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Secure Data Science


Secure Data Science
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Data Science For Cyber Security


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.



Secure Data Science


Secure Data Science
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Author : Bhavani Thuraisingham
language : en
Publisher: CRC Press
Release Date : 2022-04-27

Secure Data Science written by Bhavani Thuraisingham and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-27 with Computers categories.


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 Security


Machine Learning And Security
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Author : Clarence Chio
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2018-01-26

Machine Learning And Security written by Clarence Chio and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-26 with Computers categories.


Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions



Malware Data Science


Malware Data Science
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Author : Joshua Saxe
language : en
Publisher: No Starch Press
Release Date : 2018-09-25

Malware Data Science written by Joshua Saxe and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-25 with Computers categories.


Malware Data Science explains how to identify, analyze, and classify large-scale malware using machine learning and data visualization. Security has become a "big data" problem. The growth rate of malware has accelerated to tens of millions of new files per year while our networks generate an ever-larger flood of security-relevant data each day. In order to defend against these advanced attacks, you'll need to know how to think like a data scientist. In Malware Data Science, security data scientist Joshua Saxe introduces machine learning, statistics, social network analysis, and data visualization, and shows you how to apply these methods to malware detection and analysis. You'll learn how to: - Analyze malware using static analysis - Observe malware behavior using dynamic analysis - Identify adversary groups through shared code analysis - Catch 0-day vulnerabilities by building your own machine learning detector - Measure malware detector accuracy - Identify malware campaigns, trends, and relationships through data visualization Whether you're a malware analyst looking to add skills to your existing arsenal, or a data scientist interested in attack detection and threat intelligence, Malware Data Science will help you stay ahead of the curve.



Data Science And Security


Data Science And Security
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Author : Samiksha Shukla
language : en
Publisher: Springer Nature
Release Date : 2021-08-26

Data Science And Security written by Samiksha Shukla and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-26 with Technology & Engineering categories.


This book presents the best-selected papers presented at the International Conference on Data Science, Computation and Security (IDSCS-2021), organized by the Department of Data Science, CHRIST (Deemed to be University), Pune Lavasa Campus, India, during April 16–17, 2021. The proceeding is targeting the current research works in the areas of data science, data security, data analytics, artificial intelligence, machine learning, computer vision, algorithms design, computer networking, data mining, big data, text mining, knowledge representation, soft computing, and cloud computing.



Security Analytics


Security Analytics
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Author : Mehak Khurana
language : en
Publisher: CRC Press
Release Date : 2022-06-24

Security Analytics written by Mehak Khurana and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-24 with Computers categories.


The book gives a comprehensive overview of security issues in cyber physical systems by examining and analyzing the vulnerabilities. It also brings current understanding of common web vulnerabilities and its analysis while maintaining awareness and knowledge of contemporary standards, practices, procedures and methods of Open Web Application Security Project. This book is a medium to funnel creative energy and develop new skills of hacking and analysis of security and expedites the learning of the basics of investigating crimes, including intrusion from the outside and damaging practices from the inside, how criminals apply across devices, networks, and the internet at large and analysis of security data. Features Helps to develop an understanding of how to acquire, prepare, visualize security data. Unfolds the unventured sides of the cyber security analytics and helps spread awareness of the new technological boons. Focuses on the analysis of latest development, challenges, ways for detection and mitigation of attacks, advanced technologies, and methodologies in this area. Designs analytical models to help detect malicious behaviour. The book provides a complete view of data analytics to the readers which include cyber security issues, analysis, threats, vulnerabilities, novel ideas, analysis of latest techniques and technology, mitigation of threats and attacks along with demonstration of practical applications, and is suitable for a wide-ranging audience from graduates to professionals/practitioners and researchers.



Emerging Trends In Information System Security Using Ai Data Science For Next Generation Cyber Analytics


Emerging Trends In Information System Security Using Ai Data Science For Next Generation Cyber Analytics
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Author : Faisal Rehman
language : en
Publisher: Springer Nature
Release Date : 2025-05-19

Emerging Trends In Information System Security Using Ai Data Science For Next Generation Cyber Analytics written by Faisal Rehman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-19 with Computers categories.


This book is a comprehensive exploration into the intersection of cutting-edge technologies and the critical domain of cybersecurity; this book delves deep into the evolving landscape of cyber threats and the imperative for innovative solutions. From establishing the fundamental principles of cyber security to scrutinizing the latest advancements in AI and machine learning, each chapter offers invaluable insights into bolstering defenses against contemporary threats. Readers are guided through a journey that traverses the realms of cyber analytics, threat analysis, and the safeguarding of information systems in an increasingly interconnected world. With chapters dedicated to exploring the role of AI in securing IoT devices, employing supervised and unsupervised learning techniques for threat classification, and harnessing the power of recurrent neural networks for time series analysis, this book presents a holistic view of the evolving cybersecurity landscape. Moreover, it highlights the importance of next-generation defense mechanisms, such as generative adversarial networks (GANs) and federated learning techniques, in combating sophisticated cyber threats while preserving privacy. This book is a comprehensive guide to integrating AI and data science into modern cybersecurity strategies. It covers topics like anomaly detection, behaviour analysis, and threat intelligence, and advocates for proactive risk mitigation using AI and data science. The book provides practical applications, ethical considerations, and customizable frameworks for implementing next-gen cyber defense strategies. It bridges theory with practice, offering real-world case studies, innovative methodologies, and continuous learning resources to equip readers with the knowledge and tools to mitigate cyber threats.



Data Analytics And Decision Support For Cybersecurity


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.



Practical Data Privacy


Practical Data Privacy
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Author : Katharine Jarmul
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-04-19

Practical Data Privacy written by Katharine Jarmul and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-19 with Computers categories.


Between major privacy regulations like the GDPR and CCPA and expensive and notorious data breaches, there has never been so much pressure to ensure data privacy. Unfortunately, integrating privacy into data systems is still complicated. This essential guide will give you a fundamental understanding of modern privacy building blocks, like differential privacy, federated learning, and encrypted computation. Based on hard-won lessons, this book provides solid advice and best practices for integrating breakthrough privacy-enhancing technologies into production systems. Practical Data Privacy answers important questions such as: What do privacy regulations like GDPR and CCPA mean for my data workflows and data science use cases? What does "anonymized data" really mean? How do I actually anonymize data? How does federated learning and analysis work? Homomorphic encryption sounds great, but is it ready for use? How do I compare and choose the best privacy-preserving technologies and methods? Are there open-source libraries that can help? How do I ensure that my data science projects are secure by default and private by design? How do I work with governance and infosec teams to implement internal policies appropriately?



Cybersecurity Data Science


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.