Improving the Effectiveness of Security Controls to Prevent APT Attacks

An advanced persistent threat (APT) is a prolonged, aimed attack on a specific target. Cyber attackers gain access to a system or network and remain there for an extended period without being detected. The goal of APT attackers is generally stealing data and intellectual property. Despite all the awareness, technological advancements, and massiveinvestment, the fight against APTs is a losing battle. A false sense of security is a belief that the organization is safer than it is . We researched whether organizations have a false sense of security against APT attacks and what contributes to that belief. Our research indicated that employees were not confident about organizations’ cybersecurity posture. In this paper, we discuss one of our research contributions, which suggests remediation strategies that organizations can employ to increase the effectiveness of security controls against APT attacks

Improving the Effectiveness of Security Controls to Prevent APT Attacks

An advanced persistent threat (APT) is a prolonged, aimed attack on a specific target. Cyber attackers gain access to a system or network and remain there for an extended period without being detected. The goal of APT attackers is generally stealing data and intellectual property. Despite all the awareness, technological advancements, and massive investment, the fight against APTs is a losing battle. A false sense of security is a belief that the organization is safer than it is. We researched whether organizations have a false sense of security against APT attacks and what contributes to that belief. Our research indicated that employees were not confident about organizations’ cybersecurity posture. In this paper, we discuss one of our research contributions, which suggests remediation strategies that organizations can employ to increase the effectiveness of security controls against APT attacks

Cybersecurity Risk in U.S. Critical Infrastructure: An Analysis of Publicly Available U.S. Government Alerts and Advisories

As threat actor operations become increasingly sophisticated and emphasize the targeting of critical infrastructure and services, the need for cybersecurity information sharing will continue to grow. Escalating demand for cyber threat intelligence and information sharing across the cybersecurity community has resulted in the need to better understand the information produced by reputable sources such as U.S. CISA Alerts and ICS-CERT advisories. The text analysis program, Profiler Plus, is used to extract information from 1,574 U.S. government alerts and advisories to develop visualizations and generate enhanced insights into different cyber threat actor types, the tactics which can be used for cyber operations, and sectors of critical infrastructure at risk of an attack. The findings of this study enhance cyber threat intelligence activities by enabling an understanding of the trends in public information sharing as well as identifying gaps in open-source reporting on cyber-threat information

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

Cyber-Physical Threat Intelligence for Critical Infrastructures Security

Modern critical infrastructures comprise of many interconnected cyber and physical assets, and as such are large scale cyber-physical systems. Hence, the conventional approach of securing these infrastructures by addressing cyber security and physical security separately is no longer effective. Rather more integrated approaches that address the security of cyber and physical assets at the same time are required. This book presents integrated (i.e. cyber and physical) security approaches and technologies for the critical infrastructures that underpin our societies. Specifically, it introduces advanced techniques for threat detection, risk assessment and security information sharing, based on leading edge technologies like machine learning, security knowledge modelling, IoT security and distributed ledger infrastructures. Likewise, it presets how established security technologies like Security Information and Event Management (SIEM), pen-testing, vulnerability assessment and security data analytics can be used in the context of integrated Critical Infrastructure Protection. The novel methods and techniques of the book are exemplified in case studies involving critical infrastructures in four industrial sectors, namely finance, healthcare, energy and communications. The peculiarities of critical infrastructure protection in each one of these sectors is discussed and addressed based on sector-specific solutions. The advent of the fourth industrial revolution (Industry 4.0) is expected to increase the cyber-physical nature of critical infrastructures as well as their interconnection in the scope of sectorial and cross-sector value chains. Therefore, the demand for solutions that foster the interplay between cyber and physical security, and enable Cyber-Physical Threat Intelligence is likely to explode. In this book, we have shed light on the structure of such integrated security systems, as well as on the technologies that will underpin their operation. We hope that Security and Critical Infrastructure Protection stakeholders will find the book useful when planning their future security strategies

