[PDF] Machine Learning For Authorship Attribution And Cyber Forensics eBook

Author : Farkhund Iqbal
Publisher : Springer Nature
Page : 158 pages
File Size : 45,61 MB
Release : 2020-12-04
Category : Computers
ISBN : 3030616754

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The book first explores the cybersecurity’s landscape and the inherent susceptibility of online communication system such as e-mail, chat conversation and social media in cybercrimes. Common sources and resources of digital crimes, their causes and effects together with the emerging threats for society are illustrated in this book. This book not only explores the growing needs of cybersecurity and digital forensics but also investigates relevant technologies and methods to meet the said needs. Knowledge discovery, machine learning and data analytics are explored for collecting cyber-intelligence and forensics evidence on cybercrimes. Online communication documents, which are the main source of cybercrimes are investigated from two perspectives: the crime and the criminal. AI and machine learning methods are applied to detect illegal and criminal activities such as bot distribution, drug trafficking and child pornography. Authorship analysis is applied to identify the potential suspects and their social linguistics characteristics. Deep learning together with frequent pattern mining and link mining techniques are applied to trace the potential collaborators of the identified criminals. Finally, the aim of the book is not only to investigate the crimes and identify the potential suspects but, as well, to collect solid and precise forensics evidence to prosecute the suspects in the court of law.

Author : Patrick Juola
Publisher : Now Publishers Inc
Page : 116 pages
File Size : 24,70 MB
Release : 2008
Category : Authorship, Disputed
ISBN : 160198118X

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Authorship Attribution surveys the history and present state of the discipline, presenting some comparative results where available. It also provides a theoretical and empirically-tested basis for further work. Many modern techniques are described and evaluated, along with some insights for application for novices and experts alike.

Author : Bansal, Himani
Publisher : IGI Global
Page : 339 pages
File Size : 22,5 MB
Release : 2018-03-23
Category : Business & Economics
ISBN : 1522550984

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Social technology is quickly becoming a vital tool in our personal, educational, and professional lives. Its use must be further examined in order to determine the role of social media technology in organizational settings to promote business development and growth. Social Network Analytics for Contemporary Business Organizations is a critical scholarly resource that analyzes the application of social media in business applications. Featuring coverage on a broad range of topics, such as business management, dynamic networks, and online interaction, this book is geared towards professionals, researchers, academics, students, managers, and practitioners actively involved in the business industry.

Author : Sadia Afroz
Publisher :
Page : 182 pages
File Size : 12,85 MB
Release : 2013
Category : Authorship
ISBN :

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In digital forensics, questions often arise about the authors of documents: their identity, demographic background, and whether they can be linked to other documents. The field of stylometry uses linguistic features and machine learning techniques to answer these questions. While stylometry techniques can identify authors with high accuracy in non-adversarial scenarios, their accuracy is reduced to random guessing when faced with authors who intentionally obfuscate their writing style or attempt to imitate that of another author. Most authorship attribution methods were not evaluated in challenging real-world datasets with foreign language and unconventional spelling (e.g. l33tsp3ak). In this thesis we explore the performance of authorship attribution methods in adversarial settings where authors take measures to hide their identity by changing their writing style and by creating multiple identities. We show that using a large feature set, it is possible to distinguish regular documents from deceptive documents with high accuracy and present an analysis of linguistic features that can be modified to hide writing style. We show how to adapt regular authorship attribution to difficult datasets such as leaked underground forum and present a method for detecting multiple identities of authors. We demonstrate the utility of our approach with a case study that includes applying our technique to an underground forum and manual analysis to validate the results, enabling the discovery of previously undetected multiple accounts.

Author : Sabu M. Thampi
Publisher : Springer
Page : 442 pages
File Size : 34,8 MB
Release : 2017-10-20
Category : Technology & Engineering
ISBN : 3319683853

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This book constitutes the thoroughly refereed post-conference proceedings of the third International Symposium on Intelligent Systems Technologies and Applications (ISTA’17), September 13-16, 2017, Manipal, Karnataka, India. All submissions were evaluated on the basis of their significance, novelty, and technical quality. This proceedings contains 34 papers selected for presentation at the Symposium.

Author : Shlomi Dolev
Publisher : Springer
Page : 318 pages
File Size : 26,51 MB
Release : 2017-06-14
Category : Computers
ISBN : 331960080X

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This book constitutes the proceedings of the first International Symposium on Cyber Security Cryptography and Machine Learning, held in Beer-Sheva, Israel, in June 2017. The 17 full and 4 short papers presented include cyber security; secure software development methodologies, formal methods semantics and verification of secure systems; fault tolerance, reliability, availability of distributed secure systems; game-theoretic approaches to secure computing; automatic recovery of self-stabilizing and self-organizing systems; communication, authentication and identification security; cyber security for mobile and Internet of things; cyber security of corporations; security and privacy for cloud, edge and fog computing; cryptography; cryptographic implementation analysis and construction; secure multi-party computation; privacy-enhancing technologies and anonymity; post-quantum cryptography and security; machine learning and big data; anomaly detection and malware identification; business intelligence and security; digital forensics; digital rights management; trust management and reputation systems; information retrieval, risk analysis, DoS.

