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Data Analytics for Cybersecurity

Data Analytics for Cybersecurity PDF Author: Vandana P. Janeja
Publisher: Cambridge University Press
ISBN: 110841527X
Category : Computers
Languages : en
Pages : 240
Book Description
Shows how traditional and nontraditional methods such as anomaly detection and time series can be extended using data analytics.

Data Analytics for Cybersecurity

Data Analytics for Cybersecurity PDF Author: Vandana P. Janeja
Publisher: Cambridge University Press
ISBN: 110841527X
Category : Computers
Languages : en
Pages : 240
Book Description
Shows how traditional and nontraditional methods such as anomaly detection and time series can be extended using data analytics.

Big Data Analytics in Cybersecurity

Big Data Analytics in Cybersecurity PDF Author: Onur Savas
Publisher: CRC Press
ISBN: 1351650416
Category : Business & Economics
Languages : en
Pages : 336
Book Description
Big data is presenting challenges to cybersecurity. For an example, the Internet of Things (IoT) will reportedly soon generate a staggering 400 zettabytes (ZB) of data a year. Self-driving cars are predicted to churn out 4000 GB of data per hour of driving. Big data analytics, as an emerging analytical technology, offers the capability to collect, store, process, and visualize these vast amounts of data. Big Data Analytics in Cybersecurity examines security challenges surrounding big data and provides actionable insights that can be used to improve the current practices of network operators and administrators. Applying big data analytics in cybersecurity is critical. By exploiting data from the networks and computers, analysts can discover useful network information from data. Decision makers can make more informative decisions by using this analysis, including what actions need to be performed, and improvement recommendations to policies, guidelines, procedures, tools, and other aspects of the network processes. Bringing together experts from academia, government laboratories, and industry, the book provides insight to both new and more experienced security professionals, as well as data analytics professionals who have varying levels of cybersecurity expertise. It covers a wide range of topics in cybersecurity, which include: Network forensics Threat analysis Vulnerability assessment Visualization Cyber training. In addition, emerging security domains such as the IoT, cloud computing, fog computing, mobile computing, and cyber-social networks are examined. The book first focuses on how big data analytics can be used in different aspects of cybersecurity including network forensics, root-cause analysis, and security training. Next it discusses big data challenges and solutions in such emerging cybersecurity domains as fog computing, IoT, and mobile app security. The book concludes by presenting the tools and datasets for future cybersecurity research.

Machine Intelligence and Big Data Analytics for Cybersecurity Applications

Machine Intelligence and Big Data Analytics for Cybersecurity Applications PDF Author: Yassine Maleh
Publisher: Springer Nature
ISBN: 303057024X
Category : Computers
Languages : en
Pages : 539
Book Description
This book presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis. Cyber-attacks have posed real and wide-ranging threats for the information society. Detecting cyber-attacks becomes a challenge, not only because of the sophistication of attacks but also because of the large scale and complex nature of today’s IT infrastructures. It discusses novel trends and achievements in machine intelligence and their role in the development of secure systems and identifies open and future research issues related to the application of machine intelligence in the cybersecurity field. Bridging an important gap between machine intelligence, big data, and cybersecurity communities, it aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this area or those interested in grasping its diverse facets and exploring the latest advances on machine intelligence and big data analytics for cybersecurity applications.

Big Data Analytics in Cybersecurity

Big Data Analytics in Cybersecurity PDF Author: Onur Savas
Publisher: CRC Press
ISBN: 1498772161
Category : Business & Economics
Languages : en
Pages : 336
Book Description
Big data is presenting challenges to cybersecurity. For an example, the Internet of Things (IoT) will reportedly soon generate a staggering 400 zettabytes (ZB) of data a year. Self-driving cars are predicted to churn out 4000 GB of data per hour of driving. Big data analytics, as an emerging analytical technology, offers the capability to collect, store, process, and visualize these vast amounts of data. Big Data Analytics in Cybersecurity examines security challenges surrounding big data and provides actionable insights that can be used to improve the current practices of network operators and administrators. Applying big data analytics in cybersecurity is critical. By exploiting data from the networks and computers, analysts can discover useful network information from data. Decision makers can make more informative decisions by using this analysis, including what actions need to be performed, and improvement recommendations to policies, guidelines, procedures, tools, and other aspects of the network processes. Bringing together experts from academia, government laboratories, and industry, the book provides insight to both new and more experienced security professionals, as well as data analytics professionals who have varying levels of cybersecurity expertise. It covers a wide range of topics in cybersecurity, which include: Network forensics Threat analysis Vulnerability assessment Visualization Cyber training. In addition, emerging security domains such as the IoT, cloud computing, fog computing, mobile computing, and cyber-social networks are examined. The book first focuses on how big data analytics can be used in different aspects of cybersecurity including network forensics, root-cause analysis, and security training. Next it discusses big data challenges and solutions in such emerging cybersecurity domains as fog computing, IoT, and mobile app security. The book concludes by presenting the tools and datasets for future cybersecurity research.

