A shared cyber threat intelligence solution for SMEs

Small- and medium-sized enterprises (SMEs) frequently experience cyberattacks, but often do not have the means to counter these attacks. Therefore, cybersecurity researchers and practitioners need to aid SMEs in their defence against cyber threats. Research has shown that SMEs require solutions that are automated and adapted to their context. In recent years, we have seen a surge in initiatives to share cyber threat intelligence (CTI) to improve collective cybersecurity resilience. Shared CTI has the potential to answer the SME call for automated and adaptable solutions. Sadly, as we demonstrate in this paper, current shared intelligence approaches scarcely address SME needs. We must investigate how shared CTI can be used to improve SME cybersecurity resilience. In this paper, we tackle this challenge using a systematic review to discover current state-of-the-art approaches to using shared CTI. We find that threat intelligence sharing platforms such as MISP have the potential to address SME needs, provided that the shared intelligence is turned into actionable insights. Based on this observation, we developed a prototype application that processes MISP data automatically, prioritises cybersecurity threats for SMEs, and provides SMEs with actionable recommendations tailored to their context. Subsequent evaluations in operational environments will help to improve our application, such that SMEs are enabled to thwart cyberattacks in future.Public Health and primary carePrevention, Population and Disease management (PrePoD

A comparative analysis of cyber-threat intelligence sources, formats and languages

The sharing of cyber-threat intelligence is an essential part of multi-layered tools used to protect systems and organisations from various threats. Structured standards, such as STIX, TAXII and CybOX, were introduced to provide a common means of sharing cyber-threat intelligence and have been subsequently much-heralded as the de facto industry standards. In this paper, we investigate the landscape of the available formats and languages, along with the publicly available sources of threat feeds, how these are implemented and their suitability for providing rich cyber-threat intelligence. We also analyse at a sample of cyber-threat intelligence feeds, the type of data they provide and the issues found in aggregating and sharing the data. Moreover, the type of data supported by various formats and languages is correlated with the data needs for several use cases related to typical security operations. The main conclusions drawn by our analysis suggest that many of the standards have a poor level of adoption and implementation, with providers opting for custom or traditional simple formats

Cyber Threat Intelligence Exchange

The processing and exchange of Cyber Threat Intelligence (CTI) has become an increas- ingly important topic in recent years. This trend can be attributed to various factors. On the one hand, the exchange of information offers great potential to strengthen the knowledge base of companies and thus improve their protection against cyber threats. On the other hand, legislators in various countries have recognized this potential and translated it into legal reporting requirements. However, CTI is still a very young research area with only a small body of literature. Hence, there are hardly any guidelines, uniform standards, or specifications that define or support such an exchange. This dissertation addresses the problem by reviewing the methodological foundations for the exchange of threat intelligence in three focal areas. First, the underlying data formats and data structures are analyzed, and the basic methods and models are developed. In the further course of the work, possibilities for integrating humans into the analysis process of security incidents and into the generation of CTI are investigated. The final part of the work examines possible obstacles in the exchange of CTI. Both the legal environment and mechanisms to create incentives for an exchange are studied. This work thus creates a solid basis and a structured framework for the cooperative use of CTI

Розробка структури блокчейн-сховища для індикаторів компрометації в розподіленій системі обміну загрозами

Завданням роботи є розробка архітектури розподіленої системи обміну IoC та створення порівняльних характеристик технологій для реалізації архітектурних елементів. Мета цієї дипломної роботи полягає у створенні системи для ефективного зберігання та обміну індикаторами компрометації. Об’єктом дослідження є архітектура розподіленої системи обміну індикаторами компрометації з блокчейн сховищем для IoC. Предметом дослідження є можливість ефективного збереження та обміну чутливими даними, таким як IoC.The task of the work is to develop the architecture of a distributed IoC exchange system and create comparative characteristics of the technology for the implementation of architectural elements, such as databases or blockchains. The purpose of this graduate work is to create a system for effective storage and exchange of indicators of compromise. The object of research is the architecture of a distributed system of exchange of compromise indicators with blockchain storage for IoC. The subject of the study is the ability to efficiently store and exchange sensitive data such as IoC

Managing Big Data for Addressing Research Questions in a Collaborative Project on Automated Driving Impact Assessment

While extracting meaningful information from big data is getting relevance, literature lacks information on how to handle sensitive data by different project partners in order to collectively answer research questions (RQs), especially on impact assessment of new automated driving technologies. This paper presents the application of an established reference piloting methodology and the consequent development of a coherent, robust workflow. Key challenges include ensuring methodological soundness and data validity while protecting partners’ intellectual property. The authors draw on their experiences in a 34-partner project aimed at assessing the impact of advanced automated driving functions, across 10 European countries. In the first step of the workflow, we captured the quantitative requirements of each RQ in terms of the relevant data needed from the tests. Most of the data come from vehicular sensors, but subjective data from questionnaires are processed as well. Next, we set up a data management process involving several partners (vehicle manufacturers, research institutions, suppliers and developers), with different perspectives and requirements. Finally, we deployed the system so that it is fully integrated within the project big data toolchain and usable by all the partners. Based on our experience, we highlight the importance of the reference methodology to theoretically inform and coherently manage all the steps of the project and the need for effective and efficient tools, in order to support the everyday work of all the involved research teams, from vehicle manufacturers to data analysts

