| Author | : Mark Talabis,Robert McPherson,Inez Miyamoto,Jason Martin |
| Publisher | : Syngress |
| Release Date | : 2014-11-25 |
| ISBN 10 | : 0128005068 |
| Pages | : 182 pages |
Information Security Analytics gives you insights into the practice of analytics and, more importantly, how you can utilize analytic techniques to identify trends and outliers that may not be possible to identify using traditional security analysis techniques. Information Security Analytics dispels the myth that analytics within the information security domain is limited to just security incident and event management systems and basic network analysis. Analytic techniques can help you mine data and identify patterns and relationships in any form of security data. Using the techniques covered in this book, you will be able to gain security insights into unstructured big data of any type. The authors of Information Security Analytics bring a wealth of analytics experience to demonstrate practical, hands-on techniques through case studies and using freely-available tools that will allow you to find anomalies and outliers by combining disparate data sets. They also teach you everything you need to know about threat simulation techniques and how to use analytics as a powerful decision-making tool to assess security control and process requirements within your organization. Ultimately, you will learn how to use these simulation techniques to help predict and profile potential risks to your organization. Written by security practitioners, for security practitioners Real-world case studies and scenarios are provided for each analytics technique Learn about open-source analytics and statistical packages, tools, and applications Step-by-step guidance on how to use analytics tools and how they map to the techniques and scenarios provided Learn how to design and utilize simulations for "what-if" scenarios to simulate security events and processes Learn how to utilize big data techniques to assist in incident response and intrusion analysis
| Author | : Mark Talabis,Robert McPherson,I. Miyamoto,Jason Martin |
| Publisher | : Syngress Press |
| Release Date | : 2014-11-26 |
| ISBN 10 | : 9780128002070 |
| Pages | : 182 pages |
Information Security Analytics gives you insights into the practice of analytics and, more importantly, how you can utilize analytic techniques to identify trends and outliers that may not be possible to identify using traditional security analysis techniques. Information Security Analytics dispels the myth that analytics within the information security domain is limited to just security incident and event management systems and basic network analysis. Analytic techniques can help you mine data and identify patterns and relationships in any form of security data. Using the techniques covered in this book, you will be able to gain security insights into unstructured big data of any type. The authors of Information Security Analytics bring a wealth of analytics experience to demonstrate practical, hands-on techniques through case studies and using freely-available tools that will allow you to find anomalies and outliers by combining disparate data sets. They also teach you everything you need to know about threat simulation techniques and how to use analytics as a powerful decision-making tool to assess security control and process requirements within your organization. Ultimately, you will learn how to use these simulation techniques to help predict and profile potential risks to your organization. Written by security practitioners, for security practitioners Real-world case studies and scenarios are provided for each analytics technique Learn about open-source analytics and statistical packages, tools, and applications Step-by-step guidance on how to use analytics tools and how they map to the techniques and scenarios provided Learn how to design and utilize simulations for "what-if" scenarios to simulate security events and processes Learn how to utilize big data techniques to assist in incident response and intrusion analysis
| Author | : Mohuiddin Ahmed,Abu S.S.M Barkat Ullah,Al-Sakib Khan Pathan |
| Publisher | : CRC Press |
| Release Date | : 2020-01-27 |
| ISBN 10 | : 1000765849 |
| Pages | : 258 pages |
Security Analytics for the Internet of Everything compiles the latest trends, technologies, and applications in this emerging field. It includes chapters covering emerging security trends, cyber governance, artificial intelligence in cybersecurity, and cyber challenges. Contributions from leading international experts are included. The target audience for the book is graduate students, professionals, and researchers working in the fields of cybersecurity, computer networks, communications, and the Internet of Everything (IoE). The book also includes some chapters written in a tutorial style so that general readers can easily grasp some of the ideas.
| Author | : Martti Lehto,Pekka Neittaanmäki |
| Publisher | : Springer |
| Release Date | : 2015-05-30 |
| ISBN 10 | : 3319183028 |
| Pages | : 269 pages |
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.
| Author | : Tony Thomas,Athira P. Vijayaraghavan,Sabu Emmanuel |
| Publisher | : Springer Nature |
| Release Date | : 2019-12-16 |
| ISBN 10 | : 9811517061 |
| Pages | : 209 pages |
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.
| Author | : Izzat M Alsmadi,George Karabatis,Ahmed Aleroud |
| Publisher | : Springer |
| Release Date | : 2016-10-21 |
| ISBN 10 | : 3319442570 |
| Pages | : 379 pages |
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.
| Author | : N.A |
| Publisher | : N.A |
| Release Date | : |
| ISBN 10 | : |
| Pages | : 329 pages |
| Author | : Shishir K. Shandilya,Neal Wagner,Atulya K. Nagar |
| Publisher | : Springer Nature |
| Release Date | : 2020-01-06 |
| ISBN 10 | : 3030193535 |
| Pages | : 145 pages |
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.
| Author | : Zheng Xu,Kim-Kwang Raymond Choo,Ali Dehghantanha,Reza Parizi,Mohammad Hammoudeh |
| Publisher | : Springer |
| Release Date | : 2019-04-24 |
| ISBN 10 | : 3030152359 |
| Pages | : 1453 pages |
This book presents the outcomes of the 2019 International Conference on Cyber Security Intelligence and Analytics (CSIA2019), an international conference dedicated to promoting novel theoretical and applied research advances in the interdisciplinary field of cyber security, particularly focusing on threat intelligence, analytics, and countering cyber crime. The conference provides a forum for presenting and discussing innovative ideas, cutting-edge research findings, and novel techniques, methods and applications on all aspects of Cyber Security Intelligence and Analytics.
| Author | : Onur Savas,Julia Deng |
| Publisher | : CRC Press |
| Release Date | : 2017-09-18 |
| ISBN 10 | : 1498772161 |
| Pages | : 336 pages |
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.
| Author | : Izzat Alsmadi |
| Publisher | : Springer |
| Release Date | : 2019-01-24 |
| ISBN 10 | : 3030023605 |
| Pages | : 354 pages |
This textbook is for courses in cyber security education that follow National Initiative for Cybersecurity Education (NICE) KSAs work roles and framework, that adopt the Competency-Based Education (CBE) method. The book follows the CBT (KSA) general framework, meaning each chapter contains three sections, knowledge and questions, and skills/labs for Skills and Abilities. The author makes an explicit balance between knowledge and skills material in information security, giving readers immediate applicable skills. The book is divided into seven parts: Securely Provision; Operate and Maintain; Oversee and Govern; Protect and Defend; Analysis; Operate and Collect; Investigate. All classroom materials (in the book an ancillary) adhere to the NICE framework. Mirrors classes set up by the National Initiative for Cybersecurity Education (NICE) Adopts the Competency-Based Education (CBE) method of teaching, used by universities, corporations, and in government training Includes content and ancillaries that provide skill-based instruction on compliance laws, information security standards, risk response and recovery, and more
| Author | : Rakesh M. Verma,David J. Marchette |
| Publisher | : N.A |
| Release Date | : 2020 |
| ISBN 10 | : 9780367346027 |
| Pages | : 329 pages |
"This book organizes in one place the mathematics, probability, statistics and machine learning information that is required for a practitioner of cybersecurity analytics, as well as the basics of cybersecurity needed for a practitioner"--