Forensic Evidence Identification and Modeling for Attacks against a Simulated Online Business Information System

Forensic readiness of business information systems can support future forensics investigation or auditing on external/internal attacks, internal sabotage and espionage, and business fraud. To establish forensics readiness, it is essential for an organization to identify which fingerprints are relevant and where they can be located, to determine whether they are logged in a forensically sound way and whether all the needed fingerprints are available to reconstruct the events successfully. Also, a fingerprint identification and locating mechanism should be provided to guide potential forensics investigation in the future. Furthermore, mechanisms should be established to automate the security incident tracking and reconstruction processes. In this research, external and internal attacks are first modeled as augmented attack trees based on the vulnerabilities of business information systems. Then, modeled attacks are conducted against a honeynet that simulates an online business information system, and a forensic investigation follows each attack. Finally, an evidence tree, which is expected to provide the necessary contextual information to automate the attack tracking and reconstruction process in the future, is built for each attack based on fingerprints identified and located within the system

PRECEPT:a framework for ethical digital forensics investigations

Purpose: Cyber-enabled crimes are on the increase, and law enforcement has had to expand many of their detecting activities into the digital domain. As such, the field of digital forensics has become far more sophisticated over the years and is now able to uncover even more evidence that can be used to support prosecution of cyber criminals in a court of law. Governments, too, have embraced the ability to track suspicious individuals in the online world. Forensics investigators are driven to gather data exhaustively, being under pressure to provide law enforcement with sufficient evidence to secure a conviction. Yet, there are concerns about the ethics and justice of untrammeled investigations on a number of levels. On an organizational level, unconstrained investigations could interfere with, and damage, the organization’s right to control the disclosure of their intellectual capital. On an individual level, those being investigated could easily have their legal privacy rights violated by forensics investigations. On a societal level, there might be a sense of injustice at the perceived inequality of current practice in this domain. This paper argues the need for a practical, ethically-grounded approach to digital forensic investigations, one that acknowledges and respects the privacy rights of individuals and the intellectual capital disclosure rights of organisations, as well as acknowledging the needs of law enforcement. We derive a set of ethical guidelines, then map these onto a forensics investigation framework. We subjected the framework to expert review in two stages, refining the framework after each stage. We conclude by proposing the refined ethically-grounded digital forensics investigation framework. Our treatise is primarily UK based, but the concepts presented here have international relevance and applicability.Design methodology: In this paper, the lens of justice theory is used to explore the tension that exists between the needs of digital forensic investigations into cybercrimes on the one hand, and, on the other, individuals’ rights to privacy and organizations’ rights to control intellectual capital disclosure.Findings: The investigation revealed a potential inequality between the practices of digital forensics investigators and the rights of other stakeholders. That being so, the need for a more ethically-informed approach to digital forensics investigations, as a remedy, is highlighted, and a framework proposed to provide this.Practical Implications: Our proposed ethically-informed framework for guiding digital forensics investigations suggest a way of re-establishing the equality of the stakeholders in this arena, and ensuring that the potential for a sense of injustice is reduced.Originality/value: Justice theory is used to highlight the difficulties in squaring the circle between the rights and expectations of all stakeholders in the digital forensics arena. The outcome is the forensics investigation guideline, PRECEpt: Privacy-Respecting EthiCal framEwork, which provides the basis for a re-aligning of the balance between the requirements and expectations of digital forensic investigators on the one hand, and individual and organizational expectations and rights, on the other

PRECEPT: A Framework for Ethical Digital Forensics Investigations.