Data Analytics for Cybersecurity

Data Analytics for Cybersecurity PDF Author: Vandana P. Janeja
Publisher:
ISBN: 9781108231954
Category : COMPUTERS
Languages : en
Pages :
Book Description
"As the world becomes increasingly connected, it is also more exposed to a myriad of cyber threats. We need to use multiple types of tools and techniques to learn and understand the evolving threat landscape. Data is a common thread linking various types of devices and end users. Analyzing data across different segments of cybersecurity domains, particularly data generated during cyber-attacks, can help us understand threats better, prevent future cyber-attacks, and provide insights into the evolving cyber threat landscape. This book takes a data oriented approach to studying cyber threats, showing in depth how traditional methods such as anomaly detection can be extended using data analytics and also applies data analytics to non-traditional views of cybersecurity, such as multi domain analysis, time series and spatial data analysis, and human-centered cybersecurity"--

Data Analytics and Decision Support for Cybersecurity

Data Analytics and Decision Support for Cybersecurity PDF Author: Iván Palomares Carrascosa
Publisher: Springer
ISBN: 3319594397
Category : Computers
Languages : en
Pages : 270
Book Description
The book illustrates the inter-relationship between several data management, analytics and decision support techniques and methods commonly adopted in Cybersecurity-oriented frameworks. The recent advent of Big Data paradigms and the use of data science methods, has resulted in a higher demand for effective data-driven models that support decision-making at a strategic level. This motivates the need for defining novel data analytics and decision support approaches in a myriad of real-life scenarios and problems, with Cybersecurity-related domains being no exception. This contributed volume comprises nine chapters, written by leading international researchers, covering a compilation of recent advances in Cybersecurity-related applications of data analytics and decision support approaches. In addition to theoretical studies and overviews of existing relevant literature, this book comprises a selection of application-oriented research contributions. The investigations undertaken across these chapters focus on diverse and critical Cybersecurity problems, such as Intrusion Detection, Insider Threats, Insider Threats, Collusion Detection, Run-Time Malware Detection, Intrusion Detection, E-Learning, Online Examinations, Cybersecurity noisy data removal, Secure Smart Power Systems, Security Visualization and Monitoring. Researchers and professionals alike will find the chapters an essential read for further research on the topic.

Big Data Analytics in Cognitive Social Media and Literary Texts

Big Data Analytics in Cognitive Social Media and Literary Texts PDF Author: Sanjiv Sharma
Publisher: Springer Nature
ISBN: 9811647291
Category : Language Arts & Disciplines
Languages : en
Pages : 300
Book Description
This book provides a comprehensive overview of the theory and praxis of Big Data Analytics and how these are used to extract cognition-related information from social media and literary texts. It presents analytics that transcends the borders of discipline-specific academic research and focuses on knowledge extraction, prediction, and decision-making in the context of individual, social, and national development. The content is divided into three main sections: the first of which discusses various approaches associated with Big Data Analytics, while the second addresses the security and privacy of big data in social media, and the last focuses on the literary text as the literary data in Big Data Analytics. Sharing valuable insights into the etiology behind human cognition and its reflection in social media and literary texts, the book benefits all those interested in analytics that can be applied to literature, history, philosophy, linguistics, literary theory, media & communication studies and computational/digital humanities.

Big Data Analytics Strategies for the Smart Grid

Big Data Analytics Strategies for the Smart Grid PDF Author: Carol L. Stimmel
Publisher: CRC Press
ISBN: 1482218291
Category : Computers
Languages : en
Pages : 256
Book Description
By implementing a comprehensive data analytics program, utility companies can meet the continually evolving challenges of modern grids that are operationally efficient, while reconciling the demands of greenhouse gas legislation and establishing a meaningful return on investment from smart grid deployments.Readable and accessible, Big Data Analytic

Big Data Analytics in Cybersecurity and IT Management

Big Data Analytics in Cybersecurity and IT Management PDF Author: Onur Savas
Publisher:
ISBN: 9781315154374
Category : Big data
Languages : en
Pages :
Book Description
The power of big data in cybersecurity -- Big data analytics for network forensics -- Dynamic analytics-driven assessment of vulnerabilities and exploitation -- Big data analytics for mobile app security -- Machine unlearning: repairing learning models in adversarial -- Environments -- Cybersecurity training -- Machine unlearning: repairing learning models in adversarial environments -- Big data analytics for mobile app security -- Security, privacy and trust in cloud computing: challenges and solutions -- Cybersecurity in internet of things (IOT) -- Data visualization for cyber security -- Analyzing deviant socio-technical behaviors using social network analysis and cyber forensics-based methodologies -- Security tools -- Data and research initiatives for cybersecurity analysis

Data Analytics for Business

Data Analytics for Business PDF Author: Fenio Annansingh
Publisher: Routledge
ISBN: 1000577902
Category : Business & Economics
Languages : en
Pages : 288
Book Description
Data analytics underpin our modern data-driven economy. This textbook explains the relevance of data analytics at the firm and industry levels, tracing the evolution and key components of the field, and showing how data analytics insights can be leveraged for business results. The first section of the text covers key topics such as data analytics tools, data mining, business intelligence, customer relationship management, and cybersecurity. The chapters then take an industry focus, exploring how data analytics can be used in particular settings to strengthen business decision-making. A range of sectors are examined, including financial services, accounting, marketing, sport, health care, retail, transport, and education. With industry case studies, clear definitions of terminology, and no background knowledge required, this text supports students in gaining a solid understanding of data analytics and its practical applications. PowerPoint slides, a test bank of questions, and an instructor’s manual are also provided as online supplements. This will be a valuable text for undergraduate level courses in data analytics, data mining, business intelligence, and related areas.