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Mitigating The Insider Threat With High Dimensional Anomaly Detection
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Book Synopsis Mitigating the Insider Threat with High-Dimensional Anomaly Detection by :
Download or read book Mitigating the Insider Threat with High-Dimensional Anomaly Detection written by and published by . This book was released on 2004 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this project, we explored new techniques for detecting the threat of insider attacks in enterprise networks. In particular, we explored the use of high-dimensional search techniques such as Latent Semantic Indexing to mitigate the problem of high dimensionality that is inherent in intrusion detection. This new technique can be used for both labeled and unlabeled detection, and shows promise for detecting attacks and anomalies earlier than previously possible and detecting attacks that are similar to past ones.
Book Synopsis Mitigating the Insider Threat Using High-Dimensional Search and Modeling by :
Download or read book Mitigating the Insider Threat Using High-Dimensional Search and Modeling written by and published by . This book was released on 2006 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this project a system was built aimed at mitigating insider attacks centered around a high-dimensional search engine for correlating the large number of monitoring streams necessary for detecting insider attacks. Further accomplishments in this project include an insider attack modeling and analysis tool called MAPIT, developed by SUNY Buffalo, and a novel sketch-based anomaly detection sensor developed by Rutgers University, which can be used for detecting anomalies in IP source/destination addresses, as well as for defining small-space user profiles, e.g., file accesses.
Book Synopsis Anomaly Detection as a Service by : Danfeng (Daphne)Yao
Download or read book Anomaly Detection as a Service written by Danfeng (Daphne)Yao and published by Springer Nature. This book was released on 2022-06-01 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: Anomaly detection has been a long-standing security approach with versatile applications, ranging from securing server programs in critical environments, to detecting insider threats in enterprises, to anti-abuse detection for online social networks. Despite the seemingly diverse application domains, anomaly detection solutions share similar technical challenges, such as how to accurately recognize various normal patterns, how to reduce false alarms, how to adapt to concept drifts, and how to minimize performance impact. They also share similar detection approaches and evaluation methods, such as feature extraction, dimension reduction, and experimental evaluation. The main purpose of this book is to help advance the real-world adoption and deployment anomaly detection technologies, by systematizing the body of existing knowledge on anomaly detection. This book is focused on data-driven anomaly detection for software, systems, and networks against advanced exploits and attacks, but also touches on a number of applications, including fraud detection and insider threats. We explain the key technical components in anomaly detection workflows, give in-depth description of the state-of-the-art data-driven anomaly-based security solutions, and more importantly, point out promising new research directions. This book emphasizes on the need and challenges for deploying service-oriented anomaly detection in practice, where clients can outsource the detection to dedicated security providers and enjoy the protection without tending to the intricate details.
Book Synopsis Data Protection from Insider Threats by : Elisa Bertino
Download or read book Data Protection from Insider Threats written by Elisa Bertino and published by Morgan & Claypool Publishers. This book was released on 2012-06-01 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt: As data represent a key asset for today's organizations, the problem of how to protect this data from theft and misuse is at the forefront of these organizations' minds. Even though today several data security techniques are available to protect data and computing infrastructures, many such techniques -- such as firewalls and network security tools -- are unable to protect data from attacks posed by those working on an organization's "inside." These "insiders" usually have authorized access to relevant information systems, making it extremely challenging to block the misuse of information while still allowing them to do their jobs. This book discusses several techniques that can provide effective protection against attacks posed by people working on the inside of an organization. Chapter One introduces the notion of insider threat and reports some data about data breaches due to insider threats. Chapter Two covers authentication and access control techniques, and Chapter Three shows how these general security techniques can be extended and used in the context of protection from insider threats. Chapter Four addresses anomaly detection techniques that are used to determine anomalies in data accesses by insiders. These anomalies are often indicative of potential insider data attacks and therefore play an important role in protection from these attacks. Security information and event management (SIEM) tools and fine-grained auditing are discussed in Chapter Five. These tools aim at collecting, analyzing, and correlating -- in real-time -- any information and event that may be relevant