A Hardware-Assisted Insider Threat Detection and Prevention Framework

Today, the USB protocol is among the most widely used protocols. However, the mass-proliferation of USB has led to a threat vector wherein USB devices are assumed innocent, leaving computers open to an attack. Malicious USB devices can disguise themselves as benign devices to insert malicious commands to connected end devices. A rogue device appears benign to the average OS, requiring advanced detection schemes to identify malicious devices. However, using system-level hooks, advanced threats may subvert OS-reliant detection schemes. This thesis showcases USB-Watch, a hardware-based USB threat detection framework. The hardware can collect live USB traffic before the data can be altered in a corrupted OS. Behavioral analysis of USB devices allows for a generalizable anomaly detection classifier in hardware that can detect abnormal behavior from USB devices. The framework tested achieves an ROC AUC of 0.99 against a testbed of live USB devices

A Taxonomy of Virtualization Security Issues in Cloud Computing Environments

Objectives: To identify the main challenges and security issues of virtualization in cloud computing environments. It reviews the alleviation techniques for improving the security of cloud virtualization systems. Methods/ Statistical Analysis: Virtualization is a fundamental technology for cloud computing, and for this reason, any cloud vulnerabilities and threats affect virtualization. In this study, the systematic literature review is performed to find out the vulnerabilities and risks of virtualization in cloud computing and to identify threats, and attacks result from those vulnerabilities. Furthermore, we discover and analyze the effective mitigation techniques that are used to protect, secure, and manage virtualization environments. Findings: Thirty vulnerabilities are identified, explained, and classified into six proposed classes. Furthermore, fifteen main virtualization threats and attacks ar defined according to exploited vulnerabilities in a cloud environment. Application/Improvements: A set of common mitigation solutions are recognized and discovered to alleviate the virtualization security risks. These reviewed techniques are analyzed and evaluated according to five specified security criteria

Modeling of Advanced Threat Actors: Characterization, Categorization and Detection

