Increasingly, crimes and fraud are digital in nature, occurring at breakneck speed and encompassing large volumes of data. To combat this unlawful activity, knowledge about the use of machine learning technology and software is critical. Machine Learning Forensics for Law Enforcement, Security, and Intelligence integrates an assortment of deductive
Increasingly, crimes and fraud are digital in nature, occurring at breakneck speed and encompassing large volumes of data. To combat this unlawful activity, knowledge about the use of machine learning technology and software is critical. Machine Learning Forensics for Law Enforcement, Security, and Intelligence integrates an assortment of deductive and instructive tools, techniques, and technologies to arm professionals with the tools they need to be prepared and stay ahead of the game. Step-by-step instructions The book is a practical guide on how to conduct forensic investigations using self-organizing clustering map (SOM) neural networks, text extraction, and rule generating software to "interrogate the evidence." This powerful data is indispensable for fraud detection, cybersecurity, competitive counterintelligence, and corporate and litigation investigations. The book also provides step-by-step instructions on how to construct adaptive criminal and fraud detection systems for organizations. Prediction is the key Internet activity, email, and wireless communications can be captured, modeled, and deployed in order to anticipate potential cyber attacks and other types of crimes. The successful prediction of human reactions and server actions by quantifying their behaviors is invaluable for pre-empting criminal activity. This volume assists chief information officers, law enforcement personnel, legal and IT professionals, investigators, and competitive intelligence analysts in the strategic planning needed to recognize the patterns of criminal activities in order to predict when and where crimes and intrusions are likely to take place.
Data science, informatics and technology have inspired health professionals and informaticians to improve healthcare for the benefit of all patients, and the field of biomedical and health informatics is one which has become increasingly important in recent years. This volume presents the papers delivered at ICIMTH 2022, the 20th International Conference on Informatics, Management, and Technology in Healthcare, held in Athens, Greece, from 1-3 July 2022. The ICIMTH Conference is an annual scientific event attended by scientists from around the world working in the field of biomedical and health informatics. This year, thanks to the improvement in the situation as regards the COVID-19 pandemic and the consequent lifting of restrictions, the conference was once again a live event, but virtual sessions by means of teleconferencing were also enabled for those unable to travel due to local restrictions. The field of biomedical and health informatics was examined from a very broad perspective, with participants presenting the research and application outcomes of informatics from cell to populations, including several technologies such as imaging, sensors, biomedical equipment, and management and organizational aspects, including legal and social issues. More than 230 submissions were received, with a total of 130 accepted as full papers and 19 as short communication and poster papers after review. As expected, a significant number of papers were related to the COVID-19 pandemic. Providing a state-of-the-art overview of biomedical and health informatics, the book will be of interest to all those working in the field of healthcare, researchers and practitioners alike
Through the rise of big data and the internet of things, terrorist organizations have been freed from geographic and logistical confines and now have more power than ever before to strike the average citizen directly at home. This, coupled with the inherently asymmetrical nature of cyberwarfare, which grants great advantage to the attacker, has created an unprecedented national security risk that both governments and their citizens are woefully ill-prepared to face. Examining cyber warfare and terrorism through a critical and academic perspective can lead to a better understanding of its foundations and implications. Cyber Warfare and Terrorism: Concepts, Methodologies, Tools, and Applications is an essential reference for the latest research on the utilization of online tools by terrorist organizations to communicate with and recruit potential extremists and examines effective countermeasures employed by law enforcement agencies to defend against such threats. Highlighting a range of topics such as cyber threats, digital intelligence, and counterterrorism, this multi-volume book is ideally designed for law enforcement, government officials, lawmakers, security analysts, IT specialists, software developers, intelligence and security practitioners, students, educators, and researchers.
The tools of crime constantly evolve, and law enforcement and forensic investigators must understand advanced forensic techniques to ensure that the most complete evidence is brought to trial. Paramount also the need for investigators to ensure that evidence adheres to the boundaries of the legal system, a place where policy often lags behind new innovations. Crime Prevention Technologies and Applications for Advancing Criminal Investigation addresses the use of electronic devices and software for crime prevention, investigation, and the application of a broad spectrum of sciences to answer questions of interest to the legal system. This book fosters a forum for advancing research and development of the theory and practice of digital crime prevention and forensics.
