Web Intell. Pub Date : 2023-03-22 DOI: 10.3233/web-221823

S. Devi, R. Indhumathi

{"title":"Enhancing privacy for automatically detected quasi identifier using data anonymization","authors":"S. Devi, R. Indhumathi","doi":"10.3233/web-221823","DOIUrl":"https://doi.org/10.3233/web-221823","url":null,"abstract":"The fast advancement of information technology has resulted in more efficient information storage and retrieval. As a result, most organizations, businesses, and governments are releasing and exchanging a large amount of micro data among themselves for commercial or research purposes. However, incorrect data exchange will result in privacy breaches. Many methods and strategies have been developed to address privacy breaches, and Anonymization is one of them that many companies use. In order to perform anonymization, identification of the Quasi Identifier (QI) is significant. Hence this paper proposes a method called Quasi Identification Based on Tree (QIBT) for automatic QI identification. The proposed method derives the QI, based on the relationship between the numbers of distinct values assumed by the set of attributes. So, it uses the tree data structure to derive the unique and infrequent attribute values from the entire dataset with less computational cost. The proposed method consists of four phases: (i) Unique attribute value computation (ii) Tree construction and (iii) Computation of quasi-identifier from the tree (iv) Applying Anonymization Technique to the identified QI. Attributes with high risk of disclosure are identified using our proposed algorithm. Synthetic data are created exclusively for the detected QI using a partial synthetic data generating technique to improve usefulness. The suggested method’s efficiency is tested with a subset of the UCI machine learning dataset and produces superior results when compared to other current approaches.","PeriodicalId":245783,"journal":{"name":"Web Intell.","volume":"457 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123050362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dual stage ensemble technique for intrusion detection in cloud computing 云计算中入侵检测的双阶段集成技术

Web Intell. Pub Date : 2023-03-22 DOI: 10.3233/web-221800

P. Neelakantan, N. Yadav

{"title":"Dual stage ensemble technique for intrusion detection in cloud computing","authors":"P. Neelakantan, N. Yadav","doi":"10.3233/web-221800","DOIUrl":"https://doi.org/10.3233/web-221800","url":null,"abstract":"A capability of cloud-based IDS in identifying complicated and anonymous attacks is rising in the current era. However, unwanted delays hinder the detection rate. A malicious user might utilize vast quantities of computational power. The cloud provides to perform attacks both within and without the cloud. Furthermore, there are major challenges for intrusion detection due to the ease of the cloud and also the continual restructuring and movement of cloud resources. Intruder detection, feature extraction, and data processing are all included in the novel optimization-based Intrusion Detection System (IDS) paradigm that will be presented in this study. Data normalization is used to first pre-process the input data. Then, appropriate feature extraction is carried out, including the extraction of (a) raw features, (b) statistical features, then (c) higher-order statistical features using suggested kurtosis. The detection phase is then applied to the retrieved features. A two-stage ensemble method is suggested for finding intruders in clouds. Random forest (RF), Support Vector Machine (SVM), optimal Neural Network (NN), and RNN make up the suggested ensemble technique. The RF, SVM, and Optimized NN algorithms are directly fed the collected features. The output of these classifiers is then provided to the RNN classifier (i.e.), RF output to RNN1, SVM output to RNN2, and optimized NN output to RNN3. Then, the weighted average of RNN 1, 2, and 3 is considered as the final output. A Self Adaptive Salp Swarm Optimization optimizes the weights of NN for exact detection (SA-SSO). Finally, a test is conducted to confirm the developed model’s superiority.","PeriodicalId":245783,"journal":{"name":"Web Intell.","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125345254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cyberbullying detection through deep learning: A case study of Turkish celebrities on Twitter 基于深度学习的网络欺凌检测:以Twitter上的土耳其名人为例

Web Intell. Pub Date : 2023-03-20 DOI: 10.3233/web-221805

Bulut Karadağ, A. Akbulut, A. Zaim

引用次数: 0

Modified convolutional neural network for lung cancer detection: Improved cat swarm-based optimal training 肺癌检测的改进卷积神经网络:改进的基于猫群的最优训练

Web Intell. Pub Date : 2023-03-20 DOI: 10.3233/web-221801

Vikul Pawar, P. Premchand

{"title":"Modified convolutional neural network for lung cancer detection: Improved cat swarm-based optimal training","authors":"Vikul Pawar, P. Premchand","doi":"10.3233/web-221801","DOIUrl":"https://doi.org/10.3233/web-221801","url":null,"abstract":"Lung cancer is the most lethal and severe illness in existence. However, lung cancer patients may live longer if they receive early detection and treatment. In the medical field, the best imaging technique is CT scan imaging as it is more complex for doctors to identify cancer and interpret from CT scan images. Consequently, the computer-aided diagnosis (CAD) is more useful for doctors to find out cancerous nodules. To identify lung cancer, a number of CAD techniques utilising machine learning (ML) and image processing are used nowadays. The goal of this study is to present a novel method for detecting lung cancer that entails four main steps: (i) Pre-processing, (ii) Segmentation, (iii) Feature extraction, and (iv) Classification. ”The input image is first put through a pre-processing step in which the CLAHE model is used to pre-process the image. The segmentation phase of the pre-processed images is then initiated, and it makes use of a modified Level set segmentation method. The retrieved features from the segmented images include statistical features, colour features, and texture features (GLCM, GLRM, and LBP). The Layer Fused Conventional Neural Network (LF-CNN) is then utilised to classify these features in the end. Particularly, layer-wise modification is carried out, and along with that, the LF-CNN is trained by the Modified Cat swarm Optimization (MCSO) Algorithm via selecting optimal weights. The accepted scheme is then compared to the current models in terms of several metrics, including recall, FNR, MCC, FDR, Threat score, FPR, precision, FOR, accuracy, specificity, NPV, FMS, and sensitivity.","PeriodicalId":245783,"journal":{"name":"Web Intell.","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121648642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Decentralized multi-agent approach based on A* algorithm for on-demand transport problem 基于A*算法的按需运输问题分散多智能体方法