for the security of an organization. As such, they can be a key element in finding a solution to such undesirable insider threats. Chapter Six goes on to provide a survey of techniques for separation-of-duty (SoD). SoD is an important principle that, when implemented in systems and tools, can strengthen data protection from malicious insiders. However, to date, very few approaches have been proposed for implementing SoD in systems. In Chapter Seven, a short survey of a commercial product is presented, which provides different techniques for protection from malicious users with system privileges -- such as a DBA in database management systems. Finally, in Chapter Eight, the book concludes with a few remarks and additional research directions. Table of Contents: Introduction / Authentication / Access Control / Anomaly Detection / Security Information and Event Management and Auditing / Separation of Duty / Case Study: Oracle Database Vault / Conclusion
Book Synopsis Machine Learning Based Framework for User-Centered Insider Threat Detection by : Duc Le
Download or read book Machine Learning Based Framework for User-Centered Insider Threat Detection written by Duc Le and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Insider threat represents a major cyber-security challenge to companies, organizations, and government agencies. Harmful actions in insider threats are performed by authorized users in organizations. Due to the fact that an insider is authorized to access the organization's computer systems and has knowledge about the organization's security procedures, detecting insider threats is challenging. Many other challenges exist in this detection problem, including unbalanced data, limited ground truth, and possible user behaviour changes. This research proposes a comprehensive machine learning-based framework for insider threat detection, from data pre-processing, a combination of supervised and unsupervised learning, to deep analysis and meaningful result reporting. For the data pre-processing step, the framework introduces a data extraction approach allowing extraction of numerical feature vectors representing user activities from heterogeneous data, with different data granularity levels and temporal data representations, and enabling applications of machine learning. In the initial detection step of the framework, assume no available ground truth, unsupervised learning methods with different working principles and unsupervised ensembles are explored for anomaly detection to identify anomalous user behaviours that may indicate insider threats. Furthermore, the framework employs supervised and semi-supervised machine learning under limited ground truth availability and real-world conditions to maximize the effectiveness of limited training data and detect insider threats with high precision. Throughout the thesis, realistic evaluation and comprehensive result reporting are performed to facilitate understanding of the framework's performance under real-world conditions. Evaluation results on publicly available datasets show the effectiveness of the proposed approach. High insider threat detection rates are achieved at very low false positive rates. The robustness of the detection models is also demonstrated and comparisons with the state-of-the-art confirm the advantages of the approach.
Book Synopsis Machine Learning and Anomaly Detection for Insider Threat Detection by : Filip Wieslaw Bartoszewski
Download or read book Machine Learning and Anomaly Detection for Insider Threat Detection written by Filip Wieslaw Bartoszewski and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Mitigating Insider Threat Using Human Behavior Influence Models by : Anthony J. Puleo
Download or read book Mitigating Insider Threat Using Human Behavior Influence Models written by Anthony J. Puleo and published by . This book was released on 2006 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Anomaly Detection in Multiple Scale for Insider Threat Analysis by :
Download or read book Anomaly Detection in Multiple Scale for Insider Threat Analysis written by and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a method to quantify malicious insider activity with statistical and graph-based analysis aided with semantic scoring rules. Different types of personal activities or interactions are monitored to form a set of directed weighted graphs. The semantic scoring rules assign higher scores for the events more significant and suspicious. Then we build personal activity profiles in the form of score tables. Profiles are created in multiple scales where the low level profiles are aggregated toward more stable higherlevel profiles within the subject or object hierarchy. Further, the profiles are created in different time scales such as day, week, or month. During operation, the insider s current activity profile is compared to the historical profiles to produce an anomaly score. For each subject with a high anomaly score, a subgraph of connected subjects is extracted to look for any related score movement. Finally the subjects are ranked by their anomaly scores to help the analysts focus on high-scored subjects. The threat-ranking component supports the interaction between the User Dashboard and the Insider Threat Knowledge Base portal. The portal includes a repository for historical results, i.e., adjudicated cases containing all of the information first presented to the user and including any additional insights to help the analysts. In this paper we show the framework of the proposed system and the operational algorithms.
