Data Science In Cybersecurity And Cyberthreat Intelligence


Data Science In Cybersecurity And Cyberthreat Intelligence
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Data Science In Cybersecurity And Cyberthreat Intelligence


Data Science In Cybersecurity And Cyberthreat Intelligence
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Author : Leslie F. Sikos
language : en
Publisher: Springer Nature
Release Date : 2020-02-05

Data Science In Cybersecurity And Cyberthreat Intelligence written by Leslie F. Sikos and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-05 with Computers categories.


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


Data Science In Cybersecurity And Cyberthreat Intelligence
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Author : Leslie F. Sikos
language : en
Publisher:
Release Date : 2020

Data Science In Cybersecurity And Cyberthreat Intelligence written by Leslie F. Sikos and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Artificial intelligence categories.


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.



Big Data Analytics And Intelligent Systems For Cyber Threat Intelligence


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



Applying Artificial Intelligence In Cybersecurity Analytics And Cyber Threat Detection


Applying Artificial Intelligence In Cybersecurity Analytics And Cyber Threat Detection
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Author : Shilpa Mahajan
language : en
Publisher: John Wiley & Sons
Release Date : 2024-03-22

Applying Artificial Intelligence In Cybersecurity Analytics And Cyber Threat Detection written by Shilpa Mahajan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-22 with Computers categories.


APPLYING ARTIFICIAL INTELLIGENCE IN CYBERSECURITY ANALYTICS AND CYBER THREAT DETECTION 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 Cybersecurity 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 Cybersecurity 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 Cybersecurity 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.



Data Science For Cyber Security


Data Science For Cyber Security
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Author : Adams Niall M
language : en
Publisher: World Scientific
Release Date : 2018-09-25

Data Science For Cyber Security written by Adams Niall M and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-25 with Computers categories.


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.



Cyber Threat Intelligence


Cyber Threat Intelligence
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Author : Ali Dehghantanha
language : en
Publisher: Springer
Release Date : 2018-04-27

Cyber Threat Intelligence written by Ali Dehghantanha and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-27 with Computers categories.


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.



Machine Intelligence And Big Data Analytics For Cybersecurity Applications


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.



Mastering Cyber Intelligence


Mastering Cyber Intelligence
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Author : Jean Nestor M. Dahj
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-04-29

Mastering Cyber Intelligence written by Jean Nestor M. Dahj and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-29 with Computers categories.


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.



Handbook Of Big Data Analytics And Forensics


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 Threat Intelligence


Cyber Threat Intelligence
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Author : Ali Dehghantanha
language : en
Publisher:
Release Date : 2018

Cyber Threat Intelligence written by Ali Dehghantanha and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Computer security categories.


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.