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Cyber-enabled crimes are on the increase, and law enforcement has had to expand many of their detecting activities into the digital domain. As such, the field of digital forensics has become far more sophisticated over the years and is now able to uncover even more evidence that can be used to support prosecution of cyber criminals in a court of law. Governments, too, have embraced the ability to track suspicious individuals in the online world. Forensics investigators are driven to gather data exhaustively, being under pressure to provide law enforcement with sufficient evidence to secure a conviction. Yet, there are concerns about the ethics and justice of untrammeled investigations on a number of levels. On an organizational level, unconstrained investigations could interfere with, and damage, the organization’s right to control the disclosure of their intellectual capital. On an individual level, those being investigated could easily have their legal privacy rights violated by forensics investigations. On a societal level, there might be a sense of injustice at the perceived inequality of current practice in this domain. This paper argues the need for a practical, ethically-grounded approach to digital forensic investigations, one that acknowledges and respects the privacy rights of individuals and the intellectual capital disclosure rights of organisations, as well as acknowledging the needs of law enforcement. We derive a set of ethical guidelines, then map these onto a forensics investigation framework. We subjected the framework to expert review in two stages, refining the framework after each stage. We conclude by proposing the refined ethically-grounded digital forensics investigation framework. Our treatise is primarily UK based, but the concepts presented here have international relevance and applicability. In this paper, the lens of justice theory is used to explore the tension that exists between the needs of digital forensic investigations into cybercrimes on the one hand, and, on the other, individuals’ rights to privacy and organizations’ rights to control intellectual capital disclosure. The investigation revealed a potential inequality between the practices of digital forensics investigators and the rights of other stakeholders. That being so, the need for a more ethically-informed approach to digital forensics investigations, as a remedy, is highlighted, and a framework proposed to provide this. Our proposed ethically-informed framework for guiding digital forensics investigations suggest a way of re-establishing the equality of the stakeholders in this arena, and ensuring that the potential for a sense of injustice is reduced. Justice theory is used to highlight the difficulties in squaring the circle between the rights and expectations of all stakeholders in the digital forensics arena. The outcome is the forensics investigation guideline, PRECEpt: Privacy-Respecting EthiCal framEwork, which provides the basis for a re-aligning of the balance between the requirements and expectations of digital forensic investigators on the one hand, and individual and organizational expectations and rights, on the other

Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

Customization and automation in the future of digital forensics: live OS forensics with FENIX (forensic examiner unix)

FENIX (Forensic Examiner uNIX) is a Linux based live OS (Operating System) created to be used in remote environments for incident response and digital forensics. Between a joint effort between the Center for Information Protection (CIP) and the Iowa State University Police Department (ISUPD), FENIX has been tailored to suit the needs and requests of law enforcement forensic specialists. The very basis for FENIX is to allow ISU police officers the ability to carry an easy to operate and customize forensic toolkit with them at the scene of a crime allowing for better acquisitions and a deeper analysis to be conducted in an investigation. FENIX isn\u27t a standard forensic toolkit as others are. FENIX is a custom build of the Linux kernel with several of its own applications created for specific OS and forensic purposes and designed for a user friendly interface. However, since most users will be more familiar with existing tools those tools have the ability to interface easily with FENIX

