striving to provide the efficient quality of service. This article proposes a time prioritization-based ensemble resource management and Ant Colony based optimization (ERM-ACO) algorithm in order to aid effective resource allocation and scheduling mechanism which specifically deals with the task group feasibility, assessing and selecting the computing and the storage resources required to perform specific tasks. The research outcomes are obtained in terms of time-effective demand fulfillment rate, average response time as well as resource utilization time considering various grouping mechanisms based on data arrival intensity consideration. The proposed framework when compared to the present state-of-the-art methods, optimal fitness percentage of 98% is observed signifying the feasible outcomes for real-time scenarios.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 1-15
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.306915
Issue No: Vol. 17, No. 1 (2022)
-
- An Integrated Remote Control-Based Human-Robot Interface for Education
Application-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors: Duan; Xue-xi, Wang, Yun-ling, Dou, Wei-shan, Kumar, Rajeev, Saluja, Nitin
Pages: 1 - 18
Abstract: Portable interfaced robot arms equipped with mobile user interactions are significantly being utilized in modern world. The application of teaching robotics is being used in challenging pandemic situation but it is still challenging due to mathematical formulation. This article utilizes the augmented reality (AR) concept for remote control-based human-robot interaction using the Bluetooth correspondence. The proposed framework incorporates different modules like a robot arm control, a regulator module and a distant portable smartphone application for envisioning the robot arm points for its real-time relevance. This novel approach fuses AR innovation into portable application which permit the continuous virtual coordination with actual physical platform. The simulation yields effective outcomes with 96.94% accuracy for testing stage while maintaining error and loss values of 0.194 and 0.183 respectively. The proposed interface gives consistent results for teaching application in real time changing environment by outperforming existing methods with an accuracy improvement of 13.4
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 1-18
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.306916
Issue No: Vol. 17, No. 1 (2022)
-
- Predicting Academic Performance of Immigrant Students Using XGBoost
Regressor-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors: Jeganathan; Selvaprabu, Lakshminarayanan, Arun Raj, Ramachandran, Nandhakumar, Tunze, Godwin Brown
Pages: 1 - 19
Abstract: The education sector has been effectively dealing with the prediction of academic performance of the Immigrant students since the research associated with this domain proves beneficial enough for those countries where the ministry of education has to cater to such immigrants for altering and updating policies in order to elevate the overall education pedagogy for them. The present research begins with analyzing varied educational data mining and machine learning techniques that helps in assessing the data fetched form PISA. It’s elucidated that XGBoost stands out to be the ideal most machine learning technique for achieving the desired results. Subsequently, the parameters have been optimized using the hyper parameter tuning techniques and implemented on the XGBoost Regressor algorithm. Resultant there is low error rate and higher level of predictive ability using the machine learning algorithms which assures better predictions using the PISA data. The final results have been discussed along with the upcoming future research work.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 1-19
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.304052
Issue No: Vol. 17, No. 1 (2022)
-
- Intelligent Anti-Jamming Decision Algorithm of Bivariate Frequency Hopping
Pattern Based on DQN With PER and Pareto-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors: Zhu; Jiasheng, Zhao, Zhijin, Zheng, Shilian
Pages: 1 - 23
Abstract: To improve the anti-jamming performance of frequency hopping system in complex electromagnetic environment, a Deep Q-Network algorithm with priority experience replay (PER) based on Pareto samples (PPER-DQN) is proposed, which makes intelligent decision for bivariate FH pattern. The system model, state-action space and reward function are designed based on the main parameters of the FH pattern. The DQN is used to improve the flexibility of the FH pattern. Based on the definition of Pareto dominance, the PER based on the TD-error and immediate reward is proposed. To ensure the diversity of the training set, it is formed by Pareto sample set and several random samples. When selecting Pareto sample, the confidence coefficient is introduced to modify its priority. It guarantees the learning value of the training set and improves the learning efficiency of DQN. The simulation results show that the efficiency, convergence speed and stability of the algorithm are effectively improved. And the generated bivariate FH pattern has better performance than the conventional FH pattern.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 1-23
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.297970
Issue No: Vol. 17, No. 1 (2022)
-
- Binary Self-Adaptive Salp Swarm Optimization-Based Dynamic Load Balancing
in Cloud Computing-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors: Parida; Bivasa Ranjan, Rath, Amiya Kumar, Mohapatra, Hitesh
