Author: Nicholas A Heard
Publisher: World Scientific
ISBN: 178634565X
Category : Computers
Languages : en
Pages : 305
Book Description
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.
Data Science For Cyber-security
Author: Nicholas A Heard
Publisher: World Scientific
ISBN: 178634565X
Category : Computers
Languages : en
Pages : 305
Book Description
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.
Publisher: World Scientific
ISBN: 178634565X
Category : Computers
Languages : en
Pages : 305
Book Description
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
Author: Bhavani Thuraisingham
Publisher: CRC Press
ISBN: 1000557510
Category : Computers
Languages : en
Pages : 430
Book Description
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.
Publisher: CRC Press
ISBN: 1000557510
Category : Computers
Languages : en
Pages : 430
Book Description
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.
Malware Data Science
Author: Joshua Saxe
Publisher: No Starch Press
ISBN: 1593278594
Category : Computers
Languages : en
Pages : 274
Book Description
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.
Publisher: No Starch Press
ISBN: 1593278594
Category : Computers
Languages : en
Pages : 274
Book Description
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.
Information Security Science
Author: Carl Young
Publisher: Syngress
ISBN: 0128096462
Category : Business & Economics
Languages : en
Pages : 408
Book Description
Information Security Science: Measuring the Vulnerability to Data Compromises provides the scientific background and analytic techniques to understand and measure the risk associated with information security threats. This is not a traditional IT security book since it includes methods of information compromise that are not typically addressed in textbooks or journals. In particular, it explores the physical nature of information security risk, and in so doing exposes subtle, yet revealing, connections between information security, physical security, information technology, and information theory. This book is also a practical risk management guide, as it explains the fundamental scientific principles that are directly relevant to information security, specifies a structured methodology to evaluate a host of threats and attack vectors, identifies unique metrics that point to root causes of technology risk, and enables estimates of the effectiveness of risk mitigation. This book is the definitive reference for scientists and engineers with no background in security, and is ideal for security analysts and practitioners who lack scientific training. Importantly, it provides security professionals with the tools to prioritize information security controls and thereby develop cost-effective risk management strategies. - Specifies the analytic and scientific methods necessary to estimate the vulnerability to information loss for a spectrum of threats and attack vectors - Represents a unique treatment of the nexus between physical and information security that includes risk analyses of IT device emanations, visible information, audible information, physical information assets, and virtualized IT environments - Identifies metrics that point to the root cause of information technology risk and thereby assist security professionals in developing risk management strategies - Analyzes numerous threat scenarios and specifies countermeasures based on derived quantitative metrics - Provides chapter introductions and end-of-chapter summaries to enhance the reader's experience and facilitate an appreciation for key concepts
Publisher: Syngress
ISBN: 0128096462
Category : Business & Economics
Languages : en
Pages : 408
Book Description
Information Security Science: Measuring the Vulnerability to Data Compromises provides the scientific background and analytic techniques to understand and measure the risk associated with information security threats. This is not a traditional IT security book since it includes methods of information compromise that are not typically addressed in textbooks or journals. In particular, it explores the physical nature of information security risk, and in so doing exposes subtle, yet revealing, connections between information security, physical security, information technology, and information theory. This book is also a practical risk management guide, as it explains the fundamental scientific principles that are directly relevant to information security, specifies a structured methodology to evaluate a host of threats and attack vectors, identifies unique metrics that point to root causes of technology risk, and enables estimates of the effectiveness of risk mitigation. This book is the definitive reference for scientists and engineers with no background in security, and is ideal for security analysts and practitioners who lack scientific training. Importantly, it provides security professionals with the tools to prioritize information security controls and thereby develop cost-effective risk management strategies. - Specifies the analytic and scientific methods necessary to estimate the vulnerability to information loss for a spectrum of threats and attack vectors - Represents a unique treatment of the nexus between physical and information security that includes risk analyses of IT device emanations, visible information, audible information, physical information assets, and virtualized IT environments - Identifies metrics that point to the root cause of information technology risk and thereby assist security professionals in developing risk management strategies - Analyzes numerous threat scenarios and specifies countermeasures based on derived quantitative metrics - Provides chapter introductions and end-of-chapter summaries to enhance the reader's experience and facilitate an appreciation for key concepts
Information Security Analytics
Author: Mark Talabis
Publisher: Syngress
ISBN: 0128005068
Category : Computers
Languages : en
Pages : 183
Book Description
Information Security Analytics gives you insights into the practice of analytics and, more importantly, how you can utilize analytic techniques to identify trends and outliers that may not be possible to identify using traditional security analysis techniques. Information Security Analytics dispels the myth that analytics within the information security domain is limited to just security incident and event management systems and basic network analysis. Analytic techniques can help you mine data and identify patterns and relationships in any form of security data. Using the techniques covered in this book, you will be able to gain security insights into unstructured big data of any type. The authors of Information Security Analytics bring a wealth of analytics experience to demonstrate practical, hands-on techniques through case studies and using freely-available tools that will allow you to find anomalies and outliers by combining disparate data sets. They also teach you everything you need to know about threat simulation techniques and how to use analytics as a powerful decision-making tool to assess security control and process requirements within your organization. Ultimately, you will learn how to use these simulation techniques to help predict and profile potential risks to your organization. - Written by security practitioners, for security practitioners - Real-world case studies and scenarios are provided for each analytics technique - Learn about open-source analytics and statistical packages, tools, and applications - Step-by-step guidance on how to use analytics tools and how they map to the techniques and scenarios provided - Learn how to design and utilize simulations for "what-if" scenarios to simulate security events and processes - Learn how to utilize big data techniques to assist in incident response and intrusion analysis