Análise de malware com suporte de hardware

Orientadores: Paulo Lício de Geus, André Ricardo Abed GrégioDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: O mundo atual é impulsionado pelo uso de sistemas computacionais, estando estes pre- sentes em todos aspectos da vida cotidiana. Portanto, o correto funcionamento destes é essencial para se assegurar a manutenção das possibilidades trazidas pelos desenvolvi- mentos tecnológicos. Contudo, garantir o correto funcionamento destes não é uma tarefa fácil, dado que indivíduos mal-intencionados tentam constantemente subvertê-los visando benefíciar a si próprios ou a terceiros. Os tipos mais comuns de subversão são os ataques por códigos maliciosos (malware), capazes de dar a um atacante controle total sobre uma máquina. O combate à ameaça trazida por malware baseia-se na análise dos artefatos coletados de forma a permitir resposta aos incidentes ocorridos e o desenvolvimento de contramedidas futuras. No entanto, atacantes têm se especializado em burlar sistemas de análise e assim manter suas operações ativas. Para este propósito, faz-se uso de uma série de técnicas denominadas de "anti-análise", capazes de impedir a inspeção direta dos códigos maliciosos. Dentre essas técnicas, destaca-se a evasão do processo de análise, na qual são empregadas exemplares capazes de detectar a presença de um sistema de análise para então esconder seu comportamento malicioso. Exemplares evasivos têm sido cada vez mais utilizados em ataques e seu impacto sobre a segurança de sistemas é considerá- vel, dado que análises antes feitas de forma automática passaram a exigir a supervisão de analistas humanos em busca de sinais de evasão, aumentando assim o custo de se manter um sistema protegido. As formas mais comuns de detecção de um ambiente de análise se dão através da detecção de: (i) código injetado, usado pelo analista para inspecionar a aplicação; (ii) máquinas virtuais, usadas em ambientes de análise por questões de escala; (iii) efeitos colaterais de execução, geralmente causados por emuladores, também usados por analistas. Para lidar com malware evasivo, analistas tem se valido de técnicas ditas transparentes, isto é, que não requerem injeção de código nem causam efeitos colaterais de execução. Um modo de se obter transparência em um processo de análise é contar com suporte do hardware. Desta forma, este trabalho versa sobre a aplicação do suporte de hardware para fins de análise de ameaças evasivas. No decorrer deste texto, apresenta-se uma avaliação das tecnologias existentes de suporte de hardware, dentre as quais máqui- nas virtuais de hardware, suporte de BIOS e monitores de performance. A avaliação crítica de tais tecnologias oferece uma base de comparação entre diferentes casos de uso. Além disso, são enumeradas lacunas de desenvolvimento existentes atualmente. Mais que isso, uma destas lacunas é preenchida neste trabalho pela proposição da expansão do uso dos monitores de performance para fins de monitoração de malware. Mais especificamente, é proposto o uso do monitor BTS para fins de construção de um tracer e um debugger. O framework proposto e desenvolvido neste trabalho é capaz, ainda, de lidar com ataques do tipo ROP, um dos mais utilizados atualmente para exploração de vulnerabilidades. A avaliação da solução demonstra que não há a introdução de efeitos colaterais, o que per- mite análises de forma transparente. Beneficiando-se desta característica, demonstramos a análise de aplicações protegidas e a identificação de técnicas de evasãoAbstract: Today¿s world is driven by the usage of computer systems, which are present in all aspects of everyday life. Therefore, the correct working of these systems is essential to ensure the maintenance of the possibilities brought about by technological developments. However, ensuring the correct working of such systems is not an easy task, as many people attempt to subvert systems working for their own benefit. The most common kind of subversion against computer systems are malware attacks, which can make an attacker to gain com- plete machine control. The fight against this kind of threat is based on analysis procedures of the collected malicious artifacts, allowing the incident response and the development of future countermeasures. However, attackers have specialized in circumventing analysis systems and thus keeping their operations active. For this purpose, they employ a series of techniques called anti-analysis, able to prevent the inspection of their malicious codes. Among these techniques, I highlight the analysis procedure evasion, that is, the usage of samples able to detect the presence of an analysis solution and then hide their malicious behavior. Evasive examples have become popular, and their impact on systems security is considerable, since automatic analysis now requires human supervision in order to find evasion signs, which significantly raises the cost of maintaining a protected system. The most common ways for detecting an analysis environment are: i) Injected code detec- tion, since injection is used by analysts to inspect applications on their way; ii) Virtual machine detection, since they are used in analysis environments due to scalability issues; iii) Execution side effects detection, usually caused by emulators, also used by analysts. To handle evasive malware, analysts have relied on the so-called transparent techniques, that is, those which do not require code injection nor cause execution side effects. A way to achieve transparency in an analysis process is to rely on hardware support. In this way, this work covers the application of the hardware support for the evasive threats analysis purpose. In the course of this text, I present an assessment of existing hardware support technologies, including hardware virtual machines, BIOS support, performance monitors and PCI cards. My critical evaluation of such technologies provides basis for comparing different usage cases. In addition, I pinpoint development gaps that currently exists. More than that, I fill one of these gaps by proposing to expand the usage of performance monitors for malware monitoring purposes. More specifically, I propose the usage of the BTS monitor for the purpose of developing a tracer and a debugger. The proposed framework is also able of dealing with ROP attacks, one of the most common used technique for remote vulnerability exploitation. The framework evaluation shows no side-effect is introduced, thus allowing transparent analysis. Making use of this capability, I demonstrate how protected applications can be inspected and how evasion techniques can be identifiedMestradoCiência da ComputaçãoMestre em Ciência da ComputaçãoCAPE