This book presents a comprehensive study of different tools and techniques available to perform network forensics. Also, various aspects of network forensics are reviewed as well as related technologies and their limitations. This helps security practitioners and researchers in better understanding of the problem, current solution space, and future research scope to detect and investigate various network intrusions against such attacks efficiently. Forensic computing is rapidly gaining importance since the amount of crime involving digital systems is steadily increasing. Furthermore, the area is still underdeveloped and poses many technical and legal challenges. The rapid development of the Internet over the past decade appeared to have facilitated an increase in the incidents of online attacks. There are many reasons which are motivating the attackers to be fearless in carrying out the attacks. For example, the speed with which an attack can be carried out, the anonymity provided by the medium, nature of medium where digital information is stolen without actually removing it, increased availability of potential victims and the global impact of the attacks are some of the aspects. Forensic analysis is performed at two different levels: Computer Forensics and Network Forensics. Computer forensics deals with the collection and analysis of data from computer systems, networks, communication streams and storage media in a manner admissible in a court of law. Network forensics deals with the capture, recording or analysis of network events in order to discover evidential information about the source of security attacks in a court of law. Network forensics is not another term for network security. It is an extended phase of network security as the data for forensic analysis are collected from security products like firewalls and intrusion detection systems. The results of this data analysis are utilized for investigating the attacks. Network forensics generally refers to the collection and analysis of network data such as network traffic, firewall logs, IDS logs, etc. Technically, it is a member of the already-existing and expanding the field of digital forensics. Analogously, network forensics is defined as "The use of scientifically proved techniques to collect, fuses, identifies, examine, correlate, analyze, and document digital evidence from multiple, actively processing and transmitting digital sources for the purpose of uncovering facts related to the planned intent, or measured success of unauthorized activities meant to disrupt, corrupt, and or compromise system components as well as providing information to assist in response to or recovery from these activities." Network forensics plays a significant role in the security of today’s organizations. On the one hand, it helps to learn the details of external attacks ensuring similar future attacks are thwarted. Additionally, network forensics is essential for investigating insiders’ abuses that constitute the second costliest type of attack within organizations. Finally, law enforcement requires network forensics for crimes in which a computer or digital system is either being the target of a crime or being used as a tool in carrying a crime. Network security protects the system against attack while network forensics focuses on recording evidence of the attack. Network security products are generalized and look for possible harmful behaviors. This monitoring is a continuous process and is performed all through the day. However, network forensics involves post mortem investigation of the attack and is initiated after crime notification. There are many tools which assist in capturing data transferred over the networks so that an attack or the malicious intent of the intrusions may be investigated. Similarly, various network forensic frameworks are proposed in the literature.
Advancing technologies, especially computer technologies, have necessitated the creation of a comprehensive investigation and collection methodology for digital and online evidence. The goal of cyber forensics is to perform a structured investigation while maintaining a documented chain of evidence to find out exactly what happened on a computing device or on a network and who was responsible for it. Critical Concepts, Standards, and Techniques in Cyber Forensics is a critical research book that focuses on providing in-depth knowledge about online forensic practices and methods. Highlighting a range of topics such as data mining, digital evidence, and fraud investigation, this book is ideal for security analysts, IT specialists, software engineers, researchers, security professionals, criminal science professionals, policymakers, academicians, and students.
Digital Triage Forensics: Processing the Digital Crime Scene provides the tools, training, and techniques in Digital Triage Forensics (DTF), a procedural model for the investigation of digital crime scenes including both traditional crime scenes and the more complex battlefield crime scenes. The DTF is used by the U.S. Army and other traditional police agencies for current digital forensic applications. The tools, training, and techniques from this practice are being brought to the public in this book for the first time. Now corporations, law enforcement, and consultants can benefit from the unique perspectives of the experts who coined Digital Triage Forensics. The text covers the collection of digital media and data from cellular devices and SIM cards. It also presents outlines of pre- and post- blast investigations. This book is divided into six chapters that present an overview of the age of warfare, key concepts of digital triage and battlefield forensics, and methods of conducting pre/post-blast investigations. The first chapter considers how improvised explosive devices (IEDs) have changed from basic booby traps to the primary attack method of the insurgents in Iraq and Afghanistan. It also covers the emergence of a sustainable vehicle for prosecuting enemy combatants under the Rule of Law in Iraq as U.S. airmen, marines, sailors, and soldiers perform roles outside their normal military duties and responsibilities. The remaining chapters detail the benefits of DTF model, the roles and responsibilities of the weapons intelligence team (WIT), and the challenges and issues of collecting digital media in battlefield situations. Moreover, data collection and processing as well as debates on the changing role of digital forensics investigators are explored. This book will be helpful to forensic scientists, investigators, and military personnel, as well as to students and beginners in forensics. - Includes coverage on collecting digital media - Outlines pre- and post-blast investigations - Features content on collecting data from cellular devices and SIM cards