Automating Security Risk and Requirements Management for Cyber-Physical Systems

Cyber-physische Systeme ermöglichen zahlreiche moderne Anwendungsfälle und Geschäftsmodelle wie vernetzte Fahrzeuge, das intelligente Stromnetz (Smart Grid) oder das industrielle Internet der Dinge. Ihre Schlüsselmerkmale Komplexität, Heterogenität und Langlebigkeit machen den langfristigen Schutz dieser Systeme zu einer anspruchsvollen, aber unverzichtbaren Aufgabe. In der physischen Welt stellen die Gesetze der Physik einen festen Rahmen für Risiken und deren Behandlung dar. Im Cyberspace gibt es dagegen keine vergleichbare Konstante, die der Erosion von Sicherheitsmerkmalen entgegenwirkt. Hierdurch können sich bestehende Sicherheitsrisiken laufend ändern und neue entstehen. Um Schäden durch böswillige Handlungen zu verhindern, ist es notwendig, hohe und unbekannte Risiken frühzeitig zu erkennen und ihnen angemessen zu begegnen. Die Berücksichtigung der zahlreichen dynamischen sicherheitsrelevanten Faktoren erfordert einen neuen Automatisierungsgrad im Management von Sicherheitsrisiken und -anforderungen, der über den aktuellen Stand der Wissenschaft und Technik hinausgeht. Nur so kann langfristig ein angemessenes, umfassendes und konsistentes Sicherheitsniveau erreicht werden. Diese Arbeit adressiert den dringenden Bedarf an einer Automatisierungsmethodik bei der Analyse von Sicherheitsrisiken sowie der Erzeugung und dem Management von Sicherheitsanforderungen für Cyber-physische Systeme. Das dazu vorgestellte Rahmenwerk umfasst drei Komponenten: (1) eine modelbasierte Methodik zur Ermittlung und Bewertung von Sicherheitsrisiken; (2) Methoden zur Vereinheitlichung, Ableitung und Verwaltung von Sicherheitsanforderungen sowie (3) eine Reihe von Werkzeugen und Verfahren zur Erkennung und Reaktion auf sicherheitsrelevante Situationen. Der Schutzbedarf und die angemessene Stringenz werden durch die Sicherheitsrisikobewertung mit Hilfe von Graphen und einer sicherheitsspezifischen Modellierung ermittelt und bewertet. Basierend auf dem Modell und den bewerteten Risiken werden anschließend fundierte Sicherheitsanforderungen zum Schutz des Gesamtsystems und seiner Funktionalität systematisch abgeleitet und in einer einheitlichen, maschinenlesbaren Struktur formuliert. Diese maschinenlesbare Struktur ermöglicht es, Sicherheitsanforderungen automatisiert entlang der Lieferkette zu propagieren. Ebenso ermöglicht sie den effizienten Abgleich der vorhandenen Fähigkeiten mit externen Sicherheitsanforderungen aus Vorschriften, Prozessen und von Geschäftspartnern. Trotz aller getroffenen Maßnahmen verbleibt immer ein gewisses Restrisiko einer Kompromittierung, worauf angemessen reagiert werden muss. Dieses Restrisiko wird durch Werkzeuge und Prozesse adressiert, die sowohl die lokale und als auch die großräumige Erkennung, Klassifizierung und Korrelation von Vorfällen verbessern. Die Integration der Erkenntnisse aus solchen Vorfällen in das Modell führt häufig zu aktualisierten Bewertungen, neuen Anforderungen und verbessert weitere Analysen. Abschließend wird das vorgestellte Rahmenwerk anhand eines aktuellen Anwendungsfalls aus dem Automobilbereich demonstriert.Cyber-Physical Systems enable various modern use cases and business models such as connected vehicles, the Smart (power) Grid, or the Industrial Internet of Things. Their key characteristics, complexity, heterogeneity, and longevity make the long-term protection of these systems a demanding but indispensable task. In the physical world, the laws of physics provide a constant scope for risks and their treatment. In cyberspace, on the other hand, there is no such constant to counteract the erosion of security features. As a result, existing security risks can constantly change and new ones can arise. To prevent damage caused by malicious acts, it is necessary to identify high and unknown risks early and counter them appropriately. Considering the numerous dynamic security-relevant factors requires a new level of automation in the management of security risks and requirements, which goes beyond the current state of the art. Only in this way can an appropriate, comprehensive, and consistent level of security be achieved in the long term. This work addresses the pressing lack of an automation methodology for the security-risk assessment as well as the generation and management of security requirements for Cyber-Physical Systems. The presented framework accordingly comprises three components: (1) a model-based security risk assessment methodology, (2) methods to unify, deduce and manage security requirements, and (3) a set of tools and procedures to detect and respond to security-relevant situations. The need for protection and the appropriate rigor are determined and evaluated by the security risk assessment using graphs and a security-specific modeling. Based on the model and the assessed risks, well-founded security requirements for protecting the overall system and its functionality are systematically derived and formulated in a uniform, machine-readable structure. This machine-readable structure makes it possible to propagate security requirements automatically along the supply chain. Furthermore, they enable the efficient reconciliation of present capabilities with external security requirements from regulations, processes, and business partners. Despite all measures taken, there is always a slight risk of compromise, which requires an appropriate response. This residual risk is addressed by tools and processes that improve the local and large-scale detection, classification, and correlation of incidents. Integrating the findings from such incidents into the model often leads to updated assessments, new requirements, and improves further analyses. Finally, the presented framework is demonstrated by a recent application example from the automotive domain