Tesis por compendio[ES] La información y los sistemas que la tratan son un activo a proteger para personas, organizaciones e incluso países enteros. Nuestra dependencia en las tecnologías de la información es cada día mayor, por lo que su seguridad es clave para nuestro bienestar. Los beneficios que estas tecnologías nos proporcionan son incuestionables, pero su uso también introduce riesgos que ligados a nuestra creciente dependencia de las mismas es necesario mitigar. Los actores hostiles avanzados se categorizan principalmente en grupos criminales que buscan un beneficio económico y en países cuyo objetivo es obtener superioridad en ámbitos estratégicos como el comercial o el militar. Estos actores explotan las tecnologías, y en particular el ciberespacio, para lograr sus objetivos. La presente tesis doctoral realiza aportaciones significativas a la caracterización de los actores hostiles avanzados y a la detección de sus actividades. El análisis de sus características es básico no sólo para conocer a estos actores y sus operaciones, sino para facilitar el despliegue de contramedidas que incrementen nuestra seguridad. La detección de dichas operaciones es el primer paso necesario para neutralizarlas, y por tanto para minimizar su impacto. En el ámbito de la caracterización, este trabajo profundiza en el análisis de las tácticas y técnicas de los actores. Dicho análisis siempre es necesario para una correcta detección de las actividades hostiles en el ciberespacio, pero en el caso de los actores avanzados, desde grupos criminales hasta estados, es obligatorio: sus actividades son sigilosas, ya que el éxito de las mismas se basa, en la mayor parte de casos, en no ser detectados por la víctima. En el ámbito de la detección, este trabajo identifica y justifica los requisitos clave para poder establecer una capacidad adecuada frente a los actores hostiles avanzados. Adicionalmente, proporciona las tácticas que deben ser implementadas en los Centros de Operaciones de Seguridad para optimizar sus capacidades de detección y respuesta. Debemos destacar que estas tácticas, estructuradas en forma de kill-chain, permiten no sólo dicha optimización, sino también una aproximación homogénea y estructurada común para todos los centros defensivos. En mi opinión, una de las bases de mi trabajo debe ser la aplicabilidad de los resultados. Por este motivo, el análisis de tácticas y técnicas de los actores de la amenaza está alineado con el principal marco de trabajo público para dicho análisis, MITRE ATT&CK. Los resultados y propuestas de esta investigación pueden ser directamente incluidos en dicho marco, mejorando así la caracterización de los actores hostiles y de sus actividades en el ciberespacio. Adicionalmente, las propuestas para mejorar la detección de dichas actividades son de aplicación directa tanto en los Centros de Operaciones de Seguridad actuales como en las tecnologías de detección más comunes en la industria. De esta forma, este trabajo mejora de forma significativa las capacidades de análisis y detección actuales, y por tanto mejora a su vez la neutralización de operaciones hostiles. Estas capacidades incrementan la seguridad global de todo tipo de organizaciones y, en definitiva, de nuestra sociedad.[CA] La informació i els sistemas que la tracten són un actiu a protegir per a persones, organitzacions i fins i tot països sencers. La nostra dependència en les tecnologies de la informació es cada dia major, i per aixó la nostra seguretat és clau per al nostre benestar. Els beneficis que aquestes tecnologies ens proporcionen són inqüestionables, però el seu ús també introdueix riscos que, lligats a la nostra creixent dependència de les mateixes és necessari mitigar. Els actors hostils avançats es categoritzen principalment en grups criminals que busquen un benefici econòmic i en països el objectiu dels quals és obtindre superioritat en àmbits estratègics, com ara el comercial o el militar. Aquests actors exploten les tecnologies, i en particular el ciberespai, per a aconseguir els seus objectius. La present tesi doctoral realitza aportacions significatives a la caracterització dels actors hostils avançats i a la detecció de les seves activitats. L'anàlisi de les seves característiques és bàsic no solament per a conéixer a aquests actors i les seves operacions, sinó per a facilitar el desplegament de contramesures que incrementen la nostra seguretat. La detección de aquestes operacions és el primer pas necessari per a netralitzar-les, i per tant, per a minimitzar el seu impacte. En l'àmbit de la caracterització, aquest treball aprofundeix en l'anàlisi de lestàctiques i tècniques dels actors. Aquesta anàlisi sempre és necessària per a una correcta detecció de les activitats hostils en el ciberespai, però en el cas dels actors avançats, des de grups criminals fins a estats, és obligatòria: les seves activitats són sigiloses, ja que l'éxit de les mateixes es basa, en la major part de casos, en no ser detectats per la víctima. En l'àmbit de la detecció, aquest treball identifica i justifica els requisits clau per a poder establir una capacitat adequada front als actors hostils avançats. Adicionalment, proporciona les tàctiques que han de ser implementades en els Centres d'Operacions de Seguretat per a optimitzar les seves capacitats de detecció i resposta. Hem de destacar que aquestes tàctiques, estructurades en forma de kill-chain, permiteixen no només aquesta optimització, sinò tambié una aproximació homogènia i estructurada comú per a tots els centres defensius. En la meva opinio, una de les bases del meu treball ha de ser l'aplicabilitat dels resultats. Per això, l'anàlisi de táctiques i tècniques dels actors de l'amenaça està alineada amb el principal marc públic de treball per a aquesta anàlisi, MITRE ATT&CK. Els resultats i propostes d'aquesta investigació poden ser directament inclosos en aquest marc, millorant així la caracterització dels actors hostils i les seves activitats en el ciberespai. Addicionalment, les propostes per a millorar la detecció d'aquestes activitats són d'aplicació directa tant als Centres d'Operacions de Seguretat actuals com en les tecnologies de detecció més comuns de la industria. D'aquesta forma, aquest treball millora de forma significativa les capacitats d'anàlisi i detecció actuals, i per tant millora alhora la neutralització d'operacions hostils. Aquestes capacitats incrementen la seguretat global de tot tipus d'organitzacions i, en definitiva, de la nostra societat.[EN] Information and its related technologies are a critical asset to protect for people, organizations and even whole countries. Our dependency on information technologies increases every day, so their security is a key issue for our wellness. The benefits that information technologies provide are questionless, but their usage also presents risks that, linked to our growing dependency on technologies, we must mitigate. Advanced threat actors are mainly categorized in criminal gangs, with an economic goal, and countries, whose goal is to gain superiority in strategic affairs such as commercial or military ones. These actors exploit technologies, particularly cyberspace, to achieve their goals. This PhD Thesis significantly contributes to advanced threat actors' categorization and to the detection of their hostile activities. The analysis of their features is a must not only to know better these actors and their operations, but also to ease the deployment of countermeasures that increase our security. The detection of these operations is a mandatory first step to neutralize them, so to minimize their impact. Regarding characterization, this work delves into the analysis of advanced threat actors' tactics and techniques. This analysis is always required for an accurate detection of hostile activities in cyberspace, but in the particular case of advances threat actors, from criminal gangs to nation-states, it is mandatory: their activities are stealthy, as their success in most cases relies on not being detected by the target. Regarding detection, this work identifies and justifies the key requirements to establish an accurate response capability to face advanced threat actors. In addition, this work defines the tactics to be deployed in Security Operations Centers to optimize their detection and response capabilities. It is important to highlight that these tactics, with a kill-chain arrangement, allow not only this optimization, but particularly a homogeneous and structured approach, common to all defensive centers. In my opinion, one of the main bases of my work must be the applicability of its results. For this reason, the analysis of threat actors' tactics and techniques is aligned with the main public framework for this analysis, MITRE ATT&CK. The results and proposals from this research can be directly included in this framework, improving the threat actors' characterization, as well as their cyberspace activities' one. In addition, the proposals to improve these activities' detection are directly applicable both in current Security Operations Centers and in common industry technologies. In this way, I consider that this work significantly improves current analysis and detection capabilities, and at the same time it improves hostile operations' neutralization. These capabilities increase global security for all kind of organizations and, definitely, for our whole society.Villalón Huerta, A. (2023). Modeling of Advanced Threat Actors: Characterization, Categorization and Detection [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/193855Compendi

