Advances In Cyber Security Analytics And Decision Systems
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Advances In Cyber Security Analytics And Decision Systems
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Author : Shishir K. Shandilya
language : en
Publisher: Springer Nature
Release Date : 2020-01-06
Advances In Cyber Security Analytics And Decision Systems written by Shishir K. Shandilya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-06 with Technology & Engineering categories.
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.
Advances In Cyber Security And Intelligent Analytics
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Author : Abhishek Verma
language : en
Publisher: CRC Press
Release Date : 2022-12-21
Advances In Cyber Security And Intelligent Analytics written by Abhishek 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 2022-12-21 with Computers categories.
We live in a digital world, where we use digital tools and smart devices to communicate over the Internet. In turn, an enormous amount of data gets generated. The traditional computing architectures are inefficient in storing and managing this massive amount of data. Unfortunately, the data cannot be ignored as it helps businesses to make better decisions, solve problems, understand performance, improve processes, and understand customers. Therefore, we need modern systems capable of handling and managing data efficiently. In the past few decades, many distributed computing paradigms have emerged, and we have noticed a substantial growth in the applications based on such emerging paradigms. Some well-known emerging computing paradigms include cloud computing, fog computing, and edge computing, which have leveraged the increase in the volume of data being generated every second. However, the distributed computing paradigms face critical challenges, including network management and cyber security. We have witnessed the development of various networking models—IoT, SDN, and ICN—to support modern systems requirements. However, they are undergoing rapid changes and need special attention. The main issue faced by these paradigms is that traditional solutions cannot be directly applied to address the challenges. Therefore, there is a significant need to develop improved network management and cyber security solutions. To this end, this book highlights the challenges faced by emerging paradigms and presents the recent developments made to address the challenges. More specifically, it presents a detailed study on security issues in distributed computing environments and their possible solutions, followed by applications of medical IoT, deep learning, IoV, healthcare, etc.
Advances In Cyber Security And Intelligent Analytics
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Author : Abhishek Verma
language : en
Publisher: CRC Press
Release Date : 2022-12-21
Advances In Cyber Security And Intelligent Analytics written by Abhishek 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 2022-12-21 with Computers categories.
We live in a digital world, where we use digital tools and smart devices to communicate over the Internet. In turn, an enormous amount of data gets generated. The traditional computing architectures are inefficient in storing and managing this massive amount of data. Unfortunately, the data cannot be ignored as it helps businesses to make better decisions, solve problems, understand performance, improve processes, and understand customers. Therefore, we need modern systems capable of handling and managing data efficiently. In the past few decades, many distributed computing paradigms have emerged, and we have noticed a substantial growth in the applications based on such emerging paradigms. Some well-known emerging computing paradigms include cloud computing, fog computing, and edge computing, which have leveraged the increase in the volume of data being generated every second. However, the distributed computing paradigms face critical challenges, including network management and cyber security. We have witnessed the development of various networking models—IoT, SDN, and ICN—to support modern systems requirements. However, they are undergoing rapid changes and need special attention. The main issue faced by these paradigms is that traditional solutions cannot be directly applied to address the challenges. Therefore, there is a significant need to develop improved network management and cyber security solutions. To this end, this book highlights the challenges faced by emerging paradigms and presents the recent developments made to address the challenges. More specifically, it presents a detailed study on security issues in distributed computing environments and their possible solutions, followed by applications of medical IoT, deep learning, IoV, healthcare, etc.
Data Analytics And Decision Support For Cybersecurity
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Author : Iván Palomares Carrascosa
language : en
Publisher: Springer
Release Date : 2017-08-01
Data Analytics And Decision Support For Cybersecurity written by Iván Palomares Carrascosa and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-01 with Computers categories.
The book illustrates the inter-relationship between several data management, analytics and decision support techniques and methods commonly adopted in Cybersecurity-oriented frameworks. The recent advent of Big Data paradigms and the use of data science methods, has resulted in a higher demand for effective data-driven models that support decision-making at a strategic level. This motivates the need for defining novel data analytics and decision support approaches in a myriad of real-life scenarios and problems, with Cybersecurity-related domains being no exception. This contributed volume comprises nine chapters, written by leading international researchers, covering a compilation of recent advances in Cybersecurity-related applications of data analytics and decision support approaches. In addition to theoretical studies and overviews of existing relevant literature, this book comprises a selection of application-oriented research contributions. The investigations undertaken across these chapters focus on diverse and critical Cybersecurity problems, such as Intrusion Detection, Insider Threats, Insider Threats, Collusion Detection, Run-Time Malware Detection, Intrusion Detection, E-Learning, Online Examinations, Cybersecurity noisy data removal, Secure Smart Power Systems, Security Visualization and Monitoring. Researchers and professionals alike will find the chapters an essential read for further research on the topic.
Meeting Security Challenges Through Data Analytics And Decision Support
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Author : E. Shahbazian
language : en
Publisher: IOS Press
Release Date : 2016-11-24
Meeting Security Challenges Through Data Analytics And Decision Support written by E. Shahbazian and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-24 with Computers categories.
