Machine Intelligence and Big Data Analytics for Cybersecurity Applications PDF Download

Author: Onur Savas
Publisher: CRC Press
ISBN: 1498772161
Category : Business & Economics
Languages : en
Pages : 336

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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.

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.

Author: Mariya Ouaissa
Publisher: Springer Nature
ISBN: 303105752X
Category : Computers
Languages : en
Pages : 336

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Book Description
This book presents a collection of state-of-the-art artificial intelligence and big data analytics approaches to cybersecurity intelligence. It illustrates the latest trends in AI/ML-based strategic defense mechanisms against malware, vulnerabilities, cyber threats, as well as proactive countermeasures. It also introduces other trending technologies, such as blockchain, SDN, and IoT, and discusses their possible impact on improving security. The book discusses the convergence of AI/ML and big data in cybersecurity by providing an overview of theoretical, practical, and simulation concepts of computational intelligence and big data analytics used in different approaches of security. It also displays solutions that will help analyze complex patterns in user data and ultimately improve productivity. This book can be a source for researchers, students, and practitioners interested in the fields of artificial intelligence, cybersecurity, data analytics, and recent trends of networks.

Author: Onur Savas
Publisher:
ISBN: 9781315154374
Category : Big data
Languages : en
Pages :

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Book Description
The power of big data in cybersecurity -- Big data analytics for network forensics -- Dynamic analytics-driven assessment of vulnerabilities and exploitation -- Big data analytics for mobile app security -- Machine unlearning: repairing learning models in adversarial -- Environments -- Cybersecurity training -- Machine unlearning: repairing learning models in adversarial environments -- Big data analytics for mobile app security -- Security, privacy and trust in cloud computing: challenges and solutions -- Cybersecurity in internet of things (IOT) -- Data visualization for cyber security -- Analyzing deviant socio-technical behaviors using social network analysis and cyber forensics-based methodologies -- Security tools -- Data and research initiatives for cybersecurity analysis

Author: Yassine Maleh
Publisher: CRC Press
ISBN: 1000846695
Category : Computers
Languages : en
Pages : 310

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Book Description
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

Author: Iván Palomares Carrascosa
Publisher: Springer
ISBN: 3319594397
Category : Computers
Languages : en
Pages : 270

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Book Description
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.

Author: Bhavani Thuraisingham
Publisher: CRC Press
ISBN: 1351645765
Category : Computers
Languages : en
Pages : 953

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Book Description
Today's malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new computer defenses on the fly. Using the same algorithms that antivirus software uses to detect viruses, reactively adaptive malware deploys those algorithms to outwit antivirus defenses and to go undetected. This book provides details of the tools, the types of malware the tools will detect, implementation of the tools in a cloud computing framework and the applications for insider threat detection.

Author: Hans Weber
Publisher:
ISBN: 9781704795768
Category :
Languages : en
Pages : 70

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Book Description
This book will describe the concepts of Big Data, Data Science, Cybersecurity, and the analytics and metrics of these concepts in detail. This book will cover all the basic concepts of these technologies. In the present data-driven world, the maintenance of data is extremely important. This book will guide its readers on the impact of Big Data on the current businesses and companies, how data science is a promising new career, what is required by the data scientists these days and important languages that need to be learned in order to cope with the new requirements of the practical field of Data Science. Regarding the cybersecurity topic, this book will guide its readers, showing all the elementary theories of cybersecurity. This book includes the most famous kinds of threats and techniques used by hackers these days. It also covers the impact of cyber-security on businesses, how the impact of cyber threats can be reduced in companies, and the best practices that the companies can utilize in order to stay safe and sound over the web. All these guidelines will help small to medium-sized businesses to establish strong defense strategies for themselves. The last section of this book will explain the analytic and metrics used for big data, data science, and cybersecurity. The analytic techniques examine the IT infrastructure, whereas the metrics are responsible for measuring the well-organized performance of the company. The analytic and metrics guideline will help companies to understand their IT organization and the ways in which they can explain their performance to other individuals. By using these guidelines, any company can increase the value of their business. By using the latest technology and evaluating the company's structure, better results can be achieved in terms of the performance of the company.

Author: Pradip Kumar Das
Publisher: Springer Nature
ISBN: 981161007X
Category : Computers
Languages : en
Pages : 219

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Book Description
This book focuses on privacy and security concerns in big data and differentiates between privacy and security and privacy requirements in big data. It focuses on the results obtained after applying a systematic mapping study and implementation of security in the big data for utilizing in business under the establishment of “Business Intelligence”. The chapters start with the definition of big data, discussions why security is used in business infrastructure and how the security can be improved. In this book, some of the data security and data protection techniques are focused and it presents the challenges and suggestions to meet the requirements of computing, communication and storage capabilities for data mining and analytics applications with large aggregate data in business.

Author: Shibakali Gupta
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110605961
Category : Computers
Languages : en
Pages : 223

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Book Description
After a short description of the key concepts of big data the book explores on the secrecy and security threats posed especially by cloud based data storage. It delivers conceptual frameworks and models along with case studies of recent technology.