The authors develop a malware fingerprinting framework to cover accurate android malware detection and family attribution in this book. The authors emphasize the following: (1) the scalability over a large malware corpus; (2) the resiliency to common obfuscation techniques; (3) the portability over different platforms and architectures. First, the authors propose an approximate fingerprinting technique for android packaging that captures the underlying static structure of the android applications in the context of bulk and offline detection at the app-market level. This book proposes a malware clustering framework to perform malware clustering by building and partitioning the similarity network of malicious applications on top of this fingerprinting technique. Second, the authors propose an approximate fingerprinting technique that leverages dynamic analysis and natural language processing techniques to generate Android malware behavior reports. Based on this fingerprinting technique, the authors propose a portable malware detection framework employing machine learning classification. Third, the authors design an automatic framework to produce intelligence about the underlying malicious cyber-infrastructures of Android malware. The authors then leverage graph analysis techniques to generate relevant intelligence to identify the threat effects of malicious Internet activity associated with android malware. The authors elaborate on an effective android malware detection system, in the online detection context at the mobile device level. It is suitable for deployment on mobile devices, using machine learning classification on method call sequences. Also, it is resilient to common code obfuscation techniques and adaptive to operating systems and malware change overtime, using natural language processing and deep learning techniques. Researchers working in mobile and network security, machine learning and pattern recognition will find this book useful as a reference. Advanced-level students studying computer science within these topic areas will purchase this book as well.
This intelligence guide was prepared in response to requests from law enforcement executives for guidance in intelligence functions in a post-September 11 world. It will help law enforcement agencies develop or enhance their intelligence capacity and enable them to fight terrorism and other crimes while preserving community policing relationships. The world of law enforcement intelligence has changed dramatically since September 11, 2001. State, local, and tribal law enforcement agencies have been tasked with a variety of new responsibilities; intelligence is just one. In addition, the intelligence discipline has evolved significantly in recent years. As these various trends have merged, increasing numbers of American law enforcement agencies have begun to explore, and sometimes embrace, the intelligence function. This guide is intended to help them in this process. The guide is directed primarily toward state, local, and tribal law enforcement agencies of all sizes that need to develop or reinvigorate their intelligence function. Rather than being a manual to teach a person how to be an intelligence analyst, it is directed toward that manager, supervisor, or officer who is assigned to create an intelligence function. It is intended to provide ideas, definitions, concepts, policies, and resources. It is a primera place to start on a new managerial journey. Every law enforcement agency in the United States, regardless of agency size, must have the capacity to understand the implications of information collection, analysis, and intelligence sharing. Each agency must have an organized mechanism to receive and manage intelligence as well as a mechanism to report and share critical information with other law enforcement agencies. In addition, it is essential that law enforcement agencies develop lines of communication and information-sharing protocols with the private sector, particularly those related to the critical infrastructure, as well as with those private entities that are potential targets of terrorists and criminal enterprises. Not every agency has the staff or resources to create a formal intelligence unit, nor is it necessary in smaller agencies. This document will provide common language and processes to develop and employ an intelligence capacity in SLTLE agencies across the United States as well as articulate a uniform understanding of concepts, issues, and terminology for law enforcement intelligence (LEI). While terrorism issues are currently most pervasive in the current discussion of LEI, the principles of intelligence discussed in this document apply beyond terrorism and include organized crime and entrepreneurial crime of all forms. Drug trafficking and the associated crime of money laundering, for example, continue to be a significant challenge for law enforcement. Transnational computer crime, particularly Internet fraud, identity theft cartels, and global black marketeering of stolen and counterfeit goods, are entrepreneurial crime problems that are increasingly being relegated to SLTLE agencies to investigate simply because of the volume of criminal incidents. Similarly, local law enforcement is being increasingly drawn into human trafficking and illegal immigration enterprises and the often associated crimes related to counterfeiting of official documents, such as passports, visas, driver's licenses, Social Security cards, and credit cards. All require an intelligence capacity for SLTLE, as does the continuation of historical organized crime activities such as auto theft, cargo theft, and virtually any other scheme that can produce profit for an organized criminal entity. To be effective, the law enforcement community must interpret intelligence-related language in a consistent manner. In addition, common standards, policies, and practices will help expedite intelligence sharing while at the same time protecting the privacy of citizens and preserving hard-won community policing relationships.~