Publisher: Syngress
ISBN: 0128005068
Category : Computers
Languages : en
Pages : 183
Book Description
Information Security Analytics gives you insights into the practice of analytics and, more importantly, how you can utilize analytic techniques to identify trends and outliers that may not be possible to identify using traditional security analysis techniques. Information Security Analytics dispels the myth that analytics within the information security domain is limited to just security incident and event management systems and basic network analysis. Analytic techniques can help you mine data and identify patterns and relationships in any form of security data. Using the techniques covered in this book, you will be able to gain security insights into unstructured big data of any type. The authors of Information Security Analytics bring a wealth of analytics experience to demonstrate practical, hands-on techniques through case studies and using freely-available tools that will allow you to find anomalies and outliers by combining disparate data sets. They also teach you everything you need to know about threat simulation techniques and how to use analytics as a powerful decision-making tool to assess security control and process requirements within your organization. Ultimately, you will learn how to use these simulation techniques to help predict and profile potential risks to your organization. - Written by security practitioners, for security practitioners - Real-world case studies and scenarios are provided for each analytics technique - Learn about open-source analytics and statistical packages, tools, and applications - Step-by-step guidance on how to use analytics tools and how they map to the techniques and scenarios provided - Learn how to design and utilize simulations for "what-if" scenarios to simulate security events and processes - Learn how to utilize big data techniques to assist in incident response and intrusion analysis
Data Science and Information Security
Author: Hai Jin
Publisher: Springer Nature
ISBN: 9819712807
Category :
Languages : en
Pages : 328
Book Description
Publisher: Springer Nature
ISBN: 9819712807
Category :
Languages : en
Pages : 328
Book Description
Data Smart
Author: John W. Foreman
Publisher: John Wiley & Sons
ISBN: 1118839862
Category : Business & Economics
Languages : en
Pages : 432
Book Description
Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.
Publisher: John Wiley & Sons
ISBN: 1118839862
Category : Business & Economics
Languages : en
Pages : 432
Book Description
Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.
Introduction to Machine Learning with Applications in Information Security
Author: Mark Stamp
Publisher: CRC Press
ISBN: 1000626261
Category : Business & Economics
Languages : en
Pages : 498
Book Description
Introduction to Machine Learning with Applications in Information Security, Second Edition provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications. The book is accessible and doesn’t prove theorems, or dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core classic machine learning topics in depth, including Hidden Markov Models (HMM), Support Vector Machines (SVM), and clustering. Additional machine learning topics include k-Nearest Neighbor (k-NN), boosting, Random Forests, and Linear Discriminant Analysis (LDA). The fundamental deep learning topics of backpropagation, Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLP), and Recurrent Neural Networks (RNN) are covered in depth. A broad range of advanced deep learning architectures are also presented, including Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief Networks (DBN), Bidirectional Encoder Representations from Transformers (BERT), and Word2Vec. Finally, several cutting-edge deep learning topics are discussed, including dropout regularization, attention, explainability, and adversarial attacks. Most of the examples in the book are drawn from the field of information security, with many of the machine learning and deep learning applications focused on malware. The applications presented serve to demystify the topics by illustrating the use of various learning techniques in straightforward scenarios. Some of the exercises in this book require programming, and elementary computing concepts are assumed in a few of the application sections. However, anyone with a modest amount of computing experience should have no trouble with this aspect of the book. Instructor resources, including PowerPoint slides, lecture videos, and other relevant material are provided on an accompanying website: http://www.cs.sjsu.edu/~stamp/ML/.
Publisher: CRC Press
ISBN: 1000626261
Category : Business & Economics
Languages : en
Pages : 498
Book Description
Introduction to Machine Learning with Applications in Information Security, Second Edition provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications. The book is accessible and doesn’t prove theorems, or dwell on mathematical theory. The goal is to present topics at an intuitive level, with just enough detail to clarify the underlying concepts. The book covers core classic machine learning topics in depth, including Hidden Markov Models (HMM), Support Vector Machines (SVM), and clustering. Additional machine learning topics include k-Nearest Neighbor (k-NN), boosting, Random Forests, and Linear Discriminant Analysis (LDA). The fundamental deep learning topics of backpropagation, Convolutional Neural Networks (CNN), Multilayer Perceptrons (MLP), and Recurrent Neural Networks (RNN) are covered in depth. A broad range of advanced deep learning architectures are also presented, including Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), Extreme Learning Machines (ELM), Residual Networks (ResNet), Deep Belief Networks (DBN), Bidirectional Encoder Representations from Transformers (BERT), and Word2Vec. Finally, several cutting-edge deep learning topics are discussed, including dropout regularization, attention, explainability, and adversarial attacks. Most of the examples in the book are drawn from the field of information security, with many of the machine learning and deep learning applications focused on malware. The applications presented serve to demystify the topics by illustrating the use of various learning techniques in straightforward scenarios. Some of the exercises in this book require programming, and elementary computing concepts are assumed in a few of the application sections. However, anyone with a modest amount of computing experience should have no trouble with this aspect of the book. Instructor resources, including PowerPoint slides, lecture videos, and other relevant material are provided on an accompanying website: http://www.cs.sjsu.edu/~stamp/ML/.
