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Author: Zahir Tari Publisher: John Wiley & Sons ISBN: 1119898870 Category : Computers Languages : en Pages : 292
Book Description
DATA EXFILTRATION THREATS AND PREVENTION TECHNIQUES Comprehensive resource covering threat prevention techniques for data exfiltration and applying machine learning applications to aid in identification and prevention Data Exfiltration Threats and Prevention Techniques provides readers the knowledge needed to prevent and protect from malware attacks by introducing existing and recently developed methods in malware protection using AI, memory forensic, and pattern matching, presenting various data exfiltration attack vectors and advanced memory-based data leakage detection, and discussing ways in which machine learning methods have a positive impact on malware detection. Providing detailed descriptions of the recent advances in data exfiltration detection methods and technologies, the authors also discuss details of data breach countermeasures and attack scenarios to show how the reader may identify a potential cyber attack in the real world. Composed of eight chapters, this book presents a better understanding of the core issues related to the cyber-attacks as well as the recent methods that have been developed in the field. In Data Exfiltration Threats and Prevention Techniques, readers can expect to find detailed information on: Sensitive data classification, covering text pre-processing, supervised text classification, automated text clustering, and other sensitive text detection approaches Supervised machine learning technologies for intrusion detection systems, covering taxonomy and benchmarking of supervised machine learning techniques Behavior-based malware detection using API-call sequences, covering API-call extraction techniques and detecting data stealing behavior based on API-call sequences Memory-based sensitive data monitoring for real-time data exfiltration detection and advanced time delay data exfiltration attack and detection Aimed at professionals and students alike, Data Exfiltration Threats and Prevention Techniques highlights a range of machine learning methods that can be used to detect potential data theft and identifies research gaps and the potential to make change in the future as technology continues to grow.
Author: Zahir Tari Publisher: John Wiley & Sons ISBN: 1119898870 Category : Computers Languages : en Pages : 292
Book Description
DATA EXFILTRATION THREATS AND PREVENTION TECHNIQUES Comprehensive resource covering threat prevention techniques for data exfiltration and applying machine learning applications to aid in identification and prevention Data Exfiltration Threats and Prevention Techniques provides readers the knowledge needed to prevent and protect from malware attacks by introducing existing and recently developed methods in malware protection using AI, memory forensic, and pattern matching, presenting various data exfiltration attack vectors and advanced memory-based data leakage detection, and discussing ways in which machine learning methods have a positive impact on malware detection. Providing detailed descriptions of the recent advances in data exfiltration detection methods and technologies, the authors also discuss details of data breach countermeasures and attack scenarios to show how the reader may identify a potential cyber attack in the real world. Composed of eight chapters, this book presents a better understanding of the core issues related to the cyber-attacks as well as the recent methods that have been developed in the field. In Data Exfiltration Threats and Prevention Techniques, readers can expect to find detailed information on: Sensitive data classification, covering text pre-processing, supervised text classification, automated text clustering, and other sensitive text detection approaches Supervised machine learning technologies for intrusion detection systems, covering taxonomy and benchmarking of supervised machine learning techniques Behavior-based malware detection using API-call sequences, covering API-call extraction techniques and detecting data stealing behavior based on API-call sequences Memory-based sensitive data monitoring for real-time data exfiltration detection and advanced time delay data exfiltration attack and detection Aimed at professionals and students alike, Data Exfiltration Threats and Prevention Techniques highlights a range of machine learning methods that can be used to detect potential data theft and identifies research gaps and the potential to make change in the future as technology continues to grow.
Author: Publisher: ISBN: 9780660480800 Category : Computer security Languages : en Pages : 0
Book Description
"According to National Institute of Standards and Technology (NIST), exfiltration is the unauthorized transfer of data from a network, system, or device. Data exfiltration is a tactic used by threat actors to accomplish their objectives, such as data theft, financial extortion and gain (e.g. ransomware or cultivating insider threats), and service disruption. Data exfiltration attacks occur in various forms, including data espionage, user or system credentials theft, financial data theft, digital identity compromise, and data de-anonymization. To protect against these attacks, your organizations should secure your data lifecycle processes (e.g. creation, operation, and destruction) from end to end. In this document, we discuss some known data exfiltration techniques and propose protection strategies that can be deployed to mitigate the impact from such threats"--Overview.
