Data Science In Cybersecurity And Cyberthreat Intelligence

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Data Science in Cybersecurity and Cyberthreat Intelligence

Author : Leslie F. Sikos
Publisher : Springer Nature
ISBN 13 : 3030387887
Total Pages : 140 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Data Science in Cybersecurity and Cyberthreat Intelligence by : Leslie F. Sikos

Download or read book Data Science in Cybersecurity and Cyberthreat Intelligence written by Leslie F. Sikos and published by Springer Nature. This book was released on 2020-02-05 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of state-of-the-art approaches to utilizing machine learning, formal knowledge bases and rule sets, and semantic reasoning to detect attacks on communication networks, including IoT infrastructures, to automate malicious code detection, to efficiently predict cyberattacks in enterprises, to identify malicious URLs and DGA-generated domain names, and to improve the security of mHealth wearables. This book details how analyzing the likelihood of vulnerability exploitation using machine learning classifiers can offer an alternative to traditional penetration testing solutions. In addition, the book describes a range of techniques that support data aggregation and data fusion to automate data-driven analytics in cyberthreat intelligence, allowing complex and previously unknown cyberthreats to be identified and classified, and countermeasures to be incorporated in novel incident response and intrusion detection mechanisms.

Data Science in Cybersecurity and Cyberthreat Intelligence

Author : Leslie F. Sikos
Publisher :
ISBN 13 : 9783030387891
Total Pages : 0 pages
Book Rating : 4.3/5 (878 download)

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Book Synopsis Data Science in Cybersecurity and Cyberthreat Intelligence by : Leslie F. Sikos

Download or read book Data Science in Cybersecurity and Cyberthreat Intelligence written by Leslie F. Sikos and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of state-of-the-art approaches to utilizing machine learning, formal knowledge bases and rule sets, and semantic reasoning to detect attacks on communication networks, including IoT infrastructures, to automate malicious code detection, to efficiently predict cyberattacks in enterprises, to identify malicious URLs and DGA-generated domain names, and to improve the security of mHealth wearables. This book details how analyzing the likelihood of vulnerability exploitation using machine learning classifiers can offer an alternative to traditional penetration testing solutions. In addition, the book describes a range of techniques that support data aggregation and data fusion to automate data-driven analytics in cyberthreat intelligence, allowing complex and previously unknown cyberthreats to be identified and classified, and countermeasures to be incorporated in novel incident response and intrusion detection mechanisms.

Data Science For Cyber-security

Author : Adams Niall M
Publisher : World Scientific
ISBN 13 : 178634565X
Total Pages : 304 pages
Book Rating : 4.7/5 (863 download)

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Book Synopsis Data Science For Cyber-security by : Adams Niall M

Download or read book Data Science For Cyber-security written by Adams Niall M and published by World Scientific. This book was released on 2018-09-25 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cyber-security is a matter of rapidly growing importance in industry and government. This book provides insight into a range of data science techniques for addressing these pressing concerns.The application of statistical and broader data science techniques provides an exciting growth area in the design of cyber defences. Networks of connected devices, such as enterprise computer networks or the wider so-called Internet of Things, are all vulnerable to misuse and attack, and data science methods offer the promise to detect such behaviours from the vast collections of cyber traffic data sources that can be obtained. In many cases, this is achieved through anomaly detection of unusual behaviour against understood statistical models of normality.This volume presents contributed papers from an international conference of the same name held at Imperial College. Experts from the field have provided their latest discoveries and review state of the art technologies.

Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence

Author : Yassine Maleh
Publisher : CRC Press
ISBN 13 : 1000846695
Total Pages : 310 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence by : Yassine Maleh

Download or read book Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence written by Yassine Maleh and published by CRC Press. This book was released on 2023-04-28 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Machine Intelligence and Big Data Analytics for Cybersecurity Applications

Author : Yassine Maleh
Publisher : Springer Nature
ISBN 13 : 303057024X
Total Pages : 539 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Machine Intelligence and Big Data Analytics for Cybersecurity Applications by : Yassine Maleh

Download or read book Machine Intelligence and Big Data Analytics for Cybersecurity Applications written by Yassine Maleh and published by Springer Nature. This book was released on 2020-12-14 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Threat Intelligence

Author : Ali Dehghantanha
Publisher : Springer
ISBN 13 : 3319739514
Total Pages : 334 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Cyber Threat Intelligence by : Ali Dehghantanha

Download or read book Cyber Threat Intelligence written by Ali Dehghantanha and published by Springer. This book was released on 2018-04-27 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with up-to-date research of emerging cyber threats and defensive mechanisms, which are timely and essential. It covers cyber threat intelligence concepts against a range of threat actors and threat tools (i.e. ransomware) in cutting-edge technologies, i.e., Internet of Things (IoT), Cloud computing and mobile devices. This book also provides the technical information on cyber-threat detection methods required for the researcher and digital forensics experts, in order to build intelligent automated systems to fight against advanced cybercrimes. The ever increasing number of cyber-attacks requires the cyber security and forensic specialists to detect, analyze and defend against the cyber threats in almost real-time, and with such a large number of attacks is not possible without deeply perusing the attack features and taking corresponding intelligent defensive actions – this in essence defines cyber threat intelligence notion. However, such intelligence would not be possible without the aid of artificial intelligence, machine learning and advanced data mining techniques to collect, analyze, and interpret cyber-attack campaigns which is covered in this book. This book will focus on cutting-edge research from both academia and industry, with a particular emphasis on providing wider knowledge of the field, novelty of approaches, combination of tools and so forth to perceive reason, learn and act on a wide range of data collected from different cyber security and forensics solutions. This book introduces the notion of cyber threat intelligence and analytics and presents different attempts in utilizing machine learning and data mining techniques to create threat feeds for a range of consumers. Moreover, this book sheds light on existing and emerging trends in the field which could pave the way for future works. The inter-disciplinary nature of this book, makes it suitable for a wide range of audiences with backgrounds in artificial intelligence, cyber security, forensics, big data and data mining, distributed systems and computer networks. This would include industry professionals, advanced-level students and researchers that work within these related fields.

Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection

Author : Shilpa Mahajan
Publisher : John Wiley & Sons
ISBN 13 : 139419644X
Total Pages : 373 pages
Book Rating : 4.3/5 (941 download)

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Book Synopsis Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection by : Shilpa Mahajan

Download or read book Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection written by Shilpa Mahajan and published by John Wiley & Sons. This book was released on 2024-06-12 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Cyber Security 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 Cyber Security 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 Cyber Security 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.

Collaborative Cyber Threat Intelligence

Author : Florian Skopik
Publisher : CRC Press
ISBN 13 : 1315397889
Total Pages : 293 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Collaborative Cyber Threat Intelligence by : Florian Skopik

Download or read book Collaborative Cyber Threat Intelligence written by Florian Skopik and published by CRC Press. This book was released on 2017-10-16 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: Threat intelligence is a surprisingly complex topic that goes far beyond the obvious technical challenges of collecting, modelling and sharing technical indicators. Most books in this area focus mainly on technical measures to harden a system based on threat intel data and limit their scope to single organizations only. This book provides a unique angle on the topic of national cyber threat intelligence and security information sharing. It also provides a clear view on ongoing works in research laboratories world-wide in order to address current security concerns at national level. It allows practitioners to learn about upcoming trends, researchers to share current results, and decision makers to prepare for future developments.

