Handbook of Big Data Analytics and Forensics

This handbook discusses challenges and limitations in existing solutions, and presents state-of-the-art advances from both academia and industry, in big data analytics and digital forensics.

Author: Kim-Kwang Raymond Choo

Publisher: Springer

ISBN: 3030747522

Category: Computers

Page: 287

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This handbook discusses challenges and limitations in existing solutions, and presents state-of-the-art advances from both academia and industry, in big data analytics and digital forensics. The second chapter comprehensively reviews IoT security, privacy, and forensics literature, focusing on IoT and unmanned aerial vehicles (UAVs). The authors propose a deep learning-based approach to process cloud’s log data and mitigate enumeration attacks in the third chapter. The fourth chapter proposes a robust fuzzy learning model to protect IT-based infrastructure against advanced persistent threat (APT) campaigns. Advanced and fair clustering approach for industrial data, which is capable of training with huge volume of data in a close to linear time is introduced in the fifth chapter, as well as offering an adaptive deep learning model to detect cyberattacks targeting cyber physical systems (CPS) covered in the sixth chapter. The authors evaluate the performance of unsupervised machine learning for detecting cyberattacks against industrial control systems (ICS) in chapter 7, and the next chapter presents a robust fuzzy Bayesian approach for ICS’s cyber threat hunting. This handbook also evaluates the performance of supervised machine learning methods in identifying cyberattacks against CPS. The performance of a scalable clustering algorithm for CPS’s cyber threat hunting and the usefulness of machine learning algorithms for MacOS malware detection are respectively evaluated. This handbook continues with evaluating the performance of various machine learning techniques to detect the Internet of Things malware. The authors demonstrate how MacOSX cyberattacks can be detected using state-of-the-art machine learning models. In order to identify credit card frauds, the fifteenth chapter introduces a hybrid model. In the sixteenth chapter, the editors propose a model that leverages natural language processing techniques for generating a mapping between APT-related reports and cyber kill chain. A deep learning-based approach to detect ransomware is introduced, as well as a proposed clustering approach to detect IoT malware in the last two chapters. This handbook primarily targets professionals and scientists working in Big Data, Digital Forensics, Machine Learning, Cyber Security Cyber Threat Analytics and Cyber Threat Hunting as a reference book. Advanced level-students and researchers studying and working in Computer systems, Computer networks and Artificial intelligence will also find this reference useful.

Handbook of Big Data Analytics and Forensics

Hence, we need solutions to help us perform big data analytics, security and forensic investigation to identify and extract relevant information, identify malicious activities and evidence of relevance, etc. [7].

Author: Kim-Kwang Raymond Choo

Publisher: Springer Nature

ISBN: 9783030747534

Category:

Page:

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Handbook of Big Data and IoT Security

Challenges associated with IoT and big data forensics include locating, recovering and preserving reliable forensic artifacts [10]. Findings from data analytics and forensic investigation can also inform cyber security strategy ...

Author: Ali Dehghantanha

Publisher: Springer

ISBN: 9783030105433

Category: Computers

Page: 384

View: 268

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This handbook provides an overarching view of cyber security and digital forensic challenges related to big data and IoT environment, prior to reviewing existing data mining solutions and their potential application in big data context, and existing authentication and access control for IoT devices. An IoT access control scheme and an IoT forensic framework is also presented in this book, and it explains how the IoT forensic framework can be used to guide investigation of a popular cloud storage service. A distributed file system forensic approach is also presented, which is used to guide the investigation of Ceph. Minecraft, a Massively Multiplayer Online Game, and the Hadoop distributed file system environment are also forensically studied and their findings reported in this book. A forensic IoT source camera identification algorithm is introduced, which uses the camera's sensor pattern noise from the captured image. In addition to the IoT access control and forensic frameworks, this handbook covers a cyber defense triage process for nine advanced persistent threat (APT) groups targeting IoT infrastructure, namely: APT1, Molerats, Silent Chollima, Shell Crew, NetTraveler, ProjectSauron, CopyKittens, Volatile Cedar and Transparent Tribe. The characteristics of remote-controlled real-world Trojans using the Cyber Kill Chain are also examined. It introduces a method to leverage different crashes discovered from two fuzzing approaches, which can be used to enhance the effectiveness of fuzzers. Cloud computing is also often associated with IoT and big data (e.g., cloud-enabled IoT systems), and hence a survey of the cloud security literature and a survey of botnet detection approaches are presented in the book. Finally, game security solutions are studied and explained how one may circumvent such solutions. This handbook targets the security, privacy and forensics research community, and big data research community, including policy makers and government agencies, public and private organizations policy makers. Undergraduate and postgraduate students enrolled in cyber security and forensic programs will also find this handbook useful as a reference.