Author: Nana Essilfie-Conduah (S.M.) Publisher: ISBN: Category : Languages : en Pages : 110
Book Description
It has become common place to hear of data breaches. Typically, we hear of external hackers as the perpetrators, however, the reality is there is a high frequency of threats from insiders within an organization and that the cost and challenge in detecting these threats is considerable. The issue has affected companies in multiple private sectors (finance, retail) and the public sector is also at risk as apparent with the Edward Snowden and Chelsea Manning cases. This thesis explores the current space of insider threats in terms of frequency, cost and complexity in attack assessment. It also explores the multiple perspectives and stakeholders that make up the complex insider threat systems. Insights from multiple insider threat cases as well as subject matter experts in cyber security were used to model and pinpoint the high value metrics around access management and logging that will aid audit efforts. Following this an exploration of kill chains, blockchain technology and hierarchical organization exploration is made. Research findings highlight the wide reach of excessive privileges and the crucial role resource access and event logging of stakeholder actions plays in the success of insider threat prevention. In response to this finding a proposal is made for a combined solution that aims to provide an easy and accessible interface for searching and requesting access to resources that scales with an organization. This proposal suggests the capitalization of the transparent and immutable properties of blockchain to ledger the requesting and approval of file access through dynamic and multi user approval logic. The solution combines simplistic file-based resource access in an accessible manner with a multi layered security approach that adds further hurdles for bad actors but provides a visible and reliable look back on an immutable audit path.
Author: Ryan Van Antwerp Publisher: ISBN: Category : Data protection Languages : en Pages :
Book Description
Data exfiltration is the process of transmitting data from an infected or attacker-controlled machine back to the attacker while attempting to minimize detection. In current attack scenarios, an attacker will attempt to break into a network, achieve control of a target machine and steal sensitive data. Current network defense mechanisms are largely implemented to prevent attackers from entering a network, however there are typically few defenses implemented which prevent sensitive data from leaving a network. In addition, a major obstacle is the inability of researchers to know exactly how data will be exfiltrated from a machine. Currently, detection suites focus on attributes of the sensitive data being stolen such as file names and keywords. However, simple modification by the attacker of the data or the exfiltration channel can bypass these defense mechanisms. In order to better understand how to defend against this type of activity, the attack surface must be examined. In this research, we examine the attack surface of data exfiltration by characterizing different exfiltration methods and observing common characteristics between them. By exploring the taxonomy of exfiltration techniques, we hope to help the research community improve existing detection algorithms and identify patterns that can be used to create new detection algorithms. After examining each method, a test bench suite was designed and implemented which emulates the data exfiltration process. This plug-in based framework allows a researcher to test common exfiltration methods on any given data. The framework is also extendable in that plug-ins can be quickly implemented using a wide array of existing libraries. The results from this research show that there is a set of common characteristics among all methods that can be used to help further research of detection algorithms. Features such as exfiltration timing, destination determination and traffic symmetry can be used to construct a stronger detection suite.
