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  • 1.
    Süren, Emre
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Heiding, Fredrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Olegård, Johannes
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Lagerström, Robert
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    PatrIoT: practical and agile threat research for IoT2023In: International Journal of Information Security, ISSN 1615-5262, E-ISSN 1615-5270, Vol. 22, no 1, p. 213-233Article in journal (Refereed)
    Abstract [en]

    The Internet of things (IoT) products, which have been widely adopted, still pose challenges in the modern cybersecurity landscape. Many IoT devices are resource-constrained and almost constantly online. Furthermore, the security features of these devices are less often of concern, and fewer methods, standards, and guidelines are available for testing them. Although a few approaches are available to assess the security posture of IoT products, the ones in use are mostly based on traditional non-IoT-focused techniques and generally lack the attackers' perspective. This study provides a four-stage IoT vulnerability research methodology built on top of four key elements: logical attack surface decomposition, compilation of top 100 weaknesses, lightweight risk scoring, and step-by-step penetration testing guidelines. Our proposed methodology is evaluated with multiple IoT products. The results indicate that PatrIoT allows cyber security practitioners without much experience to advance vulnerability research activities quickly and reduces the risk of critical IoT penetration testing steps being overlooked.

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    PatrIoT
  • 2.
    Heiding, Fredrik
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Süren, Emre
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Olegård, Johannes
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering. Stockholm Univ, Stockholm, Sweden..
    Lagerström, Robert
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Penetration testing of connected households2023In: Computers & security (Print), ISSN 0167-4048, E-ISSN 1872-6208, Vol. 126, article id 103067Article in journal (Refereed)
    Abstract [en]

    Connected devices have become an integral part of modern homes and household devices, such as vac-uum cleaners and refrigerators, are now often connected to networks. This connectivity introduces an entry point for cyber attackers. The plethora of successful cyber attacks against household IoT indicates that the security of these devices, or the security of applications related to these devices, is often lacking. Existing penetration testing studies usually focus on individual devices, and recent studies often men-tion the need for more extensive vulnerability assessments. Therefore, this study investigates the cyber security of devices commonly located in connected homes. Systematic penetration tests were conducted on 22 devices in five categories related to connected homes: smart door locks, smart cameras, smart car adapters/garages, smart appliances, and miscellaneous smart home devices. In total, 17 vulnerabilities were discovered and published as new CVEs. Some CVEs received critical severity rankings from the National Vulnerability Database (NVD), reaching 9.8/10. The devices are already being sold and used worldwide, and the discovered vulnerabilities could lead to severe consequences for residents, such as an attacker gaining physical access to the house. In addition to the published CVEs, 52 weaknesses were discovered that could potentially lead to new CVEs in the future. To our knowledge, this is the most comprehensive study on penetration testing of connected household products.

  • 3.
    Heiding, Fredrik
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Katsikeas, Sotirios
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Lagerström, Robert
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Research communities in cyber security vulnerability assessments: A comprehensive literature review2023In: Computer Science Review, ISSN 1574-0137, E-ISSN 1876-7745, Vol. 48, article id 100551Article, review/survey (Refereed)
    Abstract [en]

    Ethical hacking and vulnerability assessments are gaining rapid momentum as academic fields of study. Still, it is sometimes unclear what research areas are included in the categories and how they fit into the traditional academic framework. Previous studies have reviewed literature in the field, but the attempts use manual analysis and thus fail to provide a comprehensive view of the domain. To better understand how the area is treated within academia, 537,629 related articles from the Scopus database were analyzed. A Python script was used for data mining as well as analysis of the data, and 23,459 articles were included in the final synthesis. The publication dates of the articles ranged from 1975 to 2022. They were authored by 53,495 authors and produced an aggregated total of 836,956 citations. Fifteen research communities were detected using the Louvain community detection algorithm: (smart grids, attack graphs, security testing, software vulnerabilities, Internet of Things (IoT), network vulnerability, vulnerability analysis, Android, cascading failures, authentication, Software-Defined Networking (SDN), spoofing attacks, malware, trust models, and red teaming). In addition, each community had several individual subcommunities, constituting a total of 126. From the trends of the analyzed studies, it is clear that research interest in ethical hacking and vulnerability assessment is increasing.