PrivExtractor:Towards Redressing the Imbalance of Understanding Between Virtual Assistant Users and Vendors

The use of voice-controlled virtual assistants (VAs) is significant, and user numbers increase every year. Extensive use of VAs has provided the large, cash-rich technology companies who sell them with another way of consuming users' data, providing a lucrative revenue stream. Whilst these companies are legally obliged to treat users' information "fairly and responsibly,"artificial intelligence techniques used to process data have become incredibly sophisticated, leading to users' concerns that a lack of clarity is making it hard to understand the nature and scope of data collection and use.There has been little work undertaken on a self-contained user awareness tool targeting VAs. PrivExtractor, a novel web-based awareness dashboard for VA users, intends to redress this imbalance of understanding between the data "processors"and the user. It aims to achieve this using the four largest VA vendors as a case study and providing a comparison function that examines the four companies' privacy practices and their compliance with data protection law.As a result of this research, we conclude that the companies studied are largely compliant with the law, as expected. However, the user remains disadvantaged due to the ineffectiveness of current data regulation that does not oblige the companies to fully and transparently disclose how and when they use, share, or profit from the data. Furthermore, the software tool developed during the research is, we believe, the first that is capable of a comparative analysis of VA privacy with a visual demonstration to increase ease of understanding for the user

Advanced Techniques for Improving the Efficacy of Digital Forensics Investigations

Digital forensics is the science concerned with discovering, preserving, and analyzing evidence on digital devices. The intent is to be able to determine what events have taken place, when they occurred, who performed them, and how they were performed. In order for an investigation to be effective, it must exhibit several characteristics. The results produced must be reliable, or else the theory of events based on the results will be flawed. The investigation must be comprehensive, meaning that it must analyze all targets which may contain evidence of forensic interest. Since any investigation must be performed within the constraints of available time, storage, manpower, and computation, investigative techniques must be efficient. Finally, an investigation must provide a coherent view of the events under question using the evidence gathered. Unfortunately the set of currently available tools and techniques used in digital forensic investigations does a poor job of supporting these characteristics. Many tools used contain bugs which generate inaccurate results; there are many types of devices and data for which no analysis techniques exist; most existing tools are woefully inefficient, failing to take advantage of modern hardware; and the task of aggregating data into a coherent picture of events is largely left to the investigator to perform manually. To remedy this situation, we developed a set of techniques to facilitate more effective investigations. To improve reliability, we developed the Forensic Discovery Auditing Module, a mechanism for auditing and enforcing controls on accesses to evidence. To improve comprehensiveness, we developed ramparser, a tool for deep parsing of Linux RAM images, which provides previously inaccessible data on the live state of a machine. To improve efficiency, we developed a set of performance optimizations, and applied them to the Scalpel file carver, creating order of magnitude improvements to processing speed and storage requirements. Last, to facilitate more coherent investigations, we developed the Forensic Automated Coherence Engine, which generates a high-level view of a system from the data generated by low-level forensics tools. Together, these techniques significantly improve the effectiveness of digital forensic investigations conducted using them

Uncertainty-aware video visual analytics of tracked moving objects

Vast amounts of video data render manual video analysis useless while recent automatic video analytics techniques suffer from insufficient performance. To alleviate these issues we present a scalable and reliable approach exploiting the visual analytics methodology. This involves the user in the iterative process of exploration hypotheses generation and their verification. Scalability is achieved by interactive filter definitions on trajectory features extracted by the automatic computer vision stage. We establish the interface between user and machine adopting the VideoPerpetuoGram (VPG) for visualization and enable users to provide filter-based relevance feedback. Additionally users are supported in deriving hypotheses by context-sensitive statistical graphics. To allow for reliable decision making we gather uncertainties introduced by the computer vision step communicate these information to users through uncertainty visualization and grant fuzzy hypothesis formulation to interact with the machine. Finally we demonstrate the effectiveness of our approach by the video analysis mini challenge which was part of the IEEE Symposium on Visual Analytics Science and Technology 2009