Book Synopsis Detection and Mitigation of Insider Attacks in a Cloud Infrastructure: Emerging Research and Opportunities by : Gunasekhar, T.
Download or read book Detection and Mitigation of Insider Attacks in a Cloud Infrastructure: Emerging Research and Opportunities written by Gunasekhar, T. and published by IGI Global. This book was released on 2019-02-15 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: Businesses constantly face online hacking threats or security breaches in their online mainframe that expose sensitive information to the wrong audience. Companies look to store their data in a separate location, distancing the availability of the information and reducing the risk of data breaches. Modern organizations need to remain vigilant against insider attacks, cloud computing risks, and security flaws within their mainframe. Detection and Mitigation of Insider Attacks in a Cloud Infrastructure: Emerging Research and Opportunities is an essential reference source that discusses maintaining a secure management of sensitive data, and intellectual property and provides a robust security algorithm on consumer data. Featuring research on topics such as public cryptography, security principles, and trustworthy computing, this book is ideally designed for IT professionals, business managers, researchers, students, and professionals seeking coverage on preventing and detecting the insider attacks using trusted cloud computing techniques.
Book Synopsis The CERT Guide to Insider Threats by : Dawn M. Cappelli
Download or read book The CERT Guide to Insider Threats written by Dawn M. Cappelli and published by Addison-Wesley. This book was released on 2012-01-20 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since 2001, the CERT® Insider Threat Center at Carnegie Mellon University’s Software Engineering Institute (SEI) has collected and analyzed information about more than seven hundred insider cyber crimes, ranging from national security espionage to theft of trade secrets. The CERT® Guide to Insider Threats describes CERT’s findings in practical terms, offering specific guidance and countermeasures that can be immediately applied by executives, managers, security officers, and operational staff within any private, government, or military organization. The authors systematically address attacks by all types of malicious insiders, including current and former employees, contractors, business partners, outsourcers, and even cloud-computing vendors. They cover all major types of insider cyber crime: IT sabotage, intellectual property theft, and fraud. For each, they present a crime profile describing how the crime tends to evolve over time, as well as motivations, attack methods, organizational issues, and precursor warnings that could have helped the organization prevent the incident or detect it earlier. Beyond identifying crucial patterns of suspicious behavior, the authors present concrete defensive measures for protecting both systems and data. This book also conveys the big picture of the insider threat problem over time: the complex interactions and unintended consequences of existing policies, practices, technology, insider mindsets, and organizational culture. Most important, it offers actionable recommendations for the entire organization, from executive management and board members to IT, data owners, HR, and legal departments. With this book, you will find out how to Identify hidden signs of insider IT sabotage, theft of sensitive information, and fraud Recognize insider threats throughout the software development life cycle Use advanced threat controls to resist attacks by both technical and nontechnical insiders Increase the effectiveness of existing technical security tools by enhancing rules, configurations, and associated business processes Prepare for unusual insider attacks, including attacks linked to organized crime or the Internet underground By implementing this book’s security practices, you will be incorporating protection mechanisms designed to resist the vast majority of malicious insider attacks.