The sheer quantity of widely diverse data which now results from multiple sources presents a problem for decision-makers and analysts, who are finding it impossible to cope with the ever-increasing flow of material. This has potentially serious consequences for the quality of decisions and operational processes in areas such as counterterrorism and security. This book presents the papers delivered at the NATO Advanced Research Workshop (ARW) 'Meeting Security Challenges through Data Analytics and Decision Support’, held in Aghveran, Armenia, in June 2015. The aim of the conference was to promote and enhance cooperation and dialogue between NATO and Partner countries on the subject of effective decision support for security applications. The attendance of many leading scientists from a variety of backgrounds and disciplines provided the opportunity to improve mutual understanding, as well as cognizance of the specific requirements and issues of Cyber Physical Social Systems (CPPS) and the technical advances pertinent to all collaborative human-centric information support systems in a variety of applications. The book is divided into 3 sections: counter terrorism: methodology and applications; maritime and border security; and cyber security, and will be of interest to all those involved in decision-making processes based on the analysis of big data.
Machine Intelligence And Big Data Analytics For Cybersecurity Applications
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Author : Yassine Maleh
language : en
Publisher: Springer Nature
Release Date : 2020-12-14
Machine Intelligence And Big Data Analytics For Cybersecurity Applications written by Yassine Maleh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-14 with Computers categories.
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
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Author : Zheng Xu
language : en
Publisher: Springer Nature
Release Date : 2022-02-26
Cyber Security Intelligence And Analytics written by Zheng Xu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-26 with Technology & Engineering categories.
This book presents the outcomes of the 2022 4th International Conference on Cyber Security Intelligence and Analytics (CSIA 2022), 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. Due to COVID-19, authors, keynote speakers and PC committees will attend the conference online.
Big Data Analytics And Intelligent Systems For Cyber Threat Intelligence
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Author : Yassine Maleh
language : en
Publisher: CRC Press
Release Date : 2023-04-28
Big Data Analytics And Intelligent Systems For Cyber Threat Intelligence written by Yassine Maleh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-28 with Computers categories.
In recent years, a considerable amount of effort has been devoted to cyber-threat protection of computer systems which is one of the most critical cybersecurity tasks for single users and businesses since even a single attack can result in compromised data and sufficient losses. Massive losses and frequent attacks dictate the need for accurate and timely detection methods. Current static and dynamic methods do not provide efficient detection, especially when dealing with zero-day attacks. For this reason, big data analytics and machine intelligencebased techniques can be used. This book brings together researchers in the field of big data analytics and intelligent systems for cyber threat intelligence CTI and key data to advance the mission of anticipating, prohibiting, preventing, preparing, and responding to internal security. The wide variety of topics it presents offers readers multiple perspectives on various disciplines related to big data analytics and intelligent systems for cyber threat intelligence applications. Technical topics discussed in the book include: • Big data analytics for cyber threat intelligence and detection • Artificial intelligence analytics techniques • Real-time situational awareness • Machine learning techniques for CTI • Deep learning techniques for CTI • Malware detection and prevention techniques • Intrusion and cybersecurity threat detection and analysis • Blockchain and machine learning techniques for CTI
Handbook Of Big Data Analytics And Forensics
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Author : Kim-Kwang Raymond Choo
language : en
Publisher: Springer Nature
Release Date : 2021-12-02
Handbook Of Big Data Analytics And Forensics written by Kim-Kwang Raymond Choo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-02 with Computers categories.
This handbook discusses challenges and limitations in existing solutions, and presents state-of-the-art advances from both academia and industry, in big data analytics and digital forensics. The second chapter comprehensively reviews IoT security, privacy, and forensics literature, focusing on IoT and unmanned aerial vehicles (UAVs). The authors propose a deep learning-based approach to process cloud’s log data and mitigate enumeration attacks in the third chapter. The fourth chapter proposes a robust fuzzy learning model to protect IT-based infrastructure against advanced persistent threat (APT) campaigns. Advanced and fair clustering approach for industrial data, which is capable of training with huge volume of data in a close to linear time is introduced in the fifth chapter, as well as offering an adaptive deep learning model to detect cyberattacks targeting cyber physical systems (CPS) covered in the sixth chapter. The authors evaluate the performance of unsupervised machine learning for detecting cyberattacks against industrial control systems (ICS) in chapter 7, and the next chapter presents a robust fuzzy Bayesian approach for ICS’s cyber threat hunting. This handbook also evaluates the performance of supervised machine learning methods in identifying cyberattacks against CPS. The performance of a scalable clustering algorithm for CPS’s cyber threat hunting and the usefulness of machine learning algorithms for MacOS malware detection are respectively evaluated. This handbook continues with evaluating the performance of various machine learning techniques to detect the Internet of Things malware. The authors demonstrate how MacOSX cyberattacks can be detected using state-of-the-art machine learning models. In order to identify credit card frauds, the fifteenth chapter introduces a hybrid model. In the sixteenth chapter, the editors propose a model that leverages natural language processing techniques for generating a mapping between APT-related reports and cyber kill chain. A deep learning-based approach to detect ransomware is introduced, as well as a proposed clustering approach to detect IoT malware in the last two chapters. This handbook primarily targets professionals and scientists working in Big Data, Digital Forensics, Machine Learning, Cyber Security Cyber Threat Analytics and Cyber Threat Hunting as a reference book. Advanced level-students and researchers studying and working in Computer systems, Computer networks and Artificial intelligence will also find this reference useful.
Cyber Security And Global Information Assurance Threat Analysis And Response Solutions
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Author : Knapp, Kenneth J.
language : en
Publisher: IGI Global
Release Date : 2009-04-30
Cyber Security And Global Information Assurance Threat Analysis And Response Solutions written by Knapp, Kenneth J. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-30 with Computers categories.
"This book provides a valuable resource by addressing the most pressing issues facing cyber-security from both a national and global perspective"--Provided by publisher.