Data Science For Cyber Security

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Data Science For Cyber-security

Adams Niall M,Heard Nicholas A,Rubin-delanchy Patrick
Data Science For Cyber security Book PDF

Author : Adams Niall M,Heard Nicholas A,Rubin-delanchy Patrick
Publisher : World Scientific
Page : 304 pages
File Size : 41,8 Mb
Release : 2018-09-25
Category : Computers
ISBN : 9781786345653

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Data Science For Cyber-security by Adams Niall M,Heard Nicholas A,Rubin-delanchy Patrick Pdf

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.

Cybersecurity Data Science

Scott Mongeau,Andrzej Hajdasinski
Cybersecurity Data Science Book PDF

Author : Scott Mongeau,Andrzej Hajdasinski
Publisher : Springer Nature
Page : 410 pages
File Size : 50,5 Mb
Release : 2021-10-01
Category : Computers
ISBN : 9783030748968

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Cybersecurity Data Science by Scott Mongeau,Andrzej Hajdasinski Pdf

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.

Malware Data Science

Joshua Saxe,Hillary Sanders
Malware Data Science Book PDF

Author : Joshua Saxe,Hillary Sanders
Publisher : No Starch Press
Page : 274 pages
File Size : 41,7 Mb
Release : 2018-09-25
Category : Computers
ISBN : 9781593278595

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Malware Data Science by Joshua Saxe,Hillary Sanders Pdf

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.

Secure Data Science

Bhavani Thuraisingham,Murat Kantarcioglu,Latifur Khan
Secure Data Science Book PDF

Author : Bhavani Thuraisingham,Murat Kantarcioglu,Latifur Khan
Publisher : CRC Press
Page : 430 pages
File Size : 50,9 Mb
Release : 2022-04-27
Category : Computers
ISBN : 9781000557510

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Secure Data Science by Bhavani Thuraisingham,Murat Kantarcioglu,Latifur Khan Pdf

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 Approaches in Cyber Security Analytics

Tony Thomas,Athira P. Vijayaraghavan,Sabu Emmanuel
Machine Learning Approaches in Cyber Security Analytics Book PDF

Author : Tony Thomas,Athira P. Vijayaraghavan,Sabu Emmanuel
Publisher : Springer Nature
Page : 217 pages
File Size : 48,6 Mb
Release : 2019-12-16
Category : Computers
ISBN : 9789811517068

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Machine Learning Approaches in Cyber Security Analytics by Tony Thomas,Athira P. Vijayaraghavan,Sabu Emmanuel Pdf

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.

Cybersecurity Analytics

Rakesh M. Verma,David J. Marchette
Cybersecurity Analytics Book PDF

Author : Rakesh M. Verma,David J. Marchette
Publisher : CRC Press
Page : 357 pages
File Size : 47,6 Mb
Release : 2019-11-27
Category : Mathematics
ISBN : 9781000727654

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Cybersecurity Analytics by Rakesh M. Verma,David J. Marchette Pdf

Cybersecurity Analytics is for the cybersecurity student and professional who wants to learn data science techniques critical for tackling cybersecurity challenges, and for the data science student and professional who wants to learn about cybersecurity adaptations. Trying to build a malware detector, a phishing email detector, or just interested in finding patterns in your datasets? This book can let you do it on your own. Numerous examples and datasets links are included so that the reader can "learn by doing." Anyone with a basic college-level calculus course and some probability knowledge can easily understand most of the material. The book includes chapters containing: unsupervised learning, semi-supervised learning, supervised learning, text mining, natural language processing, and more. It also includes background on security, statistics, and linear algebra. The website for the book contains a listing of datasets, updates, and other resources for serious practitioners.

Data Analysis for Network Cyber-Security

Niall Adams,Nicholas Heard
Data Analysis for Network Cyber Security Book PDF

Author : Niall Adams,Nicholas Heard
Publisher : World Scientific
Page : 200 pages
File Size : 54,8 Mb
Release : 2014-02-28
Category : Computers
ISBN : 9781783263769

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Data Analysis for Network Cyber-Security by Niall Adams,Nicholas Heard Pdf

