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Data Analysis for Network Cyber-Security

Data Analysis for Network Cyber-Security PDF Author: Niall Adams
Publisher: World Scientific
ISBN: 1783263768
Category : Computers
Languages : en
Pages : 200

Book Description
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 Analysis for Network Cyber-Security

Data Analysis for Network Cyber-Security PDF Author: Niall Adams
Publisher: World Scientific
ISBN: 1783263768
Category : Computers
Languages : en
Pages : 200

Book Description
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

Big Data Analytics in Cybersecurity

Big Data Analytics in Cybersecurity PDF Author: Onur Savas
Publisher: CRC Press
ISBN: 1351650416
Category : Business & Economics
Languages : en
Pages : 452

Book Description
Big data is presenting challenges to cybersecurity. For an example, the Internet of Things (IoT) will reportedly soon generate a staggering 400 zettabytes (ZB) of data a year. Self-driving cars are predicted to churn out 4000 GB of data per hour of driving. Big data analytics, as an emerging analytical technology, offers the capability to collect, store, process, and visualize these vast amounts of data. Big Data Analytics in Cybersecurity examines security challenges surrounding big data and provides actionable insights that can be used to improve the current practices of network operators and administrators. Applying big data analytics in cybersecurity is critical. By exploiting data from the networks and computers, analysts can discover useful network information from data. Decision makers can make more informative decisions by using this analysis, including what actions need to be performed, and improvement recommendations to policies, guidelines, procedures, tools, and other aspects of the network processes. Bringing together experts from academia, government laboratories, and industry, the book provides insight to both new and more experienced security professionals, as well as data analytics professionals who have varying levels of cybersecurity expertise. It covers a wide range of topics in cybersecurity, which include: Network forensics Threat analysis Vulnerability assessment Visualization Cyber training. In addition, emerging security domains such as the IoT, cloud computing, fog computing, mobile computing, and cyber-social networks are examined. The book first focuses on how big data analytics can be used in different aspects of cybersecurity including network forensics, root-cause analysis, and security training. Next it discusses big data challenges and solutions in such emerging cybersecurity domains as fog computing, IoT, and mobile app security. The book concludes by presenting the tools and datasets for future cybersecurity research.

Network Security Through Data Analysis

Network Security Through Data Analysis PDF Author: Michael Collins
Publisher: "O'Reilly Media, Inc."
ISBN: 149196281X
Category : Computers
Languages : en
Pages : 427

Book Description
Traditional intrusion detection and logfile analysis are no longer enough to protect today’s complex networks. In the updated second edition of this practical guide, security researcher Michael Collins shows InfoSec personnel the latest techniques and tools for collecting and analyzing network traffic datasets. You’ll understand how your network is used, and what actions are necessary to harden and defend the systems within it. In three sections, this book examines the process of collecting and organizing data, various tools for analysis, and several different analytic scenarios and techniques. New chapters focus on active monitoring and traffic manipulation, insider threat detection, data mining, regression and machine learning, and other topics. You’ll learn how to: Use sensors to collect network, service, host, and active domain data Work with the SiLK toolset, Python, and other tools and techniques for manipulating data you collect Detect unusual phenomena through exploratory data analysis (EDA), using visualization and mathematical techniques Analyze text data, traffic behavior, and communications mistakes Identify significant structures in your network with graph analysis Examine insider threat data and acquire threat intelligence Map your network and identify significant hosts within it Work with operations to develop defenses and analysis techniques

Information Fusion for Cyber-Security Analytics

Information Fusion for Cyber-Security Analytics PDF Author: Izzat M Alsmadi
Publisher: Springer
ISBN: 3319442570
Category : Technology & Engineering
Languages : en
Pages : 379

Book Description
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.

Network Security Through Data Analysis

Network Security Through Data Analysis PDF Author: Michael S Collins
Publisher: "O'Reilly Media, Inc."
ISBN: 1449357865
Category : Computers
Languages : en
Pages : 570

Book Description
Traditional intrusion detection and logfile analysis are no longer enough to protect today’s complex networks. In this practical guide, security researcher Michael Collins shows you several techniques and tools for collecting and analyzing network traffic datasets. You’ll understand how your network is used, and what actions are necessary to protect and improve it. Divided into three sections, this book examines the process of collecting and organizing data, various tools for analysis, and several different analytic scenarios and techniques. It’s ideal for network administrators and operational security analysts familiar with scripting. Explore network, host, and service sensors for capturing security data Store data traffic with relational databases, graph databases, Redis, and Hadoop Use SiLK, the R language, and other tools for analysis and visualization Detect unusual phenomena through Exploratory Data Analysis (EDA) Identify significant structures in networks with graph analysis Determine the traffic that’s crossing service ports in a network Examine traffic volume and behavior to spot DDoS and database raids Get a step-by-step process for network mapping and inventory

