Introductory Computer Forensics

INTERPOL (International Police) built cybercrime programs to keep up with emerging cyber threats, and aims to coordinate and assist international operations for ?ghting crimes involving computers. Although signi?cant international efforts are being made in dealing with cybercrime and cyber-terrorism, ?nding effective, cooperative, and collaborative ways to deal with complicated cases that span multiple jurisdictions has proven dif?cult in practic

Analyzing audit trails in a distributed and hybrid intrusion detection platform

Efforts have been made over the last decades in order to design and perfect Intrusion Detection Systems (IDS). In addition to the widespread use of Intrusion Prevention Systems (IPS) as perimeter defense devices in systems and networks, various IDS solutions are used together as elements of holistic approaches to cyber security incident detection and prevention, including Network-Intrusion Detection Systems (NIDS) and Host-Intrusion Detection Systems (HIDS). Nevertheless, specific IDS and IPS technology face several effectiveness challenges to respond to the increasing scale and complexity of information systems and sophistication of attacks. The use of isolated IDS components, focused on one-dimensional approaches, strongly limits a common analysis based on evidence correlation. Today, most organizations’ cyber-security operations centers still rely on conventional SIEM (Security Information and Event Management) technology. However, SIEM platforms also have significant drawbacks in dealing with heterogeneous and specialized security event-sources, lacking the support for flexible and uniform multi-level analysis of security audit-trails involving distributed and heterogeneous systems. In this thesis, we propose an auditing solution that leverages on different intrusion detection components and synergistically combines them in a Distributed and Hybrid IDS (DHIDS) platform, taking advantage of their benefits while overcoming the effectiveness drawbacks of each one. In this approach, security events are detected by multiple probes forming a pervasive, heterogeneous and distributed monitoring environment spread over the network, integrating NIDS, HIDS and specialized Honeypot probing systems. Events from those heterogeneous sources are converted to a canonical representation format, and then conveyed through a Publish-Subscribe middleware to a dedicated logging and auditing system, built on top of an elastic and scalable document-oriented storage system. The aggregated events can then be queried and matched against suspicious attack signature patterns, by means of a proposed declarative query-language that provides event-correlation semantics

MS IPTV audit collection services

Tese de mestrado em Segurança Informática, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2011Microsoft Mediaroom Internet Protocol Television (MS IPTV), uma plataforma de televisão digital, levou o conceito de televisão a uma dimensão totalmente nova. MS IPTV é um sistema onde o serviço de televisão digital é entregue aos clientes usando Internet Protocol (IP), através de uma conexão de banda larga. Com o advento do IPTV começaram a aparecer novas situações relacionadas com a segurança da televisão, uma vez que, a infra-estrutura começou a ganhar complexidade e exposição a uma série de novos riscos. Por esta razão, a segurança numa infra-estrutura de MS IPTV não é apenas mais uma funcionalidade, mas sim uma necessidade. Podemos mesmo dizer que hoje em dia é obrigatório aguçar o engenho para estar um passo à frente dos atacantes, uma vez que estes estão sempre à espera de uma brecha, para comprometer os sistemas. Uma infra-estrutura como o MS IPTV armazena por omissão dados relativos ao comportamento dos utilizadores ao nível dos logs, no entanto esta informação só se torna relevante se puder ser consultada e analisada com o objetivo de proporcionar uma compreensão a alto nível sobre os diferentes padrões que estão a ocorrer nos servidores ou no comportamento dos utilizadores, uma tarefa que envolve poderosas técnicas de data parsing. A tese apresenta uma abordagem que combina técnicas de data parsing, a fim de analisar os logs relevantes da infra-estrutura de MS IPTV, com o objetivo principal de aumentar a segurança através da investigação dos tipos de informações adicionais que pode ser extraída. Tentámos assim entender se é possível determinar que tipos de ataques estão a ser perpetrados contra a infra-estrutura MS IPTV, com base na análise dos logs. Como o foco central desta tese está no diagnóstico, propomos uma abordagem para descobrir ataques, onde os logs são verificados para identificar grupos coerentes de ocorrências susceptíveis de constituir ataques que apelidámos de padrões. Nos testes, verificámos que a nossa abordagem consegue bons resultados na descoberta de ataques. Os resultados obtidos têm a vantagem adicional de poderem ser integrados na ferramenta de monitorização utilizada pelas equipas de operação dos sistemas da Portugal Telecom, o System Center Operations Manager (SCOM).Microsoft Mediaroom Internet Protocol TeleVision (MS IPTV), one of the platforms for digital TV, took television to an all new dimension level. MS IPTV is described as a system where a digital television service is delivered to consumers using the Internet Protocol over a broadband connection. Since the infrastructure started to gain complexity and exposure to a number of new risks, never envisaged situations related to television security started to appear. For this reason, MS IPTV security is not only a great asset, but also a necessity. Nowadays it is mandatory to sharpen the wit to get ahead of attackers, who are always waiting for a breach to compromise our systems. MS IPTV log servers collect information about user and system behavior. However, this information only becomes relevant if it can be queried and analyzed with the purpose of providing high-level understanding about the different patterns. This task must comprise powerful data parsing techniques, since MS IPTV is able to generate close to one terabyte of logs per day. This thesis presents an approach that combines data parsing techniques in order to analyze relevant MS IPTV logs, with the main objective to increase security through the investigation of what type of additional information can be extracted from the server log files of a MS IPTV platform. The thesis focus is on diagnosis, trying to understand if it is possible to determine what type of attacks are being perpetrated against the MS IPTV infrastructure. We propose an approach for discovering attacks, where the application logs are scanned to identify coherent groups of occurrences that we call patterns, which are likely to constitute attacks. Our results showed that our approach achieves good results in discovering potential attacks. Our output results can be integrated into the MS IPTV monitoring system tool SCOM (System Center Operations Manager), which is an additional advantage over the other monitoring and log management systems

