Probabilistic Characterization Of Adversary Behavior In Cyber Security

The objective of this SMS effort is to provide a probabilistic characterization of adversary behavior in cyber security. This includes both quantitative (data analysis) and qualitative (literature review) components. A set of real LLNL email data was obtained for this study, consisting of several years worth of unfiltered traffic sent to a selection of addresses at ciac.org. The email data was subjected to three interrelated analyses: a textual study of the header data and subject matter, an examination of threats present in message attachments, and a characterization of the maliciousness of embedded URLs.

The wonders and advantages of modern age electronics and the World Wide Web have also, unfortunately, ushered in a new age of terrorism. The growing connectivity among secure and insecure networks has created new opportunities for unauthorized intrusions into sensitive or proprietary computer systems. Some of these vulnerabilities are waiting to be exploited, while numerous others already have. Everyday that a vulnerability or threat goes unchecked greatly increases an attack and the damage it can cause. Who knows what the prospects for a cascade of failures across US infrastructures could lead to. What type of group or individual would exploit this vulnerability, and why would they do it? "Inside the Mind of a Criminal Hacker" sets the stage and cast of characters for examples and scenarios such as this, providing the security specialist a window into the enemy’s mind - necessary in order to develop a well configured defense. Written by leading security and counter-terrorism experts, whose experience include first-hand exposure in working with government branches & agencies (such as the FBI, US Army, Department of Homeland Security), this book sets a standard for the fight against the cyber-terrorist. Proving, that at the heart of the very best defense is knowing and understanding your enemy. * This book will demonstrate the motives and motivations of criminal hackers through profiling attackers at post attack and forensic levels. * This book is essential to those who need to truly "know thy enemy" in order to prepare the best defense. * . The breadth of material in "Inside the Criminal Mind" will surprise every security specialist and cyber-terrorist buff of how much they do and (more importantly) don't know about the types of adversaries they stand to face.

This SpringerBrief presents a brief introduction to probabilistic risk assessment (PRA), followed by a discussion of abnormal event detection techniques in industrial control systems (ICS). It also provides an introduction to the use of game theory for the development of cyber-attack response models and a discussion on the experimental testbeds used for ICS cyber security research. The probabilistic risk assessment framework used by the nuclear industry provides a valid framework to understand the impacts of cyber-attacks in the physical world. An introduction to the PRA techniques such as fault trees, and event trees is provided along with a discussion on different levels of PRA and the application of PRA techniques in the context of cybersecurity. A discussion on machine learning based fault detection and diagnosis (FDD) methods and cyber-attack detection methods for industrial control systems are introduced in this book as well. A dynamic Bayesian networks based method that can be used to detect an abnormal event and classify it as either a component fault induced safety event or a cyber-attack is discussed. An introduction to the stochastic game formulation of the attacker-defender interaction in the context of cyber-attacks on industrial control systems to compute optimal response strategies is presented. Besides supporting cyber-attack response, the analysis based on the game model also supports the behavioral study of the defender and the attacker during a cyber-attack, and the results can then be used to analyze the risk to the system caused by a cyber-attack. A brief review of the current state of experimental testbeds used in ICS cybersecurity research and a comparison of the structures of various testbeds and the attack scenarios supported by those testbeds is included. A description of a testbed for nuclear power applications, followed by a discussion on the design of experiments that can be carried out on the testbed and the associated results is covered as well. This SpringerBrief is a useful resource tool for researchers working in the areas of cyber security for industrial control systems, energy systems and cyber physical systems. Advanced-level students that study these topics will also find this SpringerBrief useful as a study guide.

This book constitutes the refereed proceedings of the 11th European Symposium on Research in Computer Security, ESORICS 2006. The 32 revised full papers presented were carefully reviewed and selected from 160 submissions. ESORICS is confirmed as the European research event in computer security; it presents original research contributions, case studies and implementation experiences addressing any aspect of computer security - in theory, mechanisms, applications, or practical experience.

With the recent development of cyber-crime and cyber-warefare, new techniques for thwarting cyber attackers are required. Deception is a mechanism that attempts to distort or misled an adversary. It is a proven tactic leveraged in traditional warfare with a long history of noted successes. While deception has seen great success in traditional warfare, it has seen little use within the cyber security realm. Furthermore, there is very little demonstrated modeling of such defenses in terms of attackers success. This thesis establishes a novel urn-modeling technique for providing the probability of success for an attacker in two different network deception defenses, network address shuffling and honeypots. This work goes on to analyze these models in two scenarios, gaining a foothold and minimum to win, providing insight into the effect both defenses can have under various environments. Finally, this thesis performs an empirical analysis of network address shuffling to provide a cost-benefit analysis regarding attack success and the effect on legitimate network users.