Web Intell. Pub Date : 2023-03-15 DOI: 10.3233/web-221659

A. Malas, S. E. Falou, Mohamad El Falou, Mohammad Hussein

引用次数: 0

M2GCF: A multi-mixing strategy for graph neural network based collaborative filtering M2GCF:基于图神经网络的多混合协同过滤策略

Web Intell. Pub Date : 2022-11-10 DOI: 10.3233/web-220054

Jia-nuo Xu, Jiajin Huang, Jian Yang, Ning Zhong

引用次数: 0

Aquila optimized feedback artificial tree for detection of fake news and impact identification Aquila优化了假新闻检测和影响识别的反馈人工树

Web Intell. Pub Date : 2022-11-10 DOI: 10.3233/web-220046

B. Venkateswarlu, V. V. Shenoi, Praveen Tumuluru

{"title":"Aquila optimized feedback artificial tree for detection of fake news and impact identification","authors":"B. Venkateswarlu, V. V. Shenoi, Praveen Tumuluru","doi":"10.3233/web-220046","DOIUrl":"https://doi.org/10.3233/web-220046","url":null,"abstract":"In recent days, social media is termed a major source for several people residing over the world because of less cost, simpler accessibility, and quick dissemination. However, it comes with dubious trustworthiness and is of high risk in exposing fake news. Hence, the automated discovery of fake news is an essential task. An innovative model is provided to identify fake news considering social media. Here, the BERT model is utilized to perform tokenization in order to produce tokens. Multiple features linked with the data are analyzed for detecting the behavior using the deep model. The features, like Term Frequency-Inverse Document Frequency (TF-IDF), SentiWordNet scores, and sentence level features are obtained to automatically learn the features. Automatic discovery of fake news is done with Aquila Feedback Artificial tree-based Deep Residual Network (AFAT-based DRN). The optimum weight tuning of DRN is executed with AFAT and the AFAT is the fusion of Aquila optimizer (AO) and Feedback artificial tree (FAT). The impact detection of fake news is done with AFAT-based DRN, which helps to detect how many of them shared the fake news. The AFAT-based DRN offered high competence with utmost sensitivity of 92.3%, testing accuracy of 91.6%, and specificity of 91.9%.","PeriodicalId":245783,"journal":{"name":"Web Intell.","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124257775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Applying interrater reliability measure for user credibility assessment in reputation-oriented service discovery 在面向声誉的服务发现中应用互信度测度进行用户可信度评估

Web Intell. Pub Date : 2022-11-08 DOI: 10.3233/web-220002

Arnab Paul, Sourish Dhar, S. Roy

{"title":"Applying interrater reliability measure for user credibility assessment in reputation-oriented service discovery","authors":"Arnab Paul, Sourish Dhar, S. Roy","doi":"10.3233/web-220002","DOIUrl":"https://doi.org/10.3233/web-220002","url":null,"abstract":"Service Oriented Architecture is built on services in which web service discovery is one of the most widely explored domains. Service reputation plays a vital role in the discovery process while selecting the optimal service from a large pool of functionally equivalent services. Reputation mechanism attempts to forecast the future performance of a service based on its past behaviors generally obtained in the form of feedback ratings submitted by users of the service. These feedback ratings about a service may vary from user to user. Variations in feedback ratings could be because of different users’ different subjective judgments and/or dishonest users’ purposely submitted unfair ratings. This paper proposes a service reputation measurement approach counting such diversified act of rating. To realize this goal, an efficient user credibility assessment methodology has been devised by employing the measure of interrater reliability. Experiments are performed to validate the feasibility and effectiveness of the proposed reputation measurement approach. The experimental results depict that the proposed approach can fairly assess service reputations in the presence of various kinds of raters in the system.","PeriodicalId":245783,"journal":{"name":"Web Intell.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129713365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The multi-dimensional power big data mining based on improved grey clustering algorithm 基于改进灰色聚类算法的多维功率大数据挖掘

Web Intell. Pub Date : 2022-11-08 DOI: 10.3233/web-220048

Hui Li, Guangqian Lu

引用次数: 0

Communication information exchange and transmission method of industrial Internet of things based on audio information hiding 基于音频信息隐藏的工业物联网通信信息交换与传输方法

Web Intell. Pub Date : 2022-09-23 DOI: 10.3233/web-220044

Yinlei Tian, Haiyan Wang

引用次数: 0

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