Identifying evidences of computer programming skills through automatic source code evaluation

Orientador: Roberto PereiraCoorientador: Eleandro MaschioTese (doutorado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa : Curitiba, 27/03/2020Inclui referências: p. 98-106Área de concentração: Ciência da ComputaçãoResumo: Esta tese e contextualizada no ensino de programacao de computadores em cursos de Computacao e investiga aspectos e estrategias para avaliacao automatica e continua de codigos fonte desenvolvidos pelos alunos. O estado da arte foi identificado por meio de revisao sistematica de literatura e revelou que as pesquisas anteriores tendem a realizar avaliacoes baseadas em aspectos tecnicos de codigos fonte, como a avaliacao de corretude funcional e a deteccao de erros. Avaliacoes baseadas em habilidades, por outro lado, sao pouco exploradas e possuem potencial para fornecer detalhes a respeito de habilidades representadas por conceitos de alto nivel, como desvios condicionais e estruturas de repeticao. Um metodo de identificacao automatica de evidencias de aprendizado e entao proposto como uma abordagem baseada em habilidades para a avaliacao automatica de codigos fonte de programacao. O metodo e caracterizado pela implementacao de diferentes estrategias para avaliacao de codigos fonte, identificacao de evidencias de habilidades de programacao, e representacao destas habilidades em um modelo do aluno. Experimentos realizados em ambientes controlados (bases de dados artificiais) mostraram que estrategias automaticas de avaliacao de codigo fonte sao viaveis. Experimentos conduzidos em ambientes reais (codigos fonte produzidos por alunos) produziram resultados semelhantes aos ambientes controlados, entretanto revelaram limitacoes relacionadas a implementacao das estrategias, como vulnerabilidades a sintaxes inesperadas e falhas em expressoes regulares. Um conjunto de habilidades foi selecionado para compor o modelo do aluno, representado por uma rede bayesiana dinamica. Por meio de experimentos foi demonstrado que a alimentacao do modelo com evidencias resultantes da avaliacao automatica de codigos fonte permite o acompanhamento do progresso das habilidades dos alunos. Finalmente, as estrategias automaticas em conjunto com os recursos do modelo do aluno permitiram a demonstracao da avaliacao baseada em habilidades, que se mostrou um recurso valioso para identificacao de solucoes funcionalmente corretas, porem conceitualmente incorretas; quando o programa e funcionalmente correto, retornando resultados esperados a determinadas entradas, porem foi construido com recursos e conceitos incorretos. Palavras-chave: Programacao de Computadores, Avaliacao Automatica, Avaliacao Baseada em HabilidadesAbstract: This thesis is contextualized in the teaching of computer programming in Computing courses and investigates aspects and strategies for automatic and continuous evaluation of student developed source codes. The state of the art was identified through systematic literature review and revealed previous research tends to perform evaluations based on source codes technical aspects, such as functional correctness assessment and error detection. Skills-based assessments, in turn, are less explored although having potential to provide details of skills represented by high-level concepts, such as conditionals and repetition structures. A method for automatic identification of learning evidences is then proposed as a skills-based approach to automatic evaluation of programming source codes. The method is characterized by implementing different strategies for source code evaluation, identifying evidences of programming skills, and representing these skills in a student model. Experiments conducted in controlled scenarios (testing datasets) have shown automatic source code evaluation strategies are viable. Experiments conducted in real scenarios (student-made source codes) produced results similar to controlled scenarios, however, implementation-related limitations were revealed for some strategies, such as vulnerabilities to unexpected syntax and flaws in regular expressions. A skill set was selected to compose our student model, represented by a Dynamic Bayesian Network. Experiments have shown feeding the model with evidences resulting from source codes automatic evaluation allows monitoring students' skills progress. Finally, automatic strategies coupled with student model capabilities enabled demonstrating skills-based assessment, which showed a valuable resource for identifying functionally correct source codes, but conceptually incorrect; when a program is correct functionally, returning expected results to specific inputs, but it was built with erroneous concepts and resources. Keywords: Computer Programming, Automatic Evaluation, Skills-Based Assessmen