Harnessing Human Potential for Security Analytics

Humans are often considered the weakest link in cybersecurity. As a result, their potential has been continuously neglected. However, in recent years there is a contrasting development recognizing that humans can benefit the area of security analytics, especially in the case of security incidents that leave no technical traces. Therefore, the demand becomes apparent to see humans not only as a problem but also as part of the solution. In line with this shift in the perception of humans, the present dissertation pursues the research vision to evolve from a human-as-a-problem to a human-as-a-solution view in cybersecurity. A step in this direction is taken by exploring the research question of how humans can be integrated into security analytics to contribute to the improvement of the overall security posture. In addition to laying foundations in the field of security analytics, this question is approached from two directions. On the one hand, an approach in the context of the human-as-a-security-sensor paradigm is developed which harnesses the potential of security novices to detect security incidents while maintaining high data quality of human-provided information. On the other hand, contributions are made to better leverage the potential of security experts within a SOC. Besides elaborating the current state in research, a tool for determining the target state of a SOC in the form of a maturity model is developed. Based on this, the integration of security experts was improved by the innovative application of digital twins within SOCs. Accordingly, a framework is created that improves manual security analyses by simulating attacks within a digital twin. Furthermore, a cyber range was created, which offers a realistic training environment for security experts based on this digital twin

Secure Information Sharing with Distributed Ledgers

In 2009, blockchain technology was first introduced as the supporting database technology for digital currencies. Since then, more advanced derivations of the technology have been developed under the broader term Distributed Ledgers, with improved scalability and support for general-purpose application logic. As a distributed database, they are able to support interorganizational information sharing while assuring desirable information security attributes like non-repudiation, auditability and transparency. Based on these characteristics, researchers and practitioners alike have begun to identify a plethora of disruptive use cases for Distributed Ledgers in existing application domains. While these use cases are promising significant efficiency improvements and cost reductions, practical adoption has been slow in the past years. This dissertation focuses on improving three aspects contributing to slow adoption. First, it attempts to identify application areas and substantiated use cases where Distributed Ledgers can considerably advance the security of information sharing. Second, it considers the security aspects of the technology itself, identifying threats to practical applications and detection approaches for these threats. And third, it investigates success factors for successful interorganizational collaborations using Distributed Ledgers

Ausgewählte Chancen und Herausforderungen der digitalen Transformation für die Produktentwicklung und Unternehmensorganisation im Finanzdienstleistungssektor

Vor dem Hintergrund der digitalen Transformation sind Finanzdienstleistungsunternehmen auf unterschiedlichen Ebenen zahlreichen Chancen sowie Herausforderungen ausgesetzt. Während der Einsatz neuer Technologien die Optimierung bestehender Geschäftsprozesse sowie das Angebot digitalisierter Finanzdienstleistungen ermöglicht, geht dies zugleich mit veränderten Arbeitsbedingungen innerhalb der Unternehmensorganisation einher. Darüber hinaus sind Finanzdienstleister dazu angehalten die sich ändernden Kundenerwartungen bei den bisherigen Geschäftsaktivitäten sowie bei der Produktentwicklung zu berücksichtigen. Das Ziel der vorliegenden kumulativen Dissertation ist es, bestehende Forschungsdesiderate hinsichtlich der Auswirkungen der digitalen Transformation auf den Finanzdienstleistungssektor, differenziert nach der Kunden- und Produktperspektive sowie der internen Unternehmensperspektive, vertiefend zu analysieren. Das Technology-Organization-Environment (TOE)-Framework von DePietro et al. (1990) wird dabei als theoretischer Rahmen zur Einordnung und Strukturierung der Forschungsmodule verwendet. Die Ergebnisse der acht Module zeigen, dass die Kundenbedürfnisse und –erwartungen im Finanzdienstleistungssektor verstärkt von der digitalen Transformation beeinflusst werden. Dies zeigt sich in der Beratungstätigkeit bspw. durch das Angebot neuer Kundenkanäle sowie der aus dem steigenden Wettbewerbsdruck resultierenden erhöhten Preistransparenz. Im Rahmen der Produktentwicklung sind zudem u. a. ESG-Risiken und Silent Cyber-Risiken zu beachten. Aus der Analyse der Auswirkungen der digitalen Transformation auf die Unternehmensorganisation geht hervor, dass über den Einsatz digitaler Innovationen innerhalb des Backoffice die Realisation von Effizienzgewinnen sowie das Entgegenwirken eines Personalmangels möglich ist. Darüber hinaus wird in den Modulen der Einfluss des Faktors Mensch auf die Cyber-Sicherheit hervorgehoben. Während dieser einerseits als „schwächstes Glied“ und potenzielles Angriffsziel im Sicherheitskonstrukt der Unternehmen dargestellt wird, ist andererseits das Potenzial der Beschäftigten zur Frühwarnung zu berücksichtigen

Applications in Electronics Pervading Industry, Environment and Society

This book features the manuscripts accepted for the Special Issue “Applications in Electronics Pervading Industry, Environment and Society—Sensing Systems and Pervasive Intelligence” of the MDPI journal Sensors. Most of the papers come from a selection of the best papers of the 2019 edition of the “Applications in Electronics Pervading Industry, Environment and Society” (APPLEPIES) Conference, which was held in November 2019. All these papers have been significantly enhanced with novel experimental results. The papers give an overview of the trends in research and development activities concerning the pervasive application of electronics in industry, the environment, and society. The focus of these papers is on cyber physical systems (CPS), with research proposals for new sensor acquisition and ADC (analog to digital converter) methods, high-speed communication systems, cybersecurity, big data management, and data processing including emerging machine learning techniques. Physical implementation aspects are discussed as well as the trade-off found between functional performance and hardware/system costs