Description
Book SynopsisBig 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, oïers 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,
Table of Contents
Applying Big Data into Different Cybersecurity Aspects. The Power of Big Data in Cybersecurity. Big Data for Network Forensics. Dynamic Analytics-Driven Assessment of Vulnerabilities and Exploitation. Root Cause Analysis for Cybersecurity. Data Visualization for Cybersecurity. Cybersecurity Training. Machine Unlearning: Repairing Learning Models in Adversarial Environments. Big Data in Emerging Cybersecurity Domains. Big Data Analytics for Mobile App Security. Security, Privacy, and Trust in Cloud Computing. Cybersecurity in Internet of Things (IoT). Big Data Analytics for Security in Fog Computing. Analyzing Deviant Socio-Technical Behaviors Using Social Network Analysis and Cyber Forensics-Based Methodologies. Tools and Datasets for Cybersecurity. Security Tools. Data and Research Initiatives for Cybersecurity Analysis. Index.