Ransomware Simulator for In-Depth Analysis and Detection: Leveraging Centralized Logging and Sysmon for Improved Cybersecurity

Abstract Ransomware attacks have become increasingly prevalent and sophisticated, posing significant threats to organizations and individuals worldwide. To effectively combat these threats, security professionals must continuously develop and adapt their detection and mitigation strategies. This master thesis presents the design and implementation of a ransomware simulator to facilitate an in-depth analysis of ransomware Tactics, Techniques, and Procedures (TTPs) and to evaluate the effectiveness of centralized logging and Sysmon, including the latest event types, in detecting and responding to such attacks. The study explores the advanced capabilities of Sysmon as a logging tool and data source, focusing on its ability to capture multiple event types, such as file creation, process execution, and network traffic, as well as the newly added event types. The aim is to demonstrate the effectiveness of Sysmon in detecting and analyzing malicious activities, with an emphasis on the latest features. By focusing on the comprehensive aspects of a cyber-attack, the study showcases the versatility and utility of Sysmon in detecting and addressing various attack vectors. The ransomware simulator is developed using a PowerShell script that emulates various ransomware TTPs and attack scenarios, providing a comprehensive and realistic simulation of a ransomware attack. Sysmon, a powerful system monitoring tool, is utilized to monitor and log the activities associated with the simulated attack, including the events generated by the new Sysmon features. Centralized logging is achieved through the integration of Splunk Enterprise, a widely used platform for log analysis and management. The collected logs are then analyzed to identify patterns, indicators of compromise (IoCs), and potential detection and mitigation strategies. Through the development of the ransomware simulator and the subsequent analysis of Sysmon logs, this research contributes to strengthening the security posture of organizations and improving cybersecurity measures against ransomware threats, with a focus on the latest Sysmon capabilities. The results demonstrate the importance of monitoring and analyzing system events to effectively detect and respond to ransomware attacks. This research can serve as a basis for further exploration of ransomware detection and response strategies, contributing to the advancement of cybersecurity practices and the development of more robust security measures against ransomware threats

Certifications of Critical Systems – The CECRIS Experience

In recent years, a considerable amount of effort has been devoted, both in industry and academia, to the development, validation and verification of critical systems, i.e. those systems whose malfunctions or failures reach a critical level both in terms of risks to human life as well as having a large economic impact.Certifications of Critical Systems – The CECRIS Experience documents the main insights on Cost Effective Verification and Validation processes that were gained during work in the European Research Project CECRIS (acronym for Certification of Critical Systems). The objective of the research was to tackle the challenges of certification by focusing on those aspects that turn out to be more difficult/important for current and future critical systems industry: the effective use of methodologies, processes and tools.The CECRIS project took a step forward in the growing field of development, verification and validation and certification of critical systems. It focused on the more difficult/important aspects of critical system development, verification and validation and certification process. Starting from both the scientific and industrial state of the art methodologies for system development and the impact of their usage on the verification and validation and certification of critical systems, the project aimed at developing strategies and techniques supported by automatic or semi-automatic tools and methods for these activities, setting guidelines to support engineers during the planning of the verification and validation phases

