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Cybersecurity Analytics


Cybersecurity Analytics
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Cybersecurity Analytics


Cybersecurity Analytics
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Author : Rakesh M. Verma
language : en
Publisher: CRC Press
Release Date : 2019-11-25

Cybersecurity Analytics written by Rakesh M. Verma and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-25 with Mathematics categories.


Cybersecurity Analytics is for the cybersecurity student and professional who wants to learn data science techniques critical for tackling cybersecurity challenges, and for the data science student and professional who wants to learn about cybersecurity adaptations. Trying to build a malware detector, a phishing email detector, or just interested in finding patterns in your datasets? This book can let you do it on your own. Numerous examples and datasets links are included so that the reader can "learn by doing." Anyone with a basic college-level calculus course and some probability knowledge can easily understand most of the material. The book includes chapters containing: unsupervised learning, semi-supervised learning, supervised learning, text mining, natural language processing, and more. It also includes background on security, statistics, and linear algebra. The website for the book contains a listing of datasets, updates, and other resources for serious practitioners.



Applying Artificial Intelligence In Cybersecurity Analytics And Cyber Threat Detection


Applying Artificial Intelligence In Cybersecurity Analytics And Cyber Threat Detection
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Author : Shilpa Mahajan
language : en
Publisher: John Wiley & Sons
Release Date : 2024-04-02

Applying Artificial Intelligence In Cybersecurity Analytics And Cyber Threat Detection written by Shilpa Mahajan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-02 with Computers categories.


APPLYING ARTIFICIAL INTELLIGENCE IN CYBERSECURITY ANALYTICS AND CYBER THREAT DETECTION Comprehensive resource providing strategic defense mechanisms for malware, handling cybercrime, and identifying loopholes using artificial intelligence (AI) and machine learning (ML) Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection is a comprehensive look at state-of-the-art theory and practical guidelines pertaining to the subject, showcasing recent innovations, emerging trends, and concerns as well as applied challenges encountered, and solutions adopted in the fields of cybersecurity using analytics and machine learning. The text clearly explains theoretical aspects, framework, system architecture, analysis and design, implementation, validation, and tools and techniques of data science and machine learning to detect and prevent cyber threats. Using AI and ML approaches, the book offers strategic defense mechanisms for addressing malware, cybercrime, and system vulnerabilities. It also provides tools and techniques that can be applied by professional analysts to safely analyze, debug, and disassemble any malicious software they encounter. With contributions from qualified authors with significant experience in the field, Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection explores topics such as: Cybersecurity tools originating from computational statistics literature and pure mathematics, such as nonparametric probability density estimation, graph-based manifold learning, and topological data analysis Applications of AI to penetration testing, malware, data privacy, intrusion detection system (IDS), and social engineering How AI automation addresses various security challenges in daily workflows and how to perform automated analyses to proactively mitigate threats Offensive technologies grouped together and analyzed at a higher level from both an offensive and defensive standpoint Providing detailed coverage of a rapidly expanding field, Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection is an essential resource for a wide variety of researchers, scientists, and professionals involved in fields that intersect with cybersecurity, artificial intelligence, and machine learning.



Machine Learning Approaches In Cyber Security Analytics


Machine Learning Approaches In Cyber Security Analytics
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Author : Tony Thomas
language : en
Publisher: Springer Nature
Release Date : 2019-12-16

Machine Learning Approaches In Cyber Security Analytics written by Tony Thomas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-16 with Computers categories.


This book introduces various machine learning methods for cyber security analytics. With an overwhelming amount of data being generated and transferred over various networks, monitoring everything that is exchanged and identifying potential cyber threats and attacks poses a serious challenge for cyber experts. Further, as cyber attacks become more frequent and sophisticated, there is a requirement for machines to predict, detect, and identify them more rapidly. Machine learning offers various tools and techniques to automate and quickly predict, detect, and identify cyber attacks.



Big Data Analytics In Cybersecurity


Big Data Analytics In Cybersecurity
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Author : Onur Savas
language : en
Publisher: CRC Press
Release Date : 2017-09-18

Big Data Analytics In Cybersecurity written by Onur Savas and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-18 with Business & Economics categories.


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.



Cybersecurity Analytics


Cybersecurity Analytics
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Author : Rakesh M. Verma
language : en
Publisher: CRC Press
Release Date : 2019-11-27

Cybersecurity Analytics written by Rakesh M. Verma and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-27 with Mathematics categories.


Cybersecurity Analytics is for the cybersecurity student and professional who wants to learn data science techniques critical for tackling cybersecurity challenges, and for the data science student and professional who wants to learn about cybersecurity adaptations. Trying to build a malware detector, a phishing email detector, or just interested in finding patterns in your datasets? This book can let you do it on your own. Numerous examples and datasets links are included so that the reader can "learn by doing." Anyone with a basic college-level calculus course and some probability knowledge can easily understand most of the material. The book includes chapters containing: unsupervised learning, semi-supervised learning, supervised learning, text mining, natural language processing, and more. It also includes background on security, statistics, and linear algebra. The website for the book contains a listing of datasets, updates, and other resources for serious practitioners.