Dynamic Networks and Cyber-Security

Dynamic Networks and Cyber-Security PDF Author: Niall Adams
Publisher: World Scientific
ISBN: 1786340763
Category :
Languages : en
Pages : 224

Book Description
As an under-studied area of academic research, the analysis of computer network traffic data is still in its infancy. However, the challenge of detecting and mitigating malicious or unauthorised behaviour through the lens of such data is becoming an increasingly prominent issue. This collection of papers by leading researchers and practitioners synthesises cutting-edge work in the analysis of dynamic networks and statistical aspects of cyber security. The book is structured in such a way as to keep security application at the forefront of discussions. It offers readers easy access into the area of data analysis for complex cyber-security applications, with a particular focus on temporal and network aspects. Chapters can be read as standalone sections and provide rich reviews of the latest research within the field of cyber-security. Academic readers will benefit from state-of-the-art descriptions of new methodologies and their extension to real practical problems while industry professionals will appreciate access to more advanced methodology than ever before. Contents:Network Attacks and the Data They Affect (M Morgan, J Sexton, J Neil, A Ricciardi & J Theimer)Cyber-Security Data Sources for Dynamic Network Research (A D Kent)Modelling User Behaviour in a Network Using Computer Event Logs (M J M Turcotte, N A Heard & A D Kent)Network Services as Risk Factors: A Genetic Epidemiology Approach to Cyber-Security (S Gil)Community Detection and Role Identification in Directed Networks: Understanding the Twitter Network of the Care.Data Debate (B Amor, S Vuik, R Callahan, A Darzi, S N Yaliraki & M Barahona)Anomaly Detection for Cyber Security Applications (P Rubin-Delanchy, D J Lawson & N A Heard)Exponential Random Graph Modelling of Static and Dynamic Social Networks (A Caimo)Hierarchical Dynamic Walks (A V Mantzaris, P Grindrod & D J Higham)Temporal Reachability in Dynamic Networks (A Hagberg, N Lemons & S Misra) Readership: Researchers and practitioners in dynamic network analysis and cyber-security. Key Features:Detailed descriptions of the behaviour of attackersDiscussions of new public domain data sources, including data quality issuesA collection of papers introducing novel methodology for cyber-data analysis

Big Data Analytics in Cybersecurity

Big Data Analytics in Cybersecurity PDF Author: Onur Savas
Publisher: CRC Press
ISBN: 1498772161
Category : Business & Economics
Languages : en
Pages : 336

Book Description
Big data is presenting challenges to cybersecurity. For an example, the Internet of Things (IoT) will reportedly soon generate a staggering 400 zettabytes (ZB) of data a year. Self-driving cars are predicted to churn out 4000 GB of data per hour of driving. Big data analytics, as an emerging analytical technology, offers the capability to collect, store, process, and visualize these vast amounts of data. Big Data Analytics in Cybersecurity examines security challenges surrounding big data and provides actionable insights that can be used to improve the current practices of network operators and administrators. Applying big data analytics in cybersecurity is critical. By exploiting data from the networks and computers, analysts can discover useful network information from data. Decision makers can make more informative decisions by using this analysis, including what actions need to be performed, and improvement recommendations to policies, guidelines, procedures, tools, and other aspects of the network processes. Bringing together experts from academia, government laboratories, and industry, the book provides insight to both new and more experienced security professionals, as well as data analytics professionals who have varying levels of cybersecurity expertise. It covers a wide range of topics in cybersecurity, which include: Network forensics Threat analysis Vulnerability assessment Visualization Cyber training. In addition, emerging security domains such as the IoT, cloud computing, fog computing, mobile computing, and cyber-social networks are examined. The book first focuses on how big data analytics can be used in different aspects of cybersecurity including network forensics, root-cause analysis, and security training. Next it discusses big data challenges and solutions in such emerging cybersecurity domains as fog computing, IoT, and mobile app security. The book concludes by presenting the tools and datasets for future cybersecurity research.

Data Science For Cyber-security

Data Science For Cyber-security PDF Author: Adams Niall M
Publisher: World Scientific
ISBN: 178634565X
Category : Computers
Languages : en
Pages : 304

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.

Security Analytics

Security Analytics PDF Author: Mehak Khurana
Publisher: CRC Press
ISBN: 1000597563
Category : Computers
Languages : en
Pages : 286

Book Description
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.

Cyber Security Intelligence and Analytics

Cyber Security Intelligence and Analytics PDF Author: Zheng Xu
Publisher: Springer
ISBN: 3030152359
Category : Technology & Engineering
Languages : en
Pages : 1453

Book Description
This book presents the outcomes of the 2019 International Conference on Cyber Security Intelligence and Analytics (CSIA2019), an international conference dedicated to promoting novel theoretical and applied research advances in the interdisciplinary field of cyber security, particularly focusing on threat intelligence, analytics, and countering cyber crime. The conference provides a forum for presenting and discussing innovative ideas, cutting-edge research findings, and novel techniques, methods and applications on all aspects of Cyber Security Intelligence and Analytics.