There is increasing pressure to protect computer networks against unauthorized intrusion, and some work in this area is concerned with engineering systems that are robust to attack. However, no system can be made invulnerable. Data Analysis for Network Cyber-Security focuses on monitoring and analyzing network traffic data, with the intention of preventing, or quickly identifying, malicious activity. Such work involves the intersection of statistics, data mining and computer science. Fundamentally, network traffic is relational, embodying a link between devices. As such, graph analysis approaches are a natural candidate. However, such methods do not scale well to the demands of real problems, and the critical aspect of the timing of communications events is not accounted for in these approaches. This book gathers papers from leading researchers to provide both background to the problems and a description of cutting-edge methodology. The contributors are from diverse institutions and areas of expertise and were brought together at a workshop held at the University of Bristol in March 2013 to address the issues of network cyber security. The workshop was supported by the Heilbronn Institute for Mathematical Research. Contents:Inference for Graphs and Networks: Adapting Classical Tools to Modern Data (Benjamin P Olding and Patrick J Wolfe)Rapid Detection of Attacks in Computer Networks by Quickest Changepoint Detection Methods (Alexander G Tartakovsky)Statistical Detection of Intruders Within Computer Networks Using Scan Statistics (Joshua Neil, Curtis Storlie, Curtis Hash and Alex Brugh)Characterizing Dynamic Group Behavior in Social Networks for Cybernetics (Sumeet Dua and Pradeep Chowriappa)Several Approaches for Detecting Anomalies in Network Traffic Data (Céline Lévy-Leduc)Monitoring a Device in a Communication Network (Nicholas A Heard and Melissa Turcotte) Readership: Researchers and graduate students in the fields of network traffic data analysis and network cyber security. Key Features:This book is unique in being a treatise on the statistical analysis of network traffic dataThe contributors are leading researches in the field and will give authoritative descriptions of cutting edge methodologyThe book features material from diverse areas, and as such forms a unified view of network cyber securityKeywords:Network Data Analysis;Cyber Security;Change Detection;Anomaly Detection

Data Mining and Machine Learning in Cybersecurity

Sumeet Dua,Xian Du
Data Mining and Machine Learning in Cybersecurity Book PDF

Author : Sumeet Dua,Xian Du
Publisher : CRC Press
Page : 256 pages
File Size : 41,5 Mb
Release : 2016-04-19
Category : Computers
ISBN : 9781439839430

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Data Mining and Machine Learning in Cybersecurity by Sumeet Dua,Xian Du Pdf

With the rapid advancement of information discovery techniques, machine learning and data mining continue to play a significant role in cybersecurity. Although several conferences, workshops, and journals focus on the fragmented research topics in this area, there has been no single interdisciplinary resource on past and current works and possible

Machine Learning and Security

Clarence Chio,David Freeman
Machine Learning and Security Book PDF

Author : Clarence Chio,David Freeman
Publisher : "O'Reilly Media, Inc."
Page : 386 pages
File Size : 40,5 Mb
Release : 2018-01-26
Category : Computers
ISBN : 9781491979853

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Machine Learning and Security by Clarence Chio,David Freeman Pdf

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

Deep Learning Applications for Cyber Security

Mamoun Alazab,MingJian Tang
Deep Learning Applications for Cyber Security Book PDF

Author : Mamoun Alazab,MingJian Tang
Publisher : Springer
Page : 246 pages
File Size : 43,7 Mb
Release : 2019-08-14
Category : Computers
ISBN : 9783030130572

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Deep Learning Applications for Cyber Security by Mamoun Alazab,MingJian Tang Pdf

Cybercrime remains a growing challenge in terms of security and privacy practices. Working together, deep learning and cyber security experts have recently made significant advances in the fields of intrusion detection, malicious code analysis and forensic identification. This book addresses questions of how deep learning methods can be used to advance cyber security objectives, including detection, modeling, monitoring and analysis of as well as defense against various threats to sensitive data and security systems. Filling an important gap between deep learning and cyber security communities, it discusses topics covering a wide range of modern and practical deep learning techniques, frameworks and development tools to enable readers to engage with the cutting-edge research across various aspects of cyber security. The book focuses on mature and proven techniques, and provides ample examples to help readers grasp the key points.

Information Fusion for Cyber-Security Analytics

Izzat M Alsmadi,George Karabatis,Ahmed Aleroud
Information Fusion for Cyber Security Analytics Book PDF

Author : Izzat M Alsmadi,George Karabatis,Ahmed Aleroud
Publisher : Springer
Page : 379 pages
File Size : 43,9 Mb
Release : 2016-10-21
Category : Technology & Engineering
ISBN : 9783319442570

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Information Fusion for Cyber-Security Analytics by Izzat M Alsmadi,George Karabatis,Ahmed Aleroud Pdf

This book highlights several gaps that have not been addressed in existing cyber security research. It first discusses the recent attack prediction techniques that utilize one or more aspects of information to create attack prediction models. The second part is dedicated to new trends on information fusion and their applicability to cyber security; in particular, graph data analytics for cyber security, unwanted traffic detection and control based on trust management software defined networks, security in wireless sensor networks & their applications, and emerging trends in security system design using the concept of social behavioral biometric. The book guides the design of new commercialized tools that can be introduced to improve the accuracy of existing attack prediction models. Furthermore, the book advances the use of Knowledge-based Intrusion Detection Systems (IDS) to complement existing IDS technologies. It is aimed towards cyber security researchers.