An Introduction To Cyber Security


An Introduction To Cyber Security
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Author : Simplilearn
language : en
Publisher: IndraStra Whitepapers
Release Date : 2019-12-20

An Introduction To Cyber Security written by Simplilearn and has been published by IndraStra Whitepapers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-20 with Computers categories.


Cybersecurity is undoubtedly one of the fastest-growing fields. However, there is an acute shortage of skilled workforce. The cybersecurity beginners guide aims at teaching security enthusiasts all about organizational digital assets’ security, give them an overview of how the field operates, applications of cybersecurity across sectors and industries, and skills and certifications one needs to build and scale up a career in this field.



Cybersecurity Data Science


Cybersecurity Data Science
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Author : Scott Mongeau
language : en
Publisher: Springer Nature
Release Date : 2021-10-01

Cybersecurity Data Science written by Scott Mongeau and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-01 with Computers categories.


This book encompasses a systematic exploration of Cybersecurity Data Science (CSDS) as an emerging profession, focusing on current versus idealized practice. This book also analyzes challenges facing the emerging CSDS profession, diagnoses key gaps, and prescribes treatments to facilitate advancement. Grounded in the management of information systems (MIS) discipline, insights derive from literature analysis and interviews with 50 global CSDS practitioners. CSDS as a diagnostic process grounded in the scientific method is emphasized throughout Cybersecurity Data Science (CSDS) is a rapidly evolving discipline which applies data science methods to cybersecurity challenges. CSDS reflects the rising interest in applying data-focused statistical, analytical, and machine learning-driven methods to address growing security gaps. This book offers a systematic assessment of the developing domain. Advocacy is provided to strengthen professional rigor and best practices in the emerging CSDS profession. This book will be of interest to a range of professionals associated with cybersecurity and data science, spanning practitioner, commercial, public sector, and academic domains. Best practices framed will be of interest to CSDS practitioners, security professionals, risk management stewards, and institutional stakeholders. Organizational and industry perspectives will be of interest to cybersecurity analysts, managers, planners, strategists, and regulators. Research professionals and academics are presented with a systematic analysis of the CSDS field, including an overview of the state of the art, a structured evaluation of key challenges, recommended best practices, and an extensive bibliography.



Data Analytics For Business Intelligence


Data Analytics For Business Intelligence
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Author : Zhaohao Sun
language : en
Publisher: CRC Press
Release Date : 2024-12-30

Data Analytics For Business Intelligence written by Zhaohao Sun and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-30 with Computers categories.


This book studies data, analytics, and intelligence using Boolean structure. Chapters dive into the theories, foundations, technologies, and methods of data, analytics, and intelligence. The primary aim of this book is to convey the theories and technologies of data, analytics, and intelligence with applications to readers based on systematic generalization and specialization. Sun uses the Boolean structure to deconstruct all books and papers related to data, analytics, and intelligence and to reorganize them to reshape the world of big data, data analytics, analytics intelligence, data science, and artificial intelligence. Multi-industry applications in business, management, and decision-making are provided. Cutting-edge theories, technologies, and applications of data, analytics, and intelligence and their integration are also explored. Overall, this book provides original insights on sharing computing, insight computing, platform computing, a calculus of intelligent analytics and intelligent business analytics, meta computing, data analyticizing, DDPP (descriptive, diagnostic, predictive, and prescriptive) computing, and analytics. This book is a useful resource with multi-industry applications for scientists, engineers, data analysts, educators, and university students.



Data Analytics For Business


Data Analytics For Business
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Author : Fenio Annansingh
language : en
Publisher: Routledge
Release Date : 2022-04-20

Data Analytics For Business written by Fenio Annansingh and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-20 with Business & Economics categories.


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.



Handbook Of Research On Current Trends In Cybersecurity And Educational Technology


Handbook Of Research On Current Trends In Cybersecurity And Educational Technology
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Author : Jimenez, Remberto
language : en
Publisher: IGI Global
Release Date : 2023-02-17

Handbook Of Research On Current Trends In Cybersecurity And Educational Technology written by Jimenez, Remberto and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-17 with Education categories.


There has been an increased use of technology in educational settings since the start of the COVID-19 pandemic. Despite the benefits of including such technologies to support education, there is still the need for vigilance to counter the inherent risk that comes with the use of such technologies as the protection of students and their information is paramount to the effective deployment of any technology in education. The Handbook of Research on Current Trends in Cybersecurity and Educational Technology explores the full spectrum of cybersecurity and educational technology today and brings awareness to the recent developments and use cases for emergent educational technology. Covering key topics such as artificial intelligence, gamification, robotics, and online learning, this premier reference source is ideal for computer scientists, industry professionals, policymakers, administrators, researchers, academicians, scholars, practitioners, instructors, and students.