Pages: 1 - 25
Abstract: In the recent era of cloud computing, the huge demand for virtual resource provisioning requires mitigating the challenges of uniform load distribution as well as efficient resource utilization among the virtual machines in cloud datacenters. Salp swarm optimization is one of the simplest, yet efficient metaheuristic techniques to balance the load among the VMs. The proposed methodology has incorporated self-adaptive procedures to deal with the unpredictable population of the tasks being executed in cloud datacenters. Moreover, a sigmoid transfer function has been integrated to solve the discrete problem of tasks assigned to the appropriate VMs. Thus, the proposed algorithm binary self-adaptive salp swarm optimization has been simulated and compared with some of the recent metaheuristic approaches, like BSO, MPSO, and SSO for conflicting scheduling quality of service parameters. It has been observed from the result analysis that the proposed algorithm outperforms in terms of makespan, response time, and degree of load imbalance while maximizing the resource utilization.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 1-25
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.295964
Issue No: Vol. 17, No. 1 (2022)
-
- On Cost-Aware Heterogeneous Cloudlet Deployment for Mobile Edge Computing
-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors: Ye; Hengzhou, Huang, Fengyi, Hao, Wei
Pages: 1 - 23
Abstract: Edge computing undertakes downlink cloud services and uplink terminal computing tasks, data interaction latency and network transmission cost are thus significantly reduced. Although a lot of research has been conducted in mobile edge computing (MEC), which assumed that all homogeneous cloudlets are placed in WMAN and user mobility is also ignored, little attention is paid to how to place heterogeneous cloudlets in wireless metropolitan area network (WMAN) to minimize the deployment cost of cloudlets. Meanwhile, the method of selecting an optimal access point (AP) for deployment, modeling and heuristic algorithm (HA) needs to be improved. Therefore, this paper design a new heterogeneous cloudlet deployment model considering the quality of service (QoS) and mobility of users, and the Improved Heuristic Algorithm (IHA) is proposed to minimize cloudlet deployment cost. The extensive simulations demonstrate that IHA is more efficient than HA and the designed model is superior to the existing work.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 1-23
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.297968
Issue No: Vol. 17, No. 1 (2022)
-
- Multi-Objective Optimization-Oriented Resource Allocation in the Fog
Environment-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors: Harika; Sonti, Krishna, B. Chaitanya
Pages: 1 - 25
Abstract: Fog computing is a decentralized computer system where data, processing, storage, as well as applications are located anywhere between the cloud and data source. Fog computing takes the cloud closer to users, decreasing the latency and allows the deployment of new delay-sensitive appliances. An important feature of a fog-cloud network is the process of decision-making on assigning the resources to execute the tasks of application. This paper aims to propose a resource allocation strategy for fog computing that determines the effective process under the consideration of the objectives that includes the constraints like credibility score, concurrency, price affordability and task time computation. Moreover, the credibility score is determined based on the execution efficiency, Service response rate, access reliability and Reboot rate. Thereby, the optimal allocation of resources is handled by a new Hybrid Monarch-Dragon Algorithm (HM-DA) that hybrids the concept of Dragonfly Algorithm (DA) and Monarch Butterfly Optimization (MBO) algorithm.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 1-25
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.297969
Issue No: Vol. 17, No. 1 (2022)
-
- SCNTA
-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors: Rawat; Romil, Garg, Bhagwati, Pachlasiya, Kiran, Mahor, Vinod, Telang, Shrikant, Chouhan, Mukesh, Shukla, Surendra Kumar, Mishra, Rina
Pages: 1 - 19
Abstract: Real-time network inspection applications face a threat of vulnerability as high-speed networks continue to expand. For companies and ISPs, real-time traffic classification is an issue. The classifier monitor is made up of three modules: Capturing_of_Packets (CoP) and pre-processing, Reconciliation_of_Flow (RoF), and categorization of Machine Learning (ML). Based on parallel processing along with well-defined interfacing of data, the modules are framed, allowing each module to be modified and upgraded separately. The Reconciliation_of_Flow (RoF) mechanism becomes the output bottleneck in this pipeline. In this implementation, an optimal reconciliation process was used, resulting in an average delivery time of 0.62 seconds. In order to verify our method, we equated the results of the AdaBoost Ensemble Learning Algorithm (ABELA), Naive Bayes (NB), Decision Tree (DT), K-Nearest Neighbor (KNN), and Flexible Naive Bayes (FNB) in the classification module. The architectural design of the run time CSNTA categorization (flow-based) scheme is presented in this paper.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 1-19
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.297971
Issue No: Vol. 17, No. 1 (2022)
-