Book Synopsis Long Term, Low Amplitude Anomaly Detection Method for Detecting Insider Threat by : Idan Morad
Download or read book Long Term, Low Amplitude Anomaly Detection Method for Detecting Insider Threat written by Idan Morad and published by . This book was released on 2015 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Insider Threat by : Michael G. Gelles
Download or read book Insider Threat written by Michael G. Gelles and published by Butterworth-Heinemann. This book was released on 2016-05-27 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Insider Threat: Detection, Mitigation, Deterrence and Prevention presents a set of solutions to address the increase in cases of insider threat. This includes espionage, embezzlement, sabotage, fraud, intellectual property theft, and research and development theft from current or former employees. This book outlines a step-by-step path for developing an insider threat program within any organization, focusing on management and employee engagement, as well as ethical, legal, and privacy concerns. In addition, it includes tactics on how to collect, correlate, and visualize potential risk indicators into a seamless system for protecting an organization's critical assets from malicious, complacent, and ignorant insiders. Insider Threat presents robust mitigation strategies that will interrupt the forward motion of a potential insider who intends to do harm to a company or its employees, as well as an understanding of supply chain risk and cyber security, as they relate to insider threat.
Book Synopsis A Multi-Modal Insider Threat Detection and Prevention Based on User's Behaviors by : Yassir Hashem
Download or read book A Multi-Modal Insider Threat Detection and Prevention Based on User's Behaviors written by Yassir Hashem and published by . This book was released on 2018 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: Insider threat is one of the greatest concerns for information security that could cause more significant financial losses and damages than any other attack. However, implementing an efficient detection system is a very challenging task. It has long been recognized that solutions to insider threats are mainly user-centric and several psychological and psychosocial models have been proposed. A user's psychophysiological behavior measures can provide an excellent source of information for detecting user's malicious behaviors and mitigating insider threats. In this dissertation, we propose a multi-modal framework based on the user's psychophysiological measures and computer-based behaviors to distinguish between a user's behaviors during regular activities versus malicious activities. We utilize several psychophysiological measures such as electroencephalogram (EEG), electrocardiogram (ECG), and eye movement and pupil behaviors along with the computer-based behaviors such as the mouse movement dynamics, and keystrokes dynamics to build our framework for detecting malicious insiders. We conduct human subject experiments to capture the psychophysiological measures and the computer-based behaviors for a group of participants while performing several computer-based activities in different scenarios. We analyze the behavioral measures, extract useful features, and evaluate their capability in detecting insider threats. We investigate each measure separately, then we use data fusion techniques to build two modules and a comprehensive multi-modal framework. The first module combines the synchronized EEG and ECG psychophysiological measures, and the second module combines the eye movement and pupil behaviors with the computer-based behaviors to detect the malicious insiders. The multi-modal framework utilizes all the measures and behaviors in one model to achieve better detection accuracy. Our findings demonstrate that psychophysiological measures can reveal valuable knowledge about a user's malicious intent and can be used as an effective indicator in designing insider threat monitoring and detection frameworks. Our work lays out the necessary foundation to establish a new generation of insider threat detection and mitigation mechanisms that are based on a user's involuntary behaviors, such as psychophysiological measures, and learn from the real-time data to determine whether a user is malicious.
Book Synopsis Insider Attack and Cyber Security by : Salvatore J. Stolfo
Download or read book Insider Attack and Cyber Security written by Salvatore J. Stolfo and published by Springer Science & Business Media. This book was released on 2008-08-29 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book defines the nature and scope of insider problems as viewed by the financial industry. This edited volume is based on the first workshop on Insider Attack and Cyber Security, IACS 2007. The workshop was a joint effort from the Information Security Departments of Columbia University and Dartmouth College. The book sets an agenda for an ongoing research initiative to solve one of the most vexing problems encountered in security, and a range of topics from critical IT infrastructure to insider threats. In some ways, the insider problem is the ultimate security problem.