Data-Driven Security
Author: Jay Jacobs
Publisher: John Wiley & Sons
ISBN: 1118793722
Category : Computers
Languages : en
Pages : 354
Book Description
Uncover hidden patterns of data and respond with countermeasures Security professionals need all the tools at their disposal to increase their visibility in order to prevent security breaches and attacks. This careful guide explores two of the most powerful data analysis and visualization. You'll soon understand how to harness and wield data, from collection and storage to management and analysis as well as visualization and presentation. Using a hands-on approach with real-world examples, this book shows you how to gather feedback, measure the effectiveness of your security methods, and make better decisions. Everything in this book will have practical application for information security professionals. Helps IT and security professionals understand and use data, so they can thwart attacks and understand and visualize vulnerabilities in their networks Includes more than a dozen real-world examples and hands-on exercises that demonstrate how to analyze security data and intelligence and translate that information into visualizations that make plain how to prevent attacks Covers topics such as how to acquire and prepare security data, use simple statistical methods to detect malware, predict rogue behavior, correlate security events, and more Written by a team of well-known experts in the field of security and data analysis Lock down your networks, prevent hacks, and thwart malware by improving visibility into the environment, all through the power of data and Security Using Data Analysis, Visualization, and Dashboards.
Publisher: John Wiley & Sons
ISBN: 1118793722
Category : Computers
Languages : en
Pages : 354
Book Description
Uncover hidden patterns of data and respond with countermeasures Security professionals need all the tools at their disposal to increase their visibility in order to prevent security breaches and attacks. This careful guide explores two of the most powerful data analysis and visualization. You'll soon understand how to harness and wield data, from collection and storage to management and analysis as well as visualization and presentation. Using a hands-on approach with real-world examples, this book shows you how to gather feedback, measure the effectiveness of your security methods, and make better decisions. Everything in this book will have practical application for information security professionals. Helps IT and security professionals understand and use data, so they can thwart attacks and understand and visualize vulnerabilities in their networks Includes more than a dozen real-world examples and hands-on exercises that demonstrate how to analyze security data and intelligence and translate that information into visualizations that make plain how to prevent attacks Covers topics such as how to acquire and prepare security data, use simple statistical methods to detect malware, predict rogue behavior, correlate security events, and more Written by a team of well-known experts in the field of security and data analysis Lock down your networks, prevent hacks, and thwart malware by improving visibility into the environment, all through the power of data and Security Using Data Analysis, Visualization, and Dashboards.
Introduction to Information Security
Author: Timothy Shimeall
Publisher: Newnes
ISBN: 1597499722
Category : Computers
Languages : en
Pages : 383
Book Description
Most introductory texts provide a technology-based survey of methods and techniques that leaves the reader without a clear understanding of the interrelationships between methods and techniques. By providing a strategy-based introduction, the reader is given a clear understanding of how to provide overlapping defenses for critical information. This understanding provides a basis for engineering and risk-management decisions in the defense of information.Information security is a rapidly growing field, with a projected need for thousands of professionals within the next decade in the government sector alone. It is also a field that has changed in the last decade from a largely theory-based discipline to an experience-based discipline. This shift in the field has left several of the classic texts with a strongly dated feel. - Provides a broad introduction to the methods and techniques in the field of information security - Offers a strategy-based view of these tools and techniques, facilitating selection of overlapping methods for in-depth defense of information - Provides very current view of the emerging standards of practice in information security
Publisher: Newnes
ISBN: 1597499722
Category : Computers
Languages : en
Pages : 383
Book Description
Most introductory texts provide a technology-based survey of methods and techniques that leaves the reader without a clear understanding of the interrelationships between methods and techniques. By providing a strategy-based introduction, the reader is given a clear understanding of how to provide overlapping defenses for critical information. This understanding provides a basis for engineering and risk-management decisions in the defense of information.Information security is a rapidly growing field, with a projected need for thousands of professionals within the next decade in the government sector alone. It is also a field that has changed in the last decade from a largely theory-based discipline to an experience-based discipline. This shift in the field has left several of the classic texts with a strongly dated feel. - Provides a broad introduction to the methods and techniques in the field of information security - Offers a strategy-based view of these tools and techniques, facilitating selection of overlapping methods for in-depth defense of information - Provides very current view of the emerging standards of practice in information security