Insider threat : memory confidentiality and integrity in the cloud

PhD ThesisThe advantages of always available services, such as remote device backup or data storage, have helped the widespread adoption of cloud computing. However, cloud computing services challenge the traditional boundary between trusted inside and untrusted outside. A consumer’s data and applications are no longer in premises, fundamentally changing the scope of an insider threat. This thesis looks at the security risks associated with an insider threat. Specifically, we look into the critical challenge of assuring data confidentiality and integrity for the execution of arbitrary software in a consumer’s virtual machine. The problem arises from having multiple virtual machines sharing hardware resources in the same physical host, while an administrator is granted elevated privileges over such host. We used an empirical approach to collect evidence of the existence of this security problem and implemented a prototype of a novel prevention mechanism for such a problem. Finally, we propose a trustworthy cloud architecture which uses the security properties our prevention mechanism guarantees as a building block. To collect the evidence required to demonstrate how an insider threat can become a security problem to a cloud computing infrastructure, we performed a set of attacks targeting the three most commonly used virtualization software solutions. These attacks attempt to compromise data confidentiality and integrity of cloud consumers’ data. The prototype to evaluate our novel prevention mechanism was implemented in the Xen hypervisor and tested against known attacks. The prototype we implemented focuses on applying restrictions to the permissive memory access model currently in use in the most relevant virtualization software solutions. We envision the use of a mandatory memory access control model in the virtualization software. This model enforces the principle of least privilege to memory access, which means cloud administrators are assigned with only enough privileges to successfully perform their administrative tasks. Although the changes we suggest to the virtualization layer make it more restrictive, our solution is versatile enough to port all the functionality available in current virtualization viii solutions. Therefore, our trustworthy cloud architecture guarantees data confidentiality and integrity and achieves a more transparent trustworthy cloud ecosystem while preserving functionality. Our results show that a malicious insider can compromise security sensitive data in the three most important commercial virtualization software solutions. These virtualization solutions are publicly available and the number of cloud servers using these solutions accounts for the majority of the virtualization market. The prevention mechanism prototype we designed and implemented guarantees data confidentiality and integrity against such attacks and reduces the trusted computing base of the virtualization layer. These results indicate how current virtualization solutions need to reconsider their view on insider threats

Security hardened remote terminal units for SCADA networks.

Remote terminal units (RTUs) are perimeter supervisory control and data acquisition (SCADA) devices that measure and control actual physical devices. Cyber security was largely ignored in SCADA for many years, and the cyber security issues that now face SCADA and DCS, specifically RTU security, are investigated in this research. This dissertation presents a new role based access control model designed specifically for RTUs and process control. The model is developed around the process control specific data element called a point, and point operations. The model includes: assignment constraints that limit the RTU operations that a specific role can be assigned and activation constraints that allow a security administrator to specify conditions when specific RTU roles or RTU permissions cannot be used. RTU enforcement of the new access control model depends on, and is supported by, the protection provided by an RTU\u27s operating system. This dissertation investigates two approaches for using minimal kernels to reduce potential vulnerabilities in RTU protection enforcement and create a security hardened RTU capable of supporting the new RTU access control model. The first approach is to reduce a commercial OS kernel to only those components needed by the RTU, removing any known or unknown vulnerabilities contained in the eliminated code and significantly reducing the size of the kernel. The second approach proposes using a microkernel that supports partitioning as the basis for an RTU specific operating system which isolates network related RTU software, the RTU attack surface, from critical RTU operational software such as control algorithms and analog and digital input and output. In experimental analysis of a prototype hardened RTU connected to real SCADA hardware, a reduction of over 50% was obtained in reducing a 2.4 Linux kernel to run on actual RTU hardware. Functional testing demonstrated that different users were able to carryout assigned tasks with the limited set of permissions provided by the security hardened RTU and a series of simulated insider attacks were prevented by the RTU role based access control system. Analysis of communication times indicated response times would be acceptable for many SCADA and DCS application areas. Investigation of a partitioning microkernel for an RTU identified the L4 microkernel as an excellent candidate. Experimental evaluation of L4 on real hardware found the IPC overhead for simulated critical RTU operations protected by L4 partitioning to be sufficiently small to warrant continued investigation of the approach

