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Big Data Analytics in Cybersecurity Vital Source e-bog
Onur Savas
(2017)
Big Data Analytics in Cybersecurity
Onur Savas og Julia Deng
(2017)
Sprog: Engelsk
om ca. 10 hverdage
Detaljer om varen
- 1. Udgave
- Vital Source searchable e-book (Reflowable pages)
- Udgiver: Taylor & Francis (September 2017)
- ISBN: 9781351650410
Bookshelf online: 5 år fra købsdato.
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Detaljer om varen
- Hardback: 336 sider
- Udgiver: Auerbach Publishers, Incorporated (September 2017)
- Forfattere: Onur Savas og Julia Deng
- ISBN: 9781498772129
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.
I. Applying Big Data into Different Cybersecurity Aspects
1. The Power of Big Data in Cybersecurity Song Luo, Malek Ben Salem, and Yan Zhai
2. Big Data for Network Forensics Yi Cheng, Tung Thanh Nguyen, Hui Zeng, and Julia Deng
3. Dynamic Analytics-Driven Assessment of Vulnerabilities and Exploitation Hasan Cam, Magnus Ljungberg, Akhilomen Oniha, and Alexia Schulz
4. Root Cause Analysis for Cybersecurity Engin Kirda and Amin Kharraz
5. Data Visualization for Cybersecurity Lane Harrison
6. Cybersecurity Training Bob Pokorny
7. Machine Unlearning: Repairing Learning Models in Adversarial Environments Yinzhi Cao
II. Big Data in Emerging Cybersecurity Domains
8. Big Data Analytics for Mobile App Security Doina Caragea and Xinming Ou
9. Security, Privacy, and Trust in Cloud Computing Yuhong Liu, Ruiwen Li, Songjie Cai, and Yan (Lindsay) Sun
10. Cybersecurity in Internet of Things (IoT) Wenlin Han and Yang Xiao
11. Big Data Analytics for Security in Fog Computing Shanhe Yi and Qun Li
12. Analyzing Deviant Socio-Technical Behaviors Using Social Network Analysis and Cyber Forensics-Based Methodologies Samer Al-Khateeb, Muhammad Hussain, and Nitin Agarwal
III. Tools and Datasets for Cybersecurity
13. Security Tools Matthew Matchen
14. Data and Research Initiatives for Cybersecurity Analysis Julia Deng and Onur Savas
Index