Book Synopsis Alleviating Insider Threats: Mitigation Strategies and Detection Techniques by : Jeffrey Lyne Jenkins
Download or read book Alleviating Insider Threats: Mitigation Strategies and Detection Techniques written by Jeffrey Lyne Jenkins and published by . This book was released on 2013 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Insider threats--trusted members of an organization who compromise security--are considered the greatest security threat to organizations. Because of ignorance, negligence, or malicious intent, insider threats may cause security breaches resulting in substantial damages to organizations and even society. This research helps alleviate the insider threat through developing mitigation strategies and detection techniques in three studies. Study 1 examines how security controls--specifically depth-of-authentication and training recency--alleviate non-malicious insider threats through encouraging secure behavior (i.e., compliance with an organization's security policy). I found that 'simpler is better' when implementing security controls, the effects of training diminish rapidly, and intentions are poor predictors of actual secure behavior. Extending Study 1's finding on training recency, Study 2 explains how different types of training alleviate non-malicious insider threat activities. I found that just-in-time reminders are more effective than traditional training programs in improving secure behavior, and again that intentions are not an adequate predictor of actual secure behavior. Both Study 1 and Study 2 introduce effective mitigation strategies for alleviating the non-malicious insider threat; however, they have limited utility when an insider threat has malicious intention, or deliberate intentions to damage the organization. To address this limitation, Study 3 conducts research to develop a tool for detecting malicious insider threats. The tool monitors mouse movements during an insider threat screening survey to detect when respondents are being deceptive. I found that mouse movements are diagnostic of deception. Future research directions are discussed to integrate and extend the findings presented in this dissertation to develop a behavioral information security framework for alleviating both the non-malicious and malicious insider threats in organizations.
Book Synopsis Practical Applications of Data Processing, Algorithms, and Modeling by : Whig, Pawan
Download or read book Practical Applications of Data Processing, Algorithms, and Modeling written by Whig, Pawan and published by IGI Global. This book was released on 2024-04-29 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today's data-driven era, the persistent gap between theoretical understanding and practical implementation in data science poses a formidable challenge. As we navigate through the complexities of harnessing data, deciphering algorithms, and unleashing the potential of modeling techniques, the need for a comprehensive guide becomes increasingly evident. This is the landscape explored in Practical Applications of Data Processing, Algorithms, and Modeling. This book is a solution to the pervasive problem faced by aspiring data scientists, seasoned professionals, and anyone fascinated by the power of data-driven insights. From the web of algorithms to the strategic role of modeling in decision-making, this book is an effective resource in a landscape where data, without proper guidance, risks becoming an untapped resource. The objective of Practical Applications of Data Processing, Algorithms, and Modeling is to address the pressing issue at the heart of data science – the divide between theory and practice. This book seeks to examine the complexities of data processing techniques, algorithms, and modeling methodologies, offering a practical understanding of these concepts. By focusing on real-world applications, the book provides readers with the tools and knowledge needed to bridge the gap effectively, allowing them to apply these techniques across diverse industries and domains. In the face of constant technological advancements, the book highlights the latest trends and innovative approaches, fostering a deeper comprehension of how these technologies can be leveraged to solve complex problems. As a practical guide, it empowers readers with hands-on examples, case studies, and problem-solving scenarios, aiming to instill confidence in navigating data challenges and making informed decisions using data-driven insights.
Book Synopsis Insider Threats in Cyber Security by : Christian W. Probst
Download or read book Insider Threats in Cyber Security written by Christian W. Probst and published by Springer Science & Business Media. This book was released on 2010-07-28 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Insider Threats in Cyber Security is a cutting edge text presenting IT and non-IT facets of insider threats together. This volume brings together a critical mass of well-established worldwide researchers, and provides a unique multidisciplinary overview. Monica van Huystee, Senior Policy Advisor at MCI, Ontario, Canada comments "The book will be a must read, so of course I’ll need a copy." Insider Threats in Cyber Security covers all aspects of insider threats, from motivation to mitigation. It includes how to monitor insider threats (and what to monitor for), how to mitigate insider threats, and related topics and case studies. Insider Threats in Cyber Security is intended for a professional audience composed of the military, government policy makers and banking; financing companies focusing on the Secure Cyberspace industry. This book is also suitable for advanced-level students and researchers in computer science as a secondary text or reference book.