A comprehensive meta-analysis of cryptographic security mechanisms for cloud computing

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.The concept of cloud computing offers measurable computational or information resources as a service over the Internet. The major motivation behind the cloud setup is economic benefits, because it assures the reduction in expenditure for operational and infrastructural purposes. To transform it into a reality there are some impediments and hurdles which are required to be tackled, most profound of which are security, privacy and reliability issues. As the user data is revealed to the cloud, it departs the protection-sphere of the data owner. However, this brings partly new security and privacy concerns. This work focuses on these issues related to various cloud services and deployment models by spotlighting their major challenges. While the classical cryptography is an ancient discipline, modern cryptography, which has been mostly developed in the last few decades, is the subject of study which needs to be implemented so as to ensure strong security and privacy mechanisms in today’s real-world scenarios. The technological solutions, short and long term research goals of the cloud security will be described and addressed using various classical cryptographic mechanisms as well as modern ones. This work explores the new directions in cloud computing security, while highlighting the correct selection of these fundamental technologies from cryptographic point of view

Deteção de propagação de ameaças e exfiltração de dados em redes empresariais

Modern corporations face nowadays multiple threats within their networks. In an era where companies are tightly dependent on information, these threats can seriously compromise the safety and integrity of sensitive data. Unauthorized access and illicit programs comprise a way of penetrating the corporate networks, able to traversing and propagating to other terminals across the private network, in search of confidential data and business secrets. The efficiency of traditional security defenses are being questioned with the number of data breaches occurred nowadays, being essential the development of new active monitoring systems with artificial intelligence capable to achieve almost perfect detection in very short time frames. However, network monitoring and storage of network activity records are restricted and limited by legal laws and privacy strategies, like encryption, aiming to protect the confidentiality of private parties. This dissertation proposes methodologies to infer behavior patterns and disclose anomalies from network traffic analysis, detecting slight variations compared with the normal profile. Bounded by network OSI layers 1 to 4, raw data are modeled in features, representing network observations, and posteriorly, processed by machine learning algorithms to classify network activity. Assuming the inevitability of a network terminal to be compromised, this work comprises two scenarios: a self-spreading force that propagates over internal network and a data exfiltration charge which dispatch confidential info to the public network. Although features and modeling processes have been tested for these two cases, it is a generic operation that can be used in more complex scenarios as well as in different domains. The last chapter describes the proof of concept scenario and how data was generated, along with some evaluation metrics to perceive the model’s performance. The tests manifested promising results, ranging from 96% to 99% for the propagation case and 86% to 97% regarding data exfiltration.Nos dias de hoje, várias organizações enfrentam múltiplas ameaças no interior da sua rede. Numa época onde as empresas dependem cada vez mais da informação, estas ameaças podem compremeter seriamente a segurança e a integridade de dados confidenciais. O acesso não autorizado e o uso de programas ilícitos constituem uma forma de penetrar e ultrapassar as barreiras organizacionais, sendo capazes de propagarem-se para outros terminais presentes no interior da rede privada com o intuito de atingir dados confidenciais e segredos comerciais. A eficiência da segurança oferecida pelos sistemas de defesa tradicionais está a ser posta em causa devido ao elevado número de ataques de divulgação de dados sofridos pelas empresas. Desta forma, o desenvolvimento de novos sistemas de monitorização ativos usando inteligência artificial é crucial na medida de atingir uma deteção mais precisa em curtos períodos de tempo. No entanto, a monitorização e o armazenamento dos registos da atividade da rede são restritos e limitados por questões legais e estratégias de privacidade, como a cifra dos dados, visando proteger a confidencialidade das entidades. Esta dissertação propõe metodologias para inferir padrões de comportamento e revelar anomalias através da análise de tráfego que passa na rede, detetando pequenas variações em comparação com o perfil normal de atividade. Delimitado pelas camadas de rede OSI 1 a 4, os dados em bruto são modelados em features, representando observações de rede e, posteriormente, processados por algoritmos de machine learning para classificar a atividade de rede. Assumindo a inevitabilidade de um terminal ser comprometido, este trabalho compreende dois cenários: um ataque que se auto-propaga sobre a rede interna e uma tentativa de exfiltração de dados que envia informações para a rede pública. Embora os processos de criação de features e de modelação tenham sido testados para estes dois casos, é uma operação genérica que pode ser utilizada em cenários mais complexos, bem como em domínios diferentes. O último capítulo inclui uma prova de conceito e descreve o método de criação dos dados, com a utilização de algumas métricas de avaliação de forma a espelhar a performance do modelo. Os testes mostraram resultados promissores, variando entre 96% e 99% para o caso da propagação e entre 86% e 97% relativamente ao roubo de dados.Mestrado em Engenharia de Computadores e Telemátic