Data Analytics and Decision Support for Cybersecurity

Author : Iván Palomares Carrascosa
Publisher : Springer
ISBN 13 : 3319594397
Total Pages : 270 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Data Analytics and Decision Support for Cybersecurity by : Iván Palomares Carrascosa

Download or read book Data Analytics and Decision Support for Cybersecurity written by Iván Palomares Carrascosa and published by Springer. This book was released on 2017-08-01 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Cybersecurity Data Science

Author : Scott Mongeau
Publisher : Springer Nature
ISBN 13 : 3030748960
Total Pages : 410 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Cybersecurity Data Science by : Scott Mongeau

Download or read book Cybersecurity Data Science written by Scott Mongeau and published by Springer Nature. This book was released on 2021-10-01 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Mastering Cyber Intelligence

Author : Jean Nestor M. Dahj
Publisher : Packt Publishing Ltd
ISBN 13 : 1800208286
Total Pages : 528 pages
Book Rating : 4.8/5 (2 download)

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Book Synopsis Mastering Cyber Intelligence by : Jean Nestor M. Dahj

Download or read book Mastering Cyber Intelligence written by Jean Nestor M. Dahj and published by Packt Publishing Ltd. This book was released on 2022-04-29 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develop the analytical skills to effectively safeguard your organization by enhancing defense mechanisms, and become a proficient threat intelligence analyst to help strategic teams in making informed decisions Key FeaturesBuild the analytics skills and practices you need for analyzing, detecting, and preventing cyber threatsLearn how to perform intrusion analysis using the cyber threat intelligence (CTI) processIntegrate threat intelligence into your current security infrastructure for enhanced protectionBook Description The sophistication of cyber threats, such as ransomware, advanced phishing campaigns, zero-day vulnerability attacks, and advanced persistent threats (APTs), is pushing organizations and individuals to change strategies for reliable system protection. Cyber Threat Intelligence converts threat information into evidence-based intelligence that uncovers adversaries' intents, motives, and capabilities for effective defense against all kinds of threats. This book thoroughly covers the concepts and practices required to develop and drive threat intelligence programs, detailing the tasks involved in each step of the CTI lifecycle. You'll be able to plan a threat intelligence program by understanding and collecting the requirements, setting up the team, and exploring the intelligence frameworks. You'll also learn how and from where to collect intelligence data for your program, considering your organization level. With the help of practical examples, this book will help you get to grips with threat data processing and analysis. And finally, you'll be well-versed with writing tactical, technical, and strategic intelligence reports and sharing them with the community. By the end of this book, you'll have acquired the knowledge and skills required to drive threat intelligence operations from planning to dissemination phases, protect your organization, and help in critical defense decisions. What you will learnUnderstand the CTI lifecycle which makes the foundation of the studyForm a CTI team and position it in the security stackExplore CTI frameworks, platforms, and their use in the programIntegrate CTI in small, medium, and large enterprisesDiscover intelligence data sources and feedsPerform threat modelling and adversary and threat analysisFind out what Indicators of Compromise (IoCs) are and apply the pyramid of pain in threat detectionGet to grips with writing intelligence reports and sharing intelligenceWho this book is for This book is for security professionals, researchers, and individuals who want to gain profound knowledge of cyber threat intelligence and discover techniques to prevent varying types of cyber threats. Basic knowledge of cybersecurity and network fundamentals is required to get the most out of this book.

Secure Data Science

Author : Bhavani Thuraisingham
Publisher : CRC Press
ISBN 13 : 1000557510
Total Pages : 430 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Secure Data Science by : Bhavani Thuraisingham

Download or read book Secure Data Science written by Bhavani Thuraisingham and published by CRC Press. This book was released on 2022-04-27 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Secure data science, which integrates cyber security and data science, is becoming one of the critical areas in both cyber security and data science. This is because the novel data science techniques being developed have applications in solving such cyber security problems as intrusion detection, malware analysis, and insider threat detection. However, the data science techniques being applied not only for cyber security but also for every application area—including healthcare, finance, manufacturing, and marketing—could be attacked by malware. Furthermore, due to the power of data science, it is now possible to infer highly private and sensitive information from public data, which could result in the violation of individual privacy. This is the first such book that provides a comprehensive overview of integrating both cyber security and data science and discusses both theory and practice in secure data science. After an overview of security and privacy for big data services as well as cloud computing, this book describes applications of data science for cyber security applications. It also discusses such applications of data science as malware analysis and insider threat detection. Then this book addresses trends in adversarial machine learning and provides solutions to the attacks on the data science techniques. In particular, it discusses some emerging trends in carrying out trustworthy analytics so that the analytics techniques can be secured against malicious attacks. Then it focuses on the privacy threats due to the collection of massive amounts of data and potential solutions. Following a discussion on the integration of services computing, including cloud-based services for secure data science, it looks at applications of secure data science to information sharing and social media. This book is a useful resource for researchers, software developers, educators, and managers who want to understand both the high level concepts and the technical details on the design and implementation of secure data science-based systems. It can also be used as a reference book for a graduate course in secure data science. Furthermore, this book provides numerous references that would be helpful for the reader to get more details about secure data science.