Handbook of Big Data Privacy

This handbook provides comprehensive knowledge and includes an overview of the current state-of-the-art of Big Data Privacy, with chapters written by international world leaders from academia and industry working in this field.

Author: Kim-Kwang Raymond Choo

Publisher: Springer Nature

ISBN: 9783030385576

Category: Computers

Page: 397

View: 331

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This handbook provides comprehensive knowledge and includes an overview of the current state-of-the-art of Big Data Privacy, with chapters written by international world leaders from academia and industry working in this field. The first part of this book offers a review of security challenges in critical infrastructure and offers methods that utilize acritical intelligence (AI) techniques to overcome those issues. It then focuses on big data security and privacy issues in relation to developments in the Industry 4.0. Internet of Things (IoT) devices are becoming a major source of security and privacy concern in big data platforms. Multiple solutions that leverage machine learning for addressing security and privacy issues in IoT environments are also discussed this handbook. The second part of this handbook is focused on privacy and security issues in different layers of big data systems. It discusses about methods for evaluating security and privacy of big data systems on network, application and physical layers. This handbook elaborates on existing methods to use data analytic and AI techniques at different layers of big data platforms to identify privacy and security attacks. The final part of this handbook is focused on analyzing cyber threats applicable to the big data environments. It offers an in-depth review of attacks applicable to big data platforms in smart grids, smart farming, FinTech, and health sectors. Multiple solutions are presented to detect, prevent and analyze cyber-attacks and assess the impact of malicious payloads to those environments. This handbook provides information for security and privacy experts in most areas of big data including; FinTech, Industry 4.0, Internet of Things, Smart Grids, Smart Farming and more. Experts working in big data, privacy, security, forensics, malware analysis, machine learning and data analysts will find this handbook useful as a reference. Researchers and advanced-level computer science students focused on computer systems, Internet of Things, Smart Grid, Smart Farming, Industry 4.0 and network analysts will also find this handbook useful as a reference.

Handbook of Research on Engineering Business and Healthcare Applications of Data Science and Analytics

Big data threat landscape and big data practice guide. ENISA. ... Data science: What the educated citizen needs to know. ... Forensic Science Review, 3(3), 179–182. doi:10.1080/20961790.2018.1500078 PMID:30483667 Google Trends. (2019).

Author: Patil, Bhushan

Publisher: IGI Global

ISBN: 9781799830542

Category: Computers

Page: 583

View: 639

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Analyzing data sets has continued to be an invaluable application for numerous industries. By combining different algorithms, technologies, and systems used to extract information from data and solve complex problems, various sectors have reached new heights and have changed our world for the better. The Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics is a collection of innovative research on the methods and applications of data analytics. While highlighting topics including artificial intelligence, data security, and information systems, this book is ideally designed for researchers, data analysts, data scientists, healthcare administrators, executives, managers, engineers, IT consultants, academicians, and students interested in the potential of data application technologies.

Handbook of Computer Networks and Cyber Security

On the arrival of new and modern techniques for analytics and potentially to mine Big Data processes, it is now becoming essential to uplift the analytics in an improved way. The digital forensic field is getting intensive importance ...

Author: Brij B. Gupta

Publisher: Springer Nature

ISBN: 9783030222772

Category: Computers

Page: 959

View: 259

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This handbook introduces the basic principles and fundamentals of cyber security towards establishing an understanding of how to protect computers from hackers and adversaries. The highly informative subject matter of this handbook, includes various concepts, models, and terminologies along with examples and illustrations to demonstrate substantial technical details of the field. It motivates the readers to exercise better protection and defense mechanisms to deal with attackers and mitigate the situation. This handbook also outlines some of the exciting areas of future research where the existing approaches can be implemented. Exponential increase in the use of computers as a means of storing and retrieving security-intensive information, requires placement of adequate security measures to safeguard the entire computing and communication scenario. With the advent of Internet and its underlying technologies, information security aspects are becoming a prime concern towards protecting the networks and the cyber ecosystem from variety of threats, which is illustrated in this handbook. This handbook primarily targets professionals in security, privacy and trust to use and improve the reliability of businesses in a distributed manner, as well as computer scientists and software developers, who are seeking to carry out research and develop software in information and cyber security. Researchers and advanced-level students in computer science will also benefit from this reference.

