Cybersecurity Analytics

Cybersecurity Analytics PDF Author: Rakesh M. Verma
Publisher: CRC Press
ISBN: 1000727653
Category : Mathematics
Languages : en
Pages : 357

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Book Description
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.

Cybersecurity Analytics

Cybersecurity Analytics PDF Author: Rakesh M. Verma
Publisher: CRC Press
ISBN: 1000727653
Category : Mathematics
Languages : en
Pages : 357

Get Book

Book Description
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.

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 : 452

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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 Learning Approaches in Cyber Security Analytics

Machine Learning Approaches in Cyber Security Analytics PDF Author: Tony Thomas
Publisher: Springer Nature
ISBN: 9811517061
Category : Computers
Languages : en
Pages : 217

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Book Description
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.

Cyber Security: Analytics, Technology and Automation

Cyber Security: Analytics, Technology and Automation PDF Author: Martti Lehto
Publisher: Springer
ISBN: 3319183028
Category : Computers
Languages : en
Pages : 269

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Book Description
The book, in addition to the cyber threats and technology, processes cyber security from many sides as a social phenomenon and how the implementation of the cyber security strategy is carried out. The book gives a profound idea of the most spoken phenomenon of this time. The book is suitable for a wide-ranging audience from graduate to professionals/practitioners and researchers. Relevant disciplines for the book are Telecommunications / Network security, Applied mathematics / Data analysis, Mobile systems / Security, Engineering / Security of critical infrastructure and Military science / Security.

Advances in Cyber Security Analytics and Decision Systems

Advances in Cyber Security Analytics and Decision Systems PDF Author: Shishir K. Shandilya
Publisher: Springer Nature
ISBN: 3030193535
Category : Technology & Engineering
Languages : en
Pages : 153

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Book Description
This book contains research contributions from leading cyber security scholars from around the world. The authors provide comprehensive coverage of various cyber security topics, while highlighting recent trends. The book also contains a compendium of definitions and explanations of concepts, processes, acronyms, and comprehensive references on existing literature and research on cyber security and analytics, information sciences, decision systems, digital forensics, and related fields. As a whole, the book is a solid reference for dynamic and innovative research in the field, with a focus on design and development of future-ready cyber security measures. Topics include defenses against ransomware, phishing, malware, botnets, insider threats, and many others.

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

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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.

Cyber Security Intelligence and Analytics

Cyber Security Intelligence and Analytics PDF Author: Zheng Xu
Publisher: Springer Nature
ISBN: 3030433064
Category : Technology & Engineering
Languages : en
Pages : 829

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Book Description
This book presents the outcomes of the 2020 International Conference on Cyber Security Intelligence and Analytics (CSIA 2020), which was dedicated to promoting novel theoretical and applied research advances in the interdisciplinary field of cyber security, particularly those focusing on threat intelligence, analytics, and preventing cyber crime. The conference provides a forum for presenting and discussing innovative ideas, cutting-edge research findings, and novel techniques, methods, and applications concerning all aspects of cyber security intelligence and analytics. CSIA 2020, which was held in Haikou, China on February 28–29, 2020, built on the previous conference in Wuhu, China (2019), and marks the series’ second successful installment.

Information Fusion for Cyber-Security Analytics

Information Fusion for Cyber-Security Analytics PDF Author: Izzat M Alsmadi
Publisher: Springer
ISBN: 3319442570
Category : Technology & Engineering
Languages : en
Pages : 379

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Book Description
This book highlights several gaps that have not been addressed in existing cyber security research. It first discusses the recent attack prediction techniques that utilize one or more aspects of information to create attack prediction models. The second part is dedicated to new trends on information fusion and their applicability to cyber security; in particular, graph data analytics for cyber security, unwanted traffic detection and control based on trust management software defined networks, security in wireless sensor networks & their applications, and emerging trends in security system design using the concept of social behavioral biometric. The book guides the design of new commercialized tools that can be introduced to improve the accuracy of existing attack prediction models. Furthermore, the book advances the use of Knowledge-based Intrusion Detection Systems (IDS) to complement existing IDS technologies. It is aimed towards cyber security researchers.

Business Analytics and Cyber Security Management in Organizations

Business Analytics and Cyber Security Management in Organizations PDF Author: Rajagopal,
Publisher: IGI Global
ISBN: 1522509038
Category : Computers
Languages : en
Pages : 346

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Book Description
Traditional marketing techniques have become outdated by the emergence of the internet, and for companies to survive in the new technological marketplace, they must adopt digital marketing and business analytics practices. Unfortunately, with the benefits of improved storage and flow of information comes the risk of cyber-attack. Business Analytics and Cyber Security Management in Organizations compiles innovative research from international professionals discussing the opportunities and challenges of the new era of online business. Outlining updated discourse for business analytics techniques, strategies for data storage, and encryption in emerging markets, this book is ideal for business professionals, practicing managers, and students of business.

Data Analysis for Network Cyber-Security

Data Analysis for Network Cyber-Security PDF Author: Niall Adams
Publisher: World Scientific
ISBN: 1783263768
Category : Computers
Languages : en
Pages : 200

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Book Description
There is increasing pressure to protect computer networks against unauthorized intrusion, and some work in this area is concerned with engineering systems that are robust to attack. However, no system can be made invulnerable. Data Analysis for Network Cyber-Security focuses on monitoring and analyzing network traffic data, with the intention of preventing, or quickly identifying, malicious activity. Such work involves the intersection of statistics, data mining and computer science. Fundamentally, network traffic is relational, embodying a link between devices. As such, graph analysis approaches are a natural candidate. However, such methods do not scale well to the demands of real problems, and the critical aspect of the timing of communications events is not accounted for in these approaches. This book gathers papers from leading researchers to provide both background to the problems and a description of cutting-edge methodology. The contributors are from diverse institutions and areas of expertise and were brought together at a workshop held at the University of Bristol in March 2013 to address the issues of network cyber security. The workshop was supported by the Heilbronn Institute for Mathematical Research. Contents:Inference for Graphs and Networks: Adapting Classical Tools to Modern Data (Benjamin P Olding and Patrick J Wolfe)Rapid Detection of Attacks in Computer Networks by Quickest Changepoint Detection Methods (Alexander G Tartakovsky)Statistical Detection of Intruders Within Computer Networks Using Scan Statistics (Joshua Neil, Curtis Storlie, Curtis Hash and Alex Brugh)Characterizing Dynamic Group Behavior in Social Networks for Cybernetics (Sumeet Dua and Pradeep Chowriappa)Several Approaches for Detecting Anomalies in Network Traffic Data (Céline Lévy-Leduc)Monitoring a Device in a Communication Network (Nicholas A Heard and Melissa Turcotte) Readership: Researchers and graduate students in the fields of network traffic data analysis and network cyber security. Key Features:This book is unique in being a treatise on the statistical analysis of network traffic dataThe contributors are leading researches in the field and will give authoritative descriptions of cutting edge methodologyThe book features material from diverse areas, and as such forms a unified view of network cyber securityKeywords:Network Data Analysis;Cyber Security;Change Detection;Anomaly Detection