Machine Learning and Cognitive Science Applications in Cyber Security

Author : Khan, Muhammad Salman
Publisher : IGI Global
ISBN 13 : 1522581014
Total Pages : 321 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Machine Learning and Cognitive Science Applications in Cyber Security by : Khan, Muhammad Salman

Download or read book Machine Learning and Cognitive Science Applications in Cyber Security written by Khan, Muhammad Salman and published by IGI Global. This book was released on 2019-05-15 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past few years, with the evolution of advanced persistent threats and mutation techniques, sensitive and damaging information from a variety of sources have been exposed to possible corruption and hacking. Machine learning, artificial intelligence, predictive analytics, and similar disciplines of cognitive science applications have been found to have significant applications in the domain of cyber security. Machine Learning and Cognitive Science Applications in Cyber Security examines different applications of cognition that can be used to detect threats and analyze data to capture malware. Highlighting such topics as anomaly detection, intelligent platforms, and triangle scheme, this publication is designed for IT specialists, computer engineers, researchers, academicians, and industry professionals interested in the impact of machine learning in cyber security and the methodologies that can help improve the performance and reliability of machine learning applications.

Big Data Analytics in Cybersecurity

Author : Onur Savas
Publisher : CRC Press
ISBN 13 : 1498772161
Total Pages : 336 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Big Data Analytics in Cybersecurity by : Onur Savas

Download or read book Big Data Analytics in Cybersecurity written by Onur Savas and published by CRC Press. This book was released on 2017-09-18 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Tony Thomas
Publisher : Springer Nature
ISBN 13 : 9811517061
Total Pages : 217 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Machine Learning Approaches in Cyber Security Analytics by : Tony Thomas

Download or read book Machine Learning Approaches in Cyber Security Analytics written by Tony Thomas and published by Springer Nature. This book was released on 2019-12-16 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 and Computational Intelligence for Cybersecurity

Author : Mariya Ouaissa
Publisher : Springer Nature
ISBN 13 : 303105752X
Total Pages : 336 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Big Data Analytics and Computational Intelligence for Cybersecurity by : Mariya Ouaissa

Download or read book Big Data Analytics and Computational Intelligence for Cybersecurity written by Mariya Ouaissa and published by Springer Nature. This book was released on 2022-09-01 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

AI in Cybersecurity

Author : Leslie F. Sikos
Publisher : Springer
ISBN 13 : 3319988425
Total Pages : 205 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis AI in Cybersecurity by : Leslie F. Sikos

Download or read book AI in Cybersecurity written by Leslie F. Sikos and published by Springer. This book was released on 2018-09-17 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of state-of-the-art AI approaches to cybersecurity and cyberthreat intelligence, offering strategic defense mechanisms for malware, addressing cybercrime, and assessing vulnerabilities to yield proactive rather than reactive countermeasures. The current variety and scope of cybersecurity threats far exceed the capabilities of even the most skilled security professionals. In addition, analyzing yesterday’s security incidents no longer enables experts to predict and prevent tomorrow’s attacks, which necessitates approaches that go far beyond identifying known threats. Nevertheless, there are promising avenues: complex behavior matching can isolate threats based on the actions taken, while machine learning can help detect anomalies, prevent malware infections, discover signs of illicit activities, and protect assets from hackers. In turn, knowledge representation enables automated reasoning over network data, helping achieve cybersituational awareness. Bringing together contributions by high-caliber experts, this book suggests new research directions in this critical and rapidly growing field.