Author: Elisa Bertino Publisher: Morgan & Claypool Publishers ISBN: 1608457699 Category : Computers Languages : en Pages : 93
Book Description
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
Author: Andrew Coburn Publisher: John Wiley & Sons ISBN: 111949091X Category : Business & Economics Languages : en Pages : 384
Book Description
The non-technical handbook for cyber security risk management Solving Cyber Risk distills a decade of research into a practical framework for cyber security. Blending statistical data and cost information with research into the culture, psychology, and business models of the hacker community, this book provides business executives, policy-makers, and individuals with a deeper understanding of existing future threats, and an action plan for safeguarding their organizations. Key Risk Indicators reveal vulnerabilities based on organization type, IT infrastructure and existing security measures, while expert discussion from leading cyber risk specialists details practical, real-world methods of risk reduction and mitigation. By the nature of the business, your organization’s customer database is packed with highly sensitive information that is essentially hacker-bait, and even a minor flaw in security protocol could spell disaster. This book takes you deep into the cyber threat landscape to show you how to keep your data secure. Understand who is carrying out cyber-attacks, and why Identify your organization’s risk of attack and vulnerability to damage Learn the most cost-effective risk reduction measures Adopt a new cyber risk assessment and quantification framework based on techniques used by the insurance industry By applying risk management principles to cyber security, non-technical leadership gains a greater understanding of the types of threat, level of threat, and level of investment needed to fortify the organization against attack. Just because you have not been hit does not mean your data is safe, and hackers rely on their targets’ complacence to help maximize their haul. Solving Cyber Risk gives you a concrete action plan for implementing top-notch preventative measures before you’re forced to implement damage control.
Author: Publisher: ISBN: Category : Languages : en Pages :
Book Description
Unauthorized data exfiltrations from both insiders and outsiders are costly and damaging. Network communication resources can be used for transporting data illicitly out of the enterprise or cloud. Combined with built-in malware copying utilities, we define this as comprising the Data Exfiltration Surface (DXS). For securing valuable data, it is desirable to reduce the DXS and maintain controls on the egress points. Our approach is to host the data in a protected enclave that includes novel software Data Diode (SDD) installed on a secured, border gateway. The SDD allows copying data into the enclave systems but denies data from being copied out. Simultaneously, it permits remote access with remote desktop and console applications. Our tests demonstrate that we are able to effectively reduce the DXS and we are able to protect data from being exfiltrated through the use of the SDD.
Author: Tarun Kumar Chawdhury Publisher: BPB Publications ISBN: 9355518846 Category : Computers Languages : en Pages : 376
Book Description
Elevate your Java security skills for the modern cloud era KEY FEATURES ● Understanding Zero-Trust security model for Java. ● Practical cloud security strategies for developers. ● Hands-on guidance for secure Java application development. DESCRIPTION This book offers a comprehensive guide to implementing Zero-Trust security principles, cloud-based defenses, and robust application development practices. Through practical examples and expert advice, readers will gain the skills needed to design and develop secure Java applications that easily can tackle today's cyber threats. It builds focus on securing your source code through analysis, vulnerability detection, and automation. It also ensures the safety of your runtime environment for managing traffic and enables multi-factor authentication. While addressing data security concerns with encryption, anonymization, and cloud-based solutions, it also uses tools like OpenTelemetry for real-time threat detection. It manages sensitive information securely with Vault integration and explores passwordless authentication. Reference architectures, secure coding patterns, and automation practices are also provided to aid implementation. By the end of this book, you'll be well-equipped to build secure Java applications with confidence and deliver applications that are robust, reliable, and compliant. WHAT YOU WILL LEARN ● Implement Zero-Trust principles in Java applications. ● Secure Java apps in cloud environments like AWS, GCP, and Azure. ● Develop applications with security best practices from the ground up. ● Understand and mitigate common security vulnerabilities in Java. ● Apply modern security tools and techniques in Java development. WHO THIS BOOK IS FOR This book is ideal for Java developers and software architects seeking to enhance their security expertise, particularly in cloud environments. TABLE OF CONTENTS 1. Secure Design Principles for Java Applications 2. Analyzing and Securing Source Code 3. Securing Java Runtime 4. Application Data Security 5. Application Observability and Threat Protection 6. Integration with Vault 7. Established Solution Architecture and Patterns 8. Real-world Case Studies and Solutions 9. Java Software Licensing Model 10. Secure Coding Tips and Practices
Author: Zahir Tari
Author: Zahir Tari
Author: 
Author: Nana Essilfie-Conduah (S.M.)
Author: Ryan Van Antwerp
Author: 
Author: Elisa Bertino
Author: Andrew Coburn
Author: 
Author: Sanjay Goel
Author: Tarun Kumar Chawdhury