NLP-Based Techniques for Cyber Threat Intelligence

In the digital era, threat actors employ sophisticated techniques for which, often, digital traces in the form of textual data are available. Cyber Threat Intelligence~(CTI) is related to all the solutions inherent to data collection, processing, and analysis useful to understand a threat actor's targets and attack behavior. Currently, CTI is assuming an always more crucial role in identifying and mitigating threats and enabling proactive defense strategies. In this context, NLP, an artificial intelligence branch, has emerged as a powerful tool for enhancing threat intelligence capabilities. This survey paper provides a comprehensive overview of NLP-based techniques applied in the context of threat intelligence. It begins by describing the foundational definitions and principles of CTI as a major tool for safeguarding digital assets. It then undertakes a thorough examination of NLP-based techniques for CTI data crawling from Web sources, CTI data analysis, Relation Extraction from cybersecurity data, CTI sharing and collaboration, and security threats of CTI. Finally, the challenges and limitations of NLP in threat intelligence are exhaustively examined, including data quality issues and ethical considerations. This survey draws a complete framework and serves as a valuable resource for security professionals and researchers seeking to understand the state-of-the-art NLP-based threat intelligence techniques and their potential impact on cybersecurity

Symmetry-Adapted Machine Learning for Information Security

Symmetry-adapted machine learning has shown encouraging ability to mitigate the security risks in information and communication technology (ICT) systems. It is a subset of artificial intelligence (AI) that relies on the principles of processing future events by learning past events or historical data. The autonomous nature of symmetry-adapted machine learning supports effective data processing and analysis for security detection in ICT systems without the interference of human authorities. Many industries are developing machine-learning-adapted solutions to support security for smart hardware, distributed computing, and the cloud. In our Special Issue book, we focus on the deployment of symmetry-adapted machine learning for information security in various application areas. This security approach can support effective methods to handle the dynamic nature of security attacks by extraction and analysis of data to identify hidden patterns of data. The main topics of this Issue include malware classification, an intrusion detection system, image watermarking, color image watermarking, battlefield target aggregation behavior recognition model, IP camera, Internet of Things (IoT) security, service function chain, indoor positioning system, and crypto-analysis

Cyber Security and Critical Infrastructures

This book contains the manuscripts that were accepted for publication in the MDPI Special Topic "Cyber Security and Critical Infrastructure" after a rigorous peer-review process. Authors from academia, government and industry contributed their innovative solutions, consistent with the interdisciplinary nature of cybersecurity. The book contains 16 articles: an editorial explaining current challenges, innovative solutions, real-world experiences including critical infrastructure, 15 original papers that present state-of-the-art innovative solutions to attacks on critical systems, and a review of cloud, edge computing, and fog's security and privacy issues