- Biometric Cloud Services for Web-Based Examinations
-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors: Rukhiran; Meennapa, Pukdesree, Sorapak, Netinant, Paniti
Pages: 1 - 25
Abstract: Biometric recognition may be used in conjunction with human authentication on a smartphone to improve accuracy, reliability, and simplicity, and to aid in fraud prevention and user authentication. While single biometric authentication addresses environmental degradation and sensor noise limitations, and the single point of failure scenario in biometric systems can result in more robust biometric systems, multimodal biometric authentication can improve the accuracy of identification and recognition. The purpose of this research is to propose a facial and speech authentication system that is cloud-based and supports a web-based examination approach. The system enables students' biometrics to be registered, students to be recognized, and student recognition results to be reported. The confusion matrix is used to compare the results of positive and negative detection in various ways, including accuracy score, precision value, and recall value. Adaptive multimodal biometric authentication should be designed and evaluated for further research using the optimal weights for each biometric.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 1-25
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.299022
Issue No: Vol. 17, No. 1 (2022)
-
- Relationship Between Personality Patterns and Harmfulness
-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors: Matsumoto; Kazuyuki, Kishima, Ryota, Tsuchiya, Seiji, Hirobayashi, Tomoki, Yoshida, Minoru, Kita, Kenji
Pages: 1 - 24
Abstract: This paper hypothesize that harmful utterances need to be judged in context of whole sentences, and extract features of harmful expressions using a general-purpose language model. Based on the extracted features, we propose a method to predict the presence or absence of harmful categories. In addition, the authors believe that it is possible to analyze users who incite others by combining this method with research on analyzing the personality of the speaker from statements on social networking sites. The results confirmed that the proposed method can judge the possibility of harmful comments with higher accuracy than simple dictionary-based models or models using a distributed representations of words. The relationship between personality patterns and harmful expressions was also confirmed by an analysis based on a harmful judgment model.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 1-24
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.298654
Issue No: Vol. 17, No. 1 (2022)
-
- Winning the War on Terror
-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors: Wang; Yaojie, Cui, Xiaolong, He, Peiyong
Pages: 1 - 15
Abstract: From the perspective of counter-terrorism strategies, terrorist risk assessment has become an important approach for counter-terrorism early warning research. Combining with the characteristics of known terrorists, a quantitative analysis method of active risk assessment method with terrorists as the research object is proposed. This assessment method introduces deep learning algorithms into social computing problems on the basis of information coding technology. We design a special "Top-k" algorithm to screen the terrorism related features, and optimize the evaluation model through convolution neural network, so as to determine the risk level of terrorist suspects. This study provides important research ideas for counter-terrorism assessment, and verifies the feasibility and accuracy of the proposed scheme through a number of experiments, which greatly improves the efficiency of counter-terrorism early warning.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 1-15
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.288038
Issue No: Vol. 17, No. 1 (2022)
-
- Extracting Entity Synonymous Relations via Context-Aware Permutation
Invariance-
Free pre-print version: Loading...Rate this result: What is this?Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors: Yan; Nan, Huang, Subin, Kong, Chao
Pages: 1 - 17
Abstract: Discovering entity synonymous relations is an important work for many entity-based applications. Existing entity synonymous relation extraction approaches are mainly based on lexical patterns or distributional corpus-level statistics, ignoring the context semantics between entities. For example, the contexts around ''apple'' determine whether ''apple'' is a kind of fruit or Apple Inc. In this paper, an entity synonymous relation extraction approach is proposed using context-aware permutation invariance. Specifically, a triplet network is used to obtain the permutation invariance between the entities to learn whether two given entities possess synonymous relation. To track more synonymous features, the relational context semantics and entity representations are integrated into the triplet network, which can improve the performance of extracting entity synonymous relations. The proposed approach is implemented on three real-world datasets. Experimental results demonstrate that the approach performs better than the other compared approaches on entity synonymous relation extraction task.
Keywords: Web Technologies; Computer Science & IT; Web Technologies & Engineering
Citation: International Journal of Information Technology and Web Engineering (IJITWE), Volume: 17, Issue: 1 (2022) Pages: 1-17
PubDate: 2022-01-01T05:00:00Z
DOI: 10.4018/IJITWE.288039
Issue No: Vol. 17, No. 1 (2022)
-