Hands-On Machine Learning for Cybersecurity

Soma Halder,Sinan Ozdemir
Hands On Machine Learning for Cybersecurity Book PDF

Author : Soma Halder,Sinan Ozdemir
Publisher : Packt Publishing Ltd
Page : 306 pages
File Size : 51,8 Mb
Release : 2018-12-31
Category : Computers
ISBN : 9781788990967

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Hands-On Machine Learning for Cybersecurity by Soma Halder,Sinan Ozdemir Pdf

Get into the world of smart data security using machine learning algorithms and Python libraries Key FeaturesLearn machine learning algorithms and cybersecurity fundamentalsAutomate your daily workflow by applying use cases to many facets of securityImplement smart machine learning solutions to detect various cybersecurity problemsBook Description Cyber threats today are one of the costliest losses that an organization can face. In this book, we use the most efficient tool to solve the big problems that exist in the cybersecurity domain. The book begins by giving you the basics of ML in cybersecurity using Python and its libraries. You will explore various ML domains (such as time series analysis and ensemble modeling) to get your foundations right. You will implement various examples such as building system to identify malicious URLs, and building a program to detect fraudulent emails and spam. Later, you will learn how to make effective use of K-means algorithm to develop a solution to detect and alert you to any malicious activity in the network. Also learn how to implement biometrics and fingerprint to validate whether the user is a legitimate user or not. Finally, you will see how we change the game with TensorFlow and learn how deep learning is effective for creating models and training systems What you will learnUse machine learning algorithms with complex datasets to implement cybersecurity conceptsImplement machine learning algorithms such as clustering, k-means, and Naive Bayes to solve real-world problemsLearn to speed up a system using Python libraries with NumPy, Scikit-learn, and CUDAUnderstand how to combat malware, detect spam, and fight financial fraud to mitigate cyber crimesUse TensorFlow in the cybersecurity domain and implement real-world examplesLearn how machine learning and Python can be used in complex cyber issuesWho this book is for This book is for the data scientists, machine learning developers, security researchers, and anyone keen to apply machine learning to up-skill computer security. Having some working knowledge of Python and being familiar with the basics of machine learning and cybersecurity fundamentals will help to get the most out of the book

Secure Data Science

Bhavani Thuraisingham,Murat Kantarcioglu,Latifur Khan
Secure Data Science Book PDF

Author : Bhavani Thuraisingham,Murat Kantarcioglu,Latifur Khan
Publisher : CRC Press
Page : 457 pages
File Size : 54,8 Mb
Release : 2022-04-27
Category : Computers
ISBN : 9781000557503

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Secure Data Science by Bhavani Thuraisingham,Murat Kantarcioglu,Latifur Khan Pdf

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.

Data Analytics and Decision Support for Cybersecurity

Iván Palomares Carrascosa,Harsha Kumara Kalutarage,Yan Huang
Data Analytics and Decision Support for Cybersecurity Book PDF

Author : Iván Palomares Carrascosa,Harsha Kumara Kalutarage,Yan Huang
Publisher : Springer
Page : 270 pages
File Size : 46,6 Mb
Release : 2017-08-01
Category : Computers
ISBN : 9783319594392

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Data Analytics and Decision Support for Cybersecurity by Iván Palomares Carrascosa,Harsha Kumara Kalutarage,Yan Huang Pdf

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.

Machine Learning for Computer and Cyber Security

Brij B. Gupta,Quan Z. Sheng
Machine Learning for Computer and Cyber Security Book PDF

Author : Brij B. Gupta,Quan Z. Sheng
Publisher : CRC Press
Page : 333 pages
File Size : 42,8 Mb
Release : 2019-02-05
Category : Computers
ISBN : 9780429995712

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Machine Learning for Computer and Cyber Security by Brij B. Gupta,Quan Z. Sheng Pdf

While Computer Security is a broader term which incorporates technologies, protocols, standards and policies to ensure the security of the computing systems including the computer hardware, software and the information stored in it, Cyber Security is a specific, growing field to protect computer networks (offline and online) from unauthorized access, botnets, phishing scams, etc. Machine learning is a branch of Computer Science which enables computing machines to adopt new behaviors on the basis of observable and verifiable data and information. It can be applied to ensure the security of the computers and the information by detecting anomalies using data mining and other such techniques. This book will be an invaluable resource to understand the importance of machine learning and data mining in establishing computer and cyber security. It emphasizes important security aspects associated with computer and cyber security along with the analysis of machine learning and data mining based solutions. The book also highlights the future research domains in which these solutions can be applied. Furthermore, it caters to the needs of IT professionals, researchers, faculty members, scientists, graduate students, research scholars and software developers who seek to carry out research and develop combating solutions in the area of cyber security using machine learning based approaches. It is an extensive source of information for the readers belonging to the field of Computer Science and Engineering, and Cyber Security professionals. Key Features: This book contains examples and illustrations to demonstrate the principles, algorithms, challenges and applications of machine learning and data mining for computer and cyber security. It showcases important security aspects and current trends in the field. It provides an insight of the future research directions in the field. Contents of this book help to prepare the students for exercising better defense in terms of understanding the motivation of the attackers and how to deal with and mitigate the situation using machine learning based approaches in better manner.