Certifications of Critical Systems – The CECRIS Experience

In recent years, a considerable amount of effort has been devoted, both in industry and academia, to the development, validation and verification of critical systems, i.e. those systems whose malfunctions or failures reach a critical level both in terms of risks to human life as well as having a large economic impact.Certifications of Critical Systems – The CECRIS Experience documents the main insights on Cost Effective Verification and Validation processes that were gained during work in the European Research Project CECRIS (acronym for Certification of Critical Systems). The objective of the research was to tackle the challenges of certification by focusing on those aspects that turn out to be more difficult/important for current and future critical systems industry: the effective use of methodologies, processes and tools.The CECRIS project took a step forward in the growing field of development, verification and validation and certification of critical systems. It focused on the more difficult/important aspects of critical system development, verification and validation and certification process. Starting from both the scientific and industrial state of the art methodologies for system development and the impact of their usage on the verification and validation and certification of critical systems, the project aimed at developing strategies and techniques supported by automatic or semi-automatic tools and methods for these activities, setting guidelines to support engineers during the planning of the verification and validation phases

Forensic acquisition of file systems with parallel processing of digital artifacts to generate an early case assessment report

A evolução da maneira como os seres humanos interagem e realizam tarefas rotineiras mudou nas últimas décadas e uma longa lista de atividades agora somente são possíveis com o uso de tecnologias da informação – entre essas pode-se destacar a aquisição de bens e serviços, gestão e operações de negócios e comunicações. Essas transformações são visíveis também em outras atividades menos legítimas, permitindo que crimes sejam cometidos através de meios digitais. Em linhas gerais, investigadores forenses trabalham buscando por indícios de ações criminais realizadas por meio de dispositivos digitais para finalmente, tentar identificar os autores, o nível do dano causado e a história atrás que possibilitou o crime. Na sua essência, essa atividade deve seguir normas estritas para garantir que as provas sejam admitidas em tribunal, mas quanto maior o número de novos artefatos e maior o volume de dispositivos de armazenamento disponíveis, maior o tempo necessário entre a identificação de um dispositivo de um suspeito e o momento em que o investigador começa a navegar no mar de informações alojadas no dispositivo. Esta pesquisa, tem como objetivo antecipar algumas etapas do EDRM através do uso do processamento em paralelo adjacente nas unidades de processamento (CPU) atuais para para traduzir multiplos artefactos forenses do sistema operativo Windows 10 e gerar um relatório com as informações mais cruciais sobre o dispositivo adquirido. Permitindo uma análise antecipada do caso (ECA) ao mesmo tempo em que uma aquisição completa do disco está em curso, desse modo causando um impacto mínimo no tempo geral de aquisição

Machine learning techniques for android malware detection and classification

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Ingeniería Informática. Fecha de Lectura: 15-03-2019la realización de esta tesis no habría sido posible sin la financiación aportada por el proyecto CIBERDINE: Cybersecurity, Data and Risks (S2013/ICE3095) concedido por la Comunidad de Madrid

Towards an efficient vulnerability analysis methodology for better security risk management

2010 Summer.Includes bibliographical references.Risk management is a process that allows IT managers to balance between cost of the protective measures and gains in mission capability. A system administrator has to make a decision and choose an appropriate security plan that maximizes the resource utilization. However, making the decision is not a trivial task. Most organizations have tight budgets for IT security; therefore, the chosen plan must be reviewed as thoroughly as other management decisions. Unfortunately, even the best-practice security risk management frameworks do not provide adequate information for effective risk management. Vulnerability scanning and penetration testing that form the core of traditional risk management, identify only the set of system vulnerabilities. Given the complexity of today's network infrastructure, it is not enough to consider the presence or absence of vulnerabilities in isolation. Materializing a threat strongly requires the combination of multiple attacks using different vulnerabilities. Such a requirement is far beyond the capabilities of current day vulnerability scanners. Consequently, assessing the cost of an attack or cost of implementing appropriate security controls is possible only in a piecemeal manner. In this work, we develop and formalize new network vulnerability analysis model. The model encodes in a concise manner, the contributions of different security conditions that lead to system compromise. We extend the model with a systematic risk assessment methodology to support reasoning under uncertainty in an attempt to evaluate the vulnerability exploitation probability. We develop a cost model to quantify the potential loss and gain that can occur in a system if certain conditions are met (or protected). We also quantify the security control cost incurred to implement a set of security hardening measures. We propose solutions for the system administrator's decision problems covering the area of the risk analysis and risk mitigation analysis. Finally, we extend the vulnerability assessment model to the areas of intrusion detection and forensic investigation