Handbook of Research on Network Forensics and Analysis Techniques

High Capacity Despite Better Steganalysis (F5 – A Steganographic Algorithm). ... Hadoop: The definitive guide. ... Big Data Based Security Analytics for Protecting Virtualized Infrastructures in Cloud Computing. IEEE Transactions on Big ...

Author: Shrivastava, Gulshan

Publisher: IGI Global

ISBN: 9781522541011

Category: Computers

Page: 509

View: 405

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With the rapid advancement in technology, myriad new threats have emerged in online environments. The broad spectrum of these digital risks requires new and innovative methods for protection against cybercrimes. The Handbook of Research on Network Forensics and Analysis Techniques is a current research publication that examines the advancements and growth of forensic research from a relatively obscure tradecraft to an important part of many investigations. Featuring coverage on a broad range of topics including cryptocurrency, hand-based biometrics, and cyberterrorism, this publication is geared toward professionals, computer forensics practitioners, engineers, researchers, and academics seeking relevant research on the development of forensic tools.

Securing IoT and Big Data

Privacy of big data: a review. In Handbook of Big Data and IoT Security, pp. 5–23. Springer, Cham, 2019. [65] A. Nieto, R. Roman, ... Cyber forensics framework for big data analytics in IoT environment using machine learning.

Author: Vijayalakshmi Saravanan

Publisher: CRC Press

ISBN: 9781000258516

Category: Technology & Engineering

Page: 170

View: 485

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This book covers IoT and Big Data from a technical and business point of view. The book explains the design principles, algorithms, technical knowledge, and marketing for IoT systems. It emphasizes applications of big data and IoT. It includes scientific algorithms and key techniques for fusion of both areas. Real case applications from different industries are offering to facilitate ease of understanding the approach. The book goes on to address the significance of security algorithms in combing IoT and big data which is currently evolving in communication technologies. The book is written for researchers, professionals, and academicians from interdisciplinary and transdisciplinary areas. The readers will get an opportunity to know the conceptual ideas with step-by-step pragmatic examples which makes ease of understanding no matter the level of the reader.

Cognitive Social Mining Applications in Data Analytics and Forensics

Her research interests are pattern recognition and analysis of nonlinear time series data and digital analytics. ... He is a co-author of the book " “Handbook of Research on Big Data and the IoT,” edited by Dr. Gurjit Kaur and Dr.

Author: Haldorai, Anandakumar

Publisher: IGI Global

ISBN: 9781522575238

Category: Computers

Page: 326

View: 948

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Recently, there has been a rapid increase in interest regarding social network analysis in the data mining community. Cognitive radios are expected to play a major role in meeting this exploding traffic demand on social networks due to their ability to sense the environment, analyze outdoor parameters, and then make decisions for dynamic time, frequency, space, resource allocation, and management to improve the utilization of mining the social data. Cognitive Social Mining Applications in Data Analytics and Forensics is an essential reference source that reviews cognitive radio concepts and examines their applications to social mining using a machine learning approach so that an adaptive and intelligent mining is achieved. Featuring research on topics such as data mining, real-time ubiquitous social mining services, and cognitive computing, this book is ideally designed for social network analysts, researchers, academicians, and industry professionals.

Research Handbook on Big Data Law

Big. data. analytics. for. e-discovery. Johannes. C. Scholtes. and. Hendrik. Jacob. van. den. Herik. 1. INTRODUCTION. When it comes to big data and the law, e-discovery is the application that deals with the largest legal data ...

Author: Roland Vogl

Publisher: Edward Elgar Publishing

ISBN: 9781788972826

Category: Law

Page: 544

View: 959

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This state-of-the-art Research Handbook provides an overview of research into, and the scope of current thinking in, the field of big data analytics and the law. It contains a wealth of information to survey the issues surrounding big data analytics in legal settings, as well as legal issues concerning the application of big data techniques in different domains.