Author : Lejla Batina
Publisher : Springer Nature
Page : 365 pages
File Size : 32,94 MB
Release : 2022-04-07
Category : Computers
ISBN : 3030987957

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AI has become an emerging technology to assess security and privacy, with many challenges and potential solutions at the algorithm, architecture, and implementation levels. So far, research on AI and security has looked at subproblems in isolation but future solutions will require sharing of experience and best practice in these domains. The editors of this State-of-the-Art Survey invited a cross-disciplinary team of researchers to a Lorentz workshop in 2019 to improve collaboration in these areas. Some contributions were initiated at the event, others were developed since through further invitations, editing, and cross-reviewing. This contributed book contains 14 invited chapters that address side-channel attacks and fault injection, cryptographic primitives, adversarial machine learning, and intrusion detection. The chapters were evaluated based on their significance, technical quality, and relevance to the topics of security and AI, and each submission was reviewed in single-blind mode and revised.

Author : Jacques Savoy
Publisher : Springer Nature
Page : 286 pages
File Size : 41,56 MB
Release : 2020-09-28
Category : Computers
ISBN : 3030533603

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This book presents methods and approaches used to identify the true author of a doubtful document or text excerpt. It provides a broad introduction to all text categorization problems (like authorship attribution, psychological traits of the author, detecting fake news, etc.) grounded in stylistic features. Specifically, machine learning models as valuable tools for verifying hypotheses or revealing significant patterns hidden in datasets are presented in detail. Stylometry is a multi-disciplinary field combining linguistics with both statistics and computer science. The content is divided into three parts. The first, which consists of the first three chapters, offers a general introduction to stylometry, its potential applications and limitations. Further, it introduces the ongoing example used to illustrate the concepts discussed throughout the remainder of the book. The four chapters of the second part are more devoted to computer science with a focus on machine learning models. Their main aim is to explain machine learning models for solving stylometric problems. Several general strategies used to identify, extract, select, and represent stylistic markers are explained. As deep learning represents an active field of research, information on neural network models and word embeddings applied to stylometry is provided, as well as a general introduction to the deep learning approach to solving stylometric questions. In turn, the third part illustrates the application of the previously discussed approaches in real cases: an authorship attribution problem, seeking to discover the secret hand behind the nom de plume Elena Ferrante, an Italian writer known worldwide for her My Brilliant Friend’s saga; author profiling in order to identify whether a set of tweets were generated by a bot or a human being and in this second case, whether it is a man or a woman; and an exploration of stylistic variations over time using US political speeches covering a period of ca. 230 years. A solutions-based approach is adopted throughout the book, and explanations are supported by examples written in R. To complement the main content and discussions on stylometric models and techniques, examples and datasets are freely available at the author’s Github website.

Author : Gilbert Peterson
Publisher : Springer
Page : 336 pages
File Size : 23,55 MB
Release : 2014-10-09
Category : Computers
ISBN : 3662449528

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Digital forensics deals with the acquisition, preservation, examination, analysis and presentation of electronic evidence. Networked computing, wireless communications and portable electronic devices have expanded the role of digital forensics beyond traditional computer crime investigations. Practically every crime now involves some aspect of digital evidence; digital forensics provides the techniques and tools to articulate this evidence. Digital forensics also has myriad intelligence applications. Furthermore, it has a vital role in information assurance -- investigations of security breaches yield valuable information that can be used to design more secure systems. Advances in Digital Forensics X describes original research results and innovative applications in the discipline of digital forensics. In addition, it highlights some of the major technical and legal issues related to digital evidence and electronic crime investigations. The areas of coverage include: - Internet Crime Investigations; - Forensic Techniques; - Mobile Device Forensics; - Forensic Tools and Training. This book is the 10th volume in the annual series produced by the International Federation for Information Processing (IFIP) Working Group 11.9 on Digital Forensics, an international community of scientists, engineers and practitioners dedicated to advancing the state of the art of research and practice in digital forensics. The book contains a selection of twenty-two edited papers from the 10th Annual IFIP WG 11.9 International Conference on Digital Forensics, held in Vienna, Austria in the winter of 2014. Advances in Digital Forensics X is an important resource for researchers, faculty members and graduate students, as well as for practitioners and individuals engaged in research and development efforts for the law enforcement and intelligence communities.