Biblio

Critical infrastructure is a key area in cybersecurity. In the U.S., it was front and center in 1997 with the report from the President’s Commission on Critical Infrastructure Protection (PCCIP), and now affects countries worldwide. Critical Infrastructure Protection must address all types of cybersecurity threats - insider threat, ransomware, supply chain risk management issues, and so on. Unsurprisingly, in the past 25 years, the risks and incidents have increased rather than decreased and appear in the news daily. As an important component of critical infrastructure protection, secure supply chain risk management must be integrated into development projects. Both areas have important implications for security requirements engineering.

Modern power systems today are protected and controlled increasingly by embedded systems of computing technologies with a great degree of collaboration enabled by communication. Energy cyber-physical systems such as power systems infrastructures are increasingly vulnerable to cyber-attacks on the protection and control layer. We present a method of securing protective relays from malicious change in protective relay settings via collaboration of devices. Each device checks the proposed setting changes of its neighboring devices for consistency and coordination with its own settings using setting rules based on relay coordination principles. The method is enabled via peer-to-peer communication between IEDs. It is validated in a cyber-physical test bed containing a real time digital simulator and actual relays that communicate via IEC 61850 GOOSE messages. Test results showed improvement in cyber physical security by using domain based rules to block malicious changes in protection settings caused by simulated cyber-attacks. The method promotes the use of defense systems that are aware of the physical systems which they are designed to secure.

Cyber-Physical Systems (CPSs) interconnect the physical world with digital computers and networks in order to automate production and distribution processes. Nowadays, most CPSs do not work in isolation, but their digital part is connected to the Internet in order to enable remote monitoring, control and configuration. Such a connection may offer entry-points enabling attackers to gain control silently and exploit access to the physical world at the right time to cause service disruption and possibly damage to the surrounding environment. Prevention and monitoring measures can reduce the risk brought by cyber attacks, but the residual risk can still be unacceptably high in critical infrastructures or services. Resilience - i.e., the ability of a system to withstand adverse events while maintaining an acceptable functionality - is therefore a key property for such systems. In our research, we seek a model-free, quantitative, and general-purpose evaluation methodology to extract resilience indexes from, e.g., system logs and process data. While a number of resilience metrics have already been put forward, little experimental evidence is available when it comes to the cyber security of CPSs. By using the model of a real wastewater treatment plant, and simulating attacks that tamper with a critical feedback control loop, we provide a comparison between four resilience indexes selected through a thorough literature review involving over 40 papers. Our results show that the selected indexes differ in terms of behavior and sensitivity with respect to specific attacks, but they can all summarize and extract meaningful information from bulky system logs. Our evaluation includes an approach for extracting performance indicators from observed variables which does not require knowledge of system dynamics; and a discussion about combining resilience indexes into a single system-wide measure is included. 11The authors wish to thank Leonardo S.p.A. for its financial support. The research herein presented is partially supported by project NEFERIS awarded by the Italian Ministry of Defense to Leonardo S.p.A. in partnership with the University of Genoa. This work received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 830892 for project SPARTA.

Protecting critical infrastructure from cyberattacks by other nations is a matter of considerable concern. Can deterrence play a role in such protection? Can lessons from nuclear deterrence-the most elaborated and successful version of deterrence-be adapted to the cyber case? Currently, little overlap exists between the two, although that might change in the aftermath of an extensive, destructive cyberattack. The most effective way to protect the cyber-dependent infrastructure is a comprehensive defense (deterrence by denial), which was impractical in the nuclear regime. However, this approach presents challenges. Existing legal norms, particularly those related to controlling collateral damage, might provide some deterrence. Another option might be a new international agreement, but that would involve several difficult issues.

This paper presents a control strategy for Cyber-Physical System defense developed in the framework of the European Project ATENA, that concerns Critical Infrastructure (CI) protection. The aim of the controller is to find the optimal security configuration, in terms of countermeasures to implement, in order to address the system vulnerabilities. The attack/defense problem is modeled as a multi-agent general sum game, where the aim of the defender is to prevent the most damage possible by finding an optimal trade-off between prevention actions and their costs. The problem is solved utilizing Reinforcement Learning and simulation results provide a proof of the proposed concept, showing how the defender of the protected CI is able to minimize the damage caused by his her opponents by finding the Nash equilibrium of the game in the zero-sum variant, and, in a more general scenario, by driving the attacker in the position where the damage she/he can cause to the infrastructure is lower than the cost it has to sustain to enforce her/his attack strategy.

Airports are at the forefront of technological innovation, mainly due to the fact that the number of air travel passengers is exponentially increasing every year. As a result, airports enhance infrastructure's intelligence and evolve as smart facilities to support growth, by offering a pleasurable travel experience, which plays a vital role in increasing revenue of aviation sector. New challenges are coming up, which aviation has to deal and adapt, such as the integration of Industrial IoT in airport facilities and the increased use of Bring Your Own Device from travelers and employees. Cybersecurity is becoming a key enabler for safety, which is paramount in the aviation context. Smart airports strive to provide optimal services in a reliable and sustainable manner, by working around the domains of growth, efficiency, safety andsecurity. This paper researches the implementation rate of cybersecurity measures and best practices to improve airports cyber resilience. With the aim to enhance operational practices anddevelop robust cybersecurity governance in smart airports, we analyze security gaps in different areas including technical, organizational practices and policies.

Protecting Critical Infrastructures (CIs) against contemporary cyber attacks has become a crucial as well as complex task. Modern attack campaigns, such as Advanced Persistent Threats (APTs), leverage weaknesses in the organization's business processes and exploit vulnerabilities of several systems to hit their target. Although their life-cycle can last for months, these campaigns typically go undetected until they achieve their goal. They usually aim at performing data exfiltration, cause service disruptions and can also undermine the safety of humans. Novel detection techniques and incident handling approaches are therefore required, to effectively protect CI's networks and timely react to this type of threats. Correlating large amounts of data, collected from a multitude of relevant sources, is necessary and sometimes required by national authorities to establish cyber situational awareness, and allow to promptly adopt suitable countermeasures in case of an attack. In this paper we propose three novel methods for security information correlation designed to discover relevant insights and support the establishment of cyber situational awareness.

Ensuring system survivability in the wake of advanced persistent threats is a big challenge that the security community is facing to ensure critical infrastructure protection. In this paper, we define metrics and models for the assessment of coordinated massive malware campaigns targeting critical infrastructure sectors. First, we develop an analytical model that allows us to capture the effect of neighborhood on different metrics (infection probability and contagion probability). Then, we assess the impact of putting operational but possibly infected nodes into quarantine. Finally, we study the implications of scanning nodes for early detection of malware (e.g., worms), accounting for false positives and false negatives. Evaluating our methodology using a small four-node topology, we find that malware infections can be effectively contained by using quarantine and appropriate rates of scanning for soft impacts.