  • 4.
    Wester, Philip
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Heiding, Fredrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Lagerström, Robert
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Anomaly-based Intrusion Detection using Tree Augmented Naive Bayes2021In: International Workshop on Enterprise Distributed Object Computing, EDOCW, IEEE, 2021Conference paper (Refereed)
    Abstract [en]

    Information technology is continuously becoming a more central part of society and together with the increased connectivity and inter-dependency of devices, it is becoming more important to keep systems secure. Most modern enterprises use some form of intrusion detection in order to detect hostile cyber activity that enters the organization. One of the major challenges of intrusion detection in computer networks is to detect types of intrusions that have previously not been encountered. These unknown intrusions are generally detected by methods collectively called anomaly detection. It is nowadays popular to use various artificial intelligence schemes to enhance anomaly detection of network traffic, and many state-of-the-art models reach a detection rate of well over 99%. One such promising algorithm is the Tree Augmented Naive Bayes (TAN) Classifier. However, it is crucial to implement TAN correctly in order to benefit from its full performance. This study implements a TAN classifier for anomaly based intrusion detection of computer network traffic, and displays practical insights on how to maximize its performance. The algorithm is implemented in two data sets with data from simulated cyber attacks: NSL-KDD and UNSW-NB15. We contribute to the field by validating the usefulness of TAN for anomaly detection in computer networks, as well as providing practical insights to new practitioners who want to utilize TAN in intrusion detection systems.

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    fulltext
  • 5.
    Välja, Margus
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Heiding, Fredrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Franke, Ulrik
    RISE Research Institutes of Sweden, Kista, 164 40, Sweden.
    Lagerström, Robert
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Automating threat modeling using an ontology framework: Validated with data from critical infrastructures2020In: Cybersecurity, E-ISSN 2523-3246, Vol. 3, no 1Article in journal (Refereed)
    Abstract [en]

    Threat modeling is of increasing importance to IT security, and it is a complex and resource demanding task. The aim of automating threat modeling is to simplify model creation by using data that are already available. However, the collected data often lack context; this can make the automated models less precise in terms of domain knowledge than those created by an expert human modeler. The lack of domain knowledge in modeling automation can be addressed with ontologies. In this paper, we introduce an ontology framework to improve automatic threat modeling. The framework is developed with conceptual modeling and validated using three different datasets: a small scale utility lab, water utility control network, and university IT environment. The framework produced successful results such as standardizing input sources, removing duplicate name entries, and grouping application software more logically.

    Download full text (pdf)
    fulltext
  • 6.
    Heiding, Fredrik
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Lagerström, Robert
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Ethical Principles for Designing Responsible Offensive Cyber Security Training2020In: Privacy and Identity 2020, 2020, p. 21-39Conference paper (Refereed)
    Abstract [en]

    In this paper we present five principles for designing ethically responsible offensive cyber security training. The principles can be implemented in existing or new study plans and target both academic and non-academic courses. Subject matter experts within various cyber security domains were consulted to validate and fine tune the principles, together with a literature review of ethical studies in related domains. The background for designing the principles is the continuous popularity of offensive cyber security (penetration testing, ethical hacking). Offensive cyber security means actively trying to break or compromise a system in order to find its vulnerabilities. If this expertise is placed in the wrong hands, the person can cause severe damage to organizations, civilians and society at large. The proposed ethical principles are created in order to mitigate these risks while maintaining the upsides of offensive cyber security. This is achieved by incorporating the ethical principles in offensive cyber security training, in order to facilitate the practitioners with ethical knowledge of how and when to use their acquired expertise.

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    fulltext
  • 7.
    Heiding, Fredrik
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Lagerström, Robert
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Wallström, Andreas
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Omer, Mohammad-Ali
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
    Securing IoT Devices using Geographic and Continuous Login Blocking: A Honeypot Study2020In: Proceedings of the 6th International Conference on Information Systems Security and Privacy 2020, INSTICC , 2020, p. 424-431Conference paper (Refereed)
    Abstract [en]

    IoT (Internet of Things) devices have grown exponentially in the last years, both in the sheer number of devices and concerning areas of applications being introduced. Together with this rapid development we are faced with an increased need for IoT Security. Devices that have previously been analogue, such as refrigerators, door locks, and cars are now turning digital and are exposed to the threats posed by an Internet connection. This paper investigates how two existing security features (geographic IP Blocking with GeoIP and rate-limited connections with fail2ban) can be used to enhance the security of IoT devices. We analyze the success of each method by comparing units with and without the security features, collecting and comparing data about the received attacks for both kinds. The result shows that the GeoIP security feature can reduce attacks by roughly 93% and fail2ban by up to 99%. Further work in the field is encouraged to validate our findings, create better GeoIP tools, and to better understand the potential of the security techniques at a larger scale. The security features are implemented in aws instances made to simulate IoT devices, and measured with honeypots and IDSs (Intrusion Detection Systems) that collect data from the received attacks. The research is made as a fundamental work to later be extended by implementing the security features in more devices, such as single board computers that will simulate IoT devies even more accurately.

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    fulltext
1 - 7 of 7
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