Iñaki Garitano

Ángel Longueira-Romero, Rosa Iglesias, Jose Luis Flores et al.

Industrial components are of high importance because they control critical infrastructures that form the lifeline of modern societies. However, the rapid evolution of industrial components, together with the new paradigm of Industry 4.0, and the new connectivity features that will be introduced by the 5G technology, all increase the likelihood of security incidents. These incidents are caused by the vulnerabilities present in these devices. In addition, although international standards define tasks to assess vulnerabilities, they do not specify any particular method. Having a secure design is important, but is also complex, costly, and an extra factor to manage during the lifespan of the device. This paper presents a model to analyze the known vulnerabilities of industrial components over time. The proposed model is based on two main elements: a directed graph representation of the internal structure of the component, and a set of quantitative metrics that are based on international security standards; such as, the Common Vulnerability Scoring System (CVSS). This model is applied throughout the entire lifespan of a device to track vulnerabilities, identify new requirements, root causes, and test cases. The proposed model also helps to prioritize patching activities. To test its potential, the proposed model is applied to the OpenPLC project. The results show that most of the root causes of these vulnerabilities are related to memory buffer operations and are concentrated in the \textit{libssl} library. Consequently, new requirements and test cases were generated from the obtained data.

Ángel Longueira-Romero, Rosa Iglesias, David Gonzalez et al.

Embedded Systems (ES) development has been historically focused on functionality rather than security, and today it still applies in many sectors and applications. However, there is an increasing number of security threats over ES, and a successful attack could have economical, physical or even human consequences, since many of them are used to control critical applications. A standardized and general accepted security testing framework is needed to provide guidance, common reporting forms, and the possibility to compare the results along the time. This can be achieved by introducing security metrics into the evaluation or assessment process. If carefully designed and chosen, metrics could provide a quantitative, repeatable and reproducible value that would reflect the level of security protection of the ES. This paper analyzes the features that a good security metric should exhibit, introduces a taxonomy for classifying them, and finally, it carries out a literature survey on security metrics for the security evaluation of ES. In this review, more than 500 metrics were collected and analyzed. Then, they were reduced to 169 metrics that have the potential to be applied to ES security evaluation. As expected, the 77.5 % of them is related exclusively to software, and only the 0.6 % of them addresses exclusively hardware security. This work aims to lay the foundations for constructing a security evaluation methodology that uses metrics to quantify the security level of an ES.

Mikel Iturbe, José Camacho, Iñaki Garitano et al.

Process Control Systems (PCSs) are the operating core of Critical Infrastructures (CIs). As such, anomaly detection has been an active research field to ensure CI normal operation. Previous approaches have leveraged network level data for anomaly detection, or have disregarded the existence of process disturbances, thus opening the possibility of mislabelling disturbances as attacks and vice versa. In this paper we present an anomaly detection and diagnostic system based on Multivariate Statistical Process Control (MSPC), that aims to distinguish between attacks and disturbances. For this end, we expand traditional MSPC to monitor process level and controller level data. We evaluate our approach using the Tennessee-Eastman process. Results show that our approach can be used to distinguish disturbances from intrusions to a certain extent and we conclude that the proposed approach can be extended with other sources of data for improving results.