This book is intended to give researchers and practitioners in the cross-cutting fields of artificial intelligence, machine learning (AI/ML) and cyber security up-to-date and in-depth knowledge of recent techniques for improving the vulnerabilities of AI/ML systems against attacks from malicious adversaries. The ten chapters in this book, written by eminent researchers in AI/ML and cyber-security, span diverse, yet inter-related topics including game playing AI and game theory as defenses against attacks on AI/ML systems, methods for effectively addressing vulnerabilities of AI/ML operating in large, distributed environments like Internet of Things (IoT) with diverse data modalities, and, techniques to enable AI/ML systems to intelligently interact with humans that could be malicious adversaries and/or benign teammates. Readers of this book will be equipped with definitive information on recent developments suitable for countering adversarial threats in AI/ML systems towards making them operate in a safe, reliable and seamless manner.

Today’s cyber defenses are largely static allowing adversaries to pre-plan their attacks. In response to this situation, researchers have started to investigate various methods that make networked information systems less homogeneous and less predictable by engineering systems that have homogeneous functionalities but randomized manifestations. The 10 papers included in this State-of-the Art Survey present recent advances made by a large team of researchers working on the same US Department of Defense Multidisciplinary University Research Initiative (MURI) project during 2013-2019. This project has developed a new class of technologies called Adaptive Cyber Defense (ACD) by building on two active but heretofore separate research areas: Adaptation Techniques (AT) and Adversarial Reasoning (AR). AT methods introduce diversity and uncertainty into networks, applications, and hosts. AR combines machine learning, behavioral science, operations research, control theory, and game theory to address the goal of computing effective strategies in dynamic, adversarial environments.

Cloud technologies have revolutionized the way we store information and perform various computing tasks. With the rise of this new technology, the ability to secure information stored on the cloud becomes a concern. The Handbook of Research on Securing Cloud-Based Databases with Biometric Applications explores the latest innovations in promoting cloud security through human authentication techniques. Exploring methods of access by identification, including the analysis of facial features, fingerprints, DNA, dental characteristics, and voice patterns, this publication is designed especially for IT professionals, academicians, and upper-level students seeking current research surrounding cloud security.

ESORICS, the European Symposium on Research in Computer Security, is the leading research-oriented conference on the theory and practice of computer security in Europe. It takes place every two years, at various locations throughout Europe, and is coordinated by an independent Steering Committee. ESORICS 2002 was jointly organized by the Swiss Federal Institute of Te- nology (ETH) and the IBM Zurich Research Laboratory, and took place in Zurich, Switzerland, October 14-16, 2002. The program committee received 83 submissions, originating from 22 co- tries. For fans of statistics: 55 submissions came from countries in Europe, the Middle East, or Africa, 16 came from Asia, and 12from North America. The leading countries were USA (11 submissions), Germany (9), France (7), Italy (7), Japan (6), and UK (6). Each submission was reviewed by at least three p- gram committee members or other experts. Each submission coauthored by a program committee member received two additional reviews. The program c- mittee chair and cochair were not allowed to submit papers. The ?nal selection of papers was made at a program committee meeting and resulted in 16 accepted papers. In comparison, ESORICS 2000 received 75 submissions and accepted 19 of them. The program re?ects the full range of security research: we accepted papers on access control, authentication, cryptography, database security, formal methods, intrusion detection, mobile code security, privacy, secure hardware, and secure protocols. We gratefully acknowledge all authors who submitted papers for their e?orts in maintaining the standards of this conference.

This book brings together the essential methodologies required to understand the advancement of digital technologies into digital transformation, as well as to protect them against cyber threat vulnerabilities (in this context cybersecurity attack ontology is included, modeling different types of adversary knowledge). It covers such essential methodologies as CIA Triad, Security Risk, Likelihood, and Consequence Level, Threat Attack Profiling, Threat Intelligence, Threat Lifecycle and more. The idea behind digital transformation is to use digital technologies not only to replicate an existing process in a digital form, but to use digital technology to transform that process into something intelligent (where anything is connected with everything at any time and accessible and controlled and designed advanced). Against this background, cyber threat attacks become reality, using advanced digital technologies with their extreme interconnected capability which call for sophisticated cybersecurity protecting digital technologies of digital transformation. Scientists, advanced-level students and researchers working in computer science, electrical engineering and applied mathematics will find this book useful as a reference guide. Professionals working in the field of big data analytics or digital/intelligent manufacturing will also find this book to be a valuable tool.