Data Science In Cybersecurity And Cyberthreat Intelligence

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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
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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.
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.
Cybersecurity Data Science
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Author : Scott Mongeau
language : en
Publisher: Springer Nature
Release Date : 2021-10-01
Cybersecurity Data Science written by Scott Mongeau and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-01 with Computers categories.
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.
Data Science For Cyber Security
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Author : Nicholas A Heard
language : en
Publisher: World Scientific
Release Date : 2018-09-26
Data Science For Cyber Security written by Nicholas A Heard and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-26 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.
Ai In Cybersecurity
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Author : Leslie F. Sikos
language : en
Publisher: Springer
Release Date : 2018-09-27
Ai In Cybersecurity written by Leslie F. Sikos and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-27 with Technology & Engineering categories.
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.
Cyber Threat Intelligence
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Author : Aaron Roberts
language : en
Publisher: Apress
Release Date : 2021-08-10
Cyber Threat Intelligence written by Aaron Roberts and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-10 with Computers categories.
Understand the process of setting up a successful cyber threat intelligence (CTI) practice within an established security team. This book shows you how threat information that has been collected, evaluated, and analyzed is a critical component in protecting your organization’s resources. Adopting an intelligence-led approach enables your organization to nimbly react to situations as they develop. Security controls and responses can then be applied as soon as they become available, enabling prevention rather than response. There are a lot of competing approaches and ways of working, but this book cuts through the confusion. Author Aaron Roberts introduces the best practices and methods for using CTI successfully. This book will help not only senior security professionals, but also those looking to break into the industry. You will learn the theories and mindset needed to be successful in CTI. This book covers the cybersecurity wild west, the merits and limitations of structured intelligence data, and how using structured intelligence data can, and should, be the standard practice for any intelligence team. You will understand your organizations’ risks, based on the industry and the adversaries you are most likely to face, the importance of open-source intelligence (OSINT) to any CTI practice, and discover the gaps that exist with your existing commercial solutions and where to plug those gaps, and much more. What You Will Learn Know the wide range of cybersecurity products and the risks and pitfalls aligned with blindly working with a vendor Understand critical intelligence concepts such as the intelligence cycle, setting intelligence requirements, the diamond model, and how to apply intelligence to existing security information Understand structured intelligence (STIX) and why it’s important, and aligning STIX to ATT&CK and how structured intelligence helps improve final intelligence reporting Know how to approach CTI, depending on your budget Prioritize areas when it comes to funding and the best approaches to incident response, requests for information, or ad hoc reporting Critically evaluate services received from your existing vendors, including what they do well, what they don’t do well (or at all), how you can improve on this, the things you should consider moving in-house rather than outsourcing, and the benefits of finding and maintaining relationships with excellent vendors Who This Book Is For Senior security leaders in charge of cybersecurity teams who are considering starting a threat intelligence team, those considering a career change into cyber threat intelligence (CTI) who want a better understanding of the main philosophies and ways of working in the industry, and security professionals with no prior intelligence experience but have technical proficiency in other areas (e.g., programming, security architecture, or engineering)
Threat Forecasting
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Author : John Pirc
language : en
Publisher: Syngress
Release Date : 2016-05-17
Threat Forecasting written by John Pirc and has been published by Syngress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-17 with Computers categories.
Drawing upon years of practical experience and using numerous examples and illustrative case studies, Threat Forecasting: Leveraging Big Data for Predictive Analysis discusses important topics, including the danger of using historic data as the basis for predicting future breaches, how to use security intelligence as a tool to develop threat forecasting techniques, and how to use threat data visualization techniques and threat simulation tools. Readers will gain valuable security insights into unstructured big data, along with tactics on how to use the data to their advantage to reduce risk. - Presents case studies and actual data to demonstrate threat data visualization techniques and threat simulation tools - Explores the usage of kill chain modelling to inform actionable security intelligence - Demonstrates a methodology that can be used to create a full threat forecast analysis for enterprise networks of any size
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
Cybersecurity And Data Science Innovations For Sustainable Development Of Heicc
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Author : Thangavel Murugan
language : en
Publisher: CRC Press
Release Date : 2025-01-30
Cybersecurity And Data Science Innovations For Sustainable Development Of Heicc written by Thangavel Murugan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-30 with Computers categories.
Cybersecurity and Data Science Innovations for Sustainable Development of HEICC: Healthcare, Education, Industry, Cities, and Communities brings together a collection of chapters that explore the intersection of cybersecurity, data science, and sustainable development across key sectors: healthcare, education, industry, cities, and communities. It delves into cybersecurity advancements and examines how innovations in cybersecurity are shaping the landscape of healthcare, education, industry, and urban environments. Data science advancements take center stage, showcasing the transformative power of data analytics in improving outcomes across HEICC sectors. Whether it’s optimizing resource allocation in healthcare, protecting patient privacy, personalizing learning experiences in education, enhancing efficiency in industry, or fostering sustainable development in cities and communities, data science offers unprecedented opportunities for innovation and progress. Key points: Healthcare system security and privacy, protecting patient data, and enabling development of novel healthcare solutions Securing educational data, improving online learning security, and harnessing data analytics for tailored education approaches Manufacturing, finance, and transportation. Diving into critical infrastructure security, detecting and mitigating cyber threats, and using data‐driven insights for better industrial operations Helping cities and communities develop sustainably, smart city security challenges, data privacy in urban environments, data analytics for urban planning, and community cybersecurity awareness This book serves as a comprehensive guide for researchers, practitioners, policymakers, and stakeholders navigating the complex landscape of cybersecurity and data science in the pursuit of sustainable development across HEICC domains.