Handbook of Research on Machine and Deep Learning Applications for Cyber Security最新文献

Applications of Machine Learning in Cyber Security 机器学习在网络安全中的应用

Handbook of Research on Machine and Deep Learning Applications for Cyber Security Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-9611-0.CH005

Charu Virmani, Tanu Choudhary, Anuradha Pillai, M. Rani

引用次数: 45

Variable Selection Method for Regression Models Using Computational Intelligence Techniques 基于计算智能技术的回归模型变量选择方法

Handbook of Research on Machine and Deep Learning Applications for Cyber Security Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-9611-0.CH019

S. Dhamodharavadhani, R. Rathipriya

引用次数: 11

Big Data Analytics With Machine Learning and Deep Learning Methods for Detection of Anomalies in Network Traffic 用机器学习和深度学习方法检测网络流量异常的大数据分析

Handbook of Research on Machine and Deep Learning Applications for Cyber Security Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-9611-0.CH015

V. Narayan, D. Shanmugapriya

{"title":"Big Data Analytics With Machine Learning and Deep Learning Methods for Detection of Anomalies in Network Traffic","authors":"V. Narayan, D. Shanmugapriya","doi":"10.4018/978-1-5225-9611-0.CH015","DOIUrl":"https://doi.org/10.4018/978-1-5225-9611-0.CH015","url":null,"abstract":"Information is vital for any organization to communicate through any network. The growth of internet utilization and the web users increased the cyber threats. Cyber-attacks in the network change the traffic flow of each system. Anomaly detection techniques have been developed for different types of cyber-attack or anomaly strategies. Conventional ADS protect information transferred through the network or cyber attackers. The stable prevention of anomalies by machine and deep-learning algorithms are applied for cyber-security. Big data solutions handle voluminous data in a short span of time. Big data management is the organization and manipulation of huge volumes of structured data, semi-structured data and unstructured data, but it does not handle a data imbalance problem during the training process. Big data-based machine and deep-learning algorithms for anomaly detection involve the classification of decision boundary between normal traffic flow and anomaly traffic flow. The performance of anomaly detection is efficiently increased by different algorithms.","PeriodicalId":354100,"journal":{"name":"Handbook of Research on Machine and Deep Learning Applications for Cyber Security","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134395886","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

A Secure Protocol for High-Dimensional Big Data Providing Data Privacy 提供数据隐私的高维大数据安全协议

Handbook of Research on Machine and Deep Learning Applications for Cyber Security Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-9611-0.CH016

J. Anitha, S. Prasad

引用次数: 0