Protection in commodity monolithic operating systems

This dissertation suggests and partially demonstrates that it is feasible to retrofit real privilege separation within commodity operating systems by "nesting" a small memory management protection domain inside a monolithic kernel's single-address space: all the while allowing both domains to operate at the same hardware privilege level. This dissertation also demonstrates a microarchitectural return-integrity protection domain that efficiently asserts dynamic "return-to-sender" semantics for all operating system return control-flow operations. Employing these protection domains, we provide mitigations to large classes of kernel attacks such as code injection and return-oriented programming and deploy information protection policies that are not feasible with existing systems. Operating systems form the foundation of information protection in multiprogramming environments. Unfortunately, today's commodity operating systems employ monolithic kernel design, where any single exploit in the vast code base undermines all information protection in the system because all kernel code operates with full supervisor privileges, meaning that even perfectly secure applications are vulnerable. This dissertation explores an approach that retrofits fundamental information protection design principles into commodity monolithic operating systems, the aim of which is a micro-evolution of commodity system design that incrementally decomposes monolithic operating systems from the ground up, thereby applying microkernel-like security properties for billions of users worldwide. The key contribution is the creation of a new operating system organization, the Nested Kernel Architecture, which "nests" a new, efficient intra-kernel memory isolation mechanism into a traditional monolithic operating system design. Using the Nested Kernel Architecture we introduce write-protection services for kernel developers to deploy security policies in ways not possible in current systems—while greatly reducing the trusted computing base—and demonstrate the value of these services by deploying three special data protection policies. Overall, the Nested Kernel Architecture demonstrates practical in-place protections that require only minor code modifications with minimal run- time overheads

Design and Deployment of an Access Control Module for Data Lakes

Nowadays big data is considered an extremely valued asset for companies, which are discovering new avenues to use it for their business profit. However, an organization’s ability to effectively extract valuable information from data is based on its knowledge management infrastructure. Thus, most organizations are transitioning from data warehouse (DW) storages to data lake (DL) infrastructures, from which further insights are derived. The present work is carried out as part of a cybersecurity project in a financial institution that manages vast volumes and variety of data that is kept in a data lake. Although DL is presented as the answer to the current big data scenario, this infrastructure presents certain flaws on authentication and access control. Preceding work on DL access control points out that the main goal is to avoid fraudulent behaviors derived from user’s access, such as secondary use1, that could result in business data being exposed to third parties. To overcome the risk, traditional mechanisms attempt to identify these behaviors based on rules, however, they cannot reveal all different kinds of fraud because they only look for known patterns of misuse. The present work proposes a novel access control system for data lakes, assisted by Oracle’s database audit trail and based on anomaly detection mechanisms, that automatically looks for events that do not conform the normal or expected behavior. Thus, the overall aim of this project is to develop and deploy an automated system for identifying abnormal accesses to the DL, which can be separated into four subgoals: explore the different technologies that could be applied in the domain of anomaly detection, design the solution, deploy it, and evaluate the results. For the purpose, feature engineering is performed, and four different unsupervised ML models are built and evaluated. According to the quality of the results, the better model is finally productionalized with Docker. To conclude, although anomaly detection has been a lasting yet active research area for several decades, there are still some unique problem complexities and challenges that leave the way open for the proposed solution to be further improved.Doble Grado en Ingeniería Informática y Administración de Empresa