Biblio

Information systems, networks, and technologies have become an integral part of modern critical control systems that manage many of today’s critical infrastructures. The continuous operation, maintenance, and protection of critical infrastructures have become a high national priority for governments around the world because our society heavily depends on them for most of our daily activities (travel, power usage, banking transactions, telecommunications, etc) and safety. It is therefore critical that these infrastructures have to be protected from potential accidental incidents or cyberattacks. We present the fundamental architectural components of critical control systems which manage most critical infrastructures. We identify some of the vulnerabilities and threats to modern critical control systems followed by protection solutions that can be deployed to mitigate attacks exploiting these vulnerabilities.

The protection of critical user-centric applications, such as Smart Grids and their monitoring systems, has become one of the most cutting-edge research areas in recent years. The dynamic complexity of their cyber-physical systems (CPSs) and their strong inter-dependencies with power systems, are bringing about a significant increase in security problems that may be exploited by attackers. These security holes may, for example, trigger the disintegration of the structural controllability properties due to the problem of non-locality, affecting, sooner or later, the provision of the essential services to end-users. One way to address these situations could be through automatic checkpoints in charge of inspecting the healthy status of the control network and its critical nature. This inspection can be subject to special mechanisms composed of trustworthy cyberphysical elements capable of detecting structural changes in the control and activating restoration procedures with support for warning. This is precisely the aim of this paper, which presents a CPSs-based checkpoint model with the capacity to manage heterogeneous replications that help ensure data redundancy, thereby guaranteeing the validity of the checkpoints. As a support to this study, a theoretical and practical analysis is addressed to show the functionality of the approach in real contexts.

Abstract Cyber-physical systems (CPSs), integrated in critical infrastructures, could provide the minimal services that traditional situational awareness (SA) systems demand. However, their application in SA solutions for the protection of large control distributions against unforeseen faults may be insufficient. Dynamic protection measures have to be provided not only to locally detect unplanned deviations but also to prevent, respond, and restore from these deviations. The provision of these services as an integral part of the SA brings about a new research field known as wide-area situational awareness (WASA), highly dependent on CPSs for control from anywhere across multiple interconnections, and at any time. Thus, we review the state-of-the art of this new paradigm, exploring the different preventive and corrective measures considering the heterogeneity of CPSs, resulting in a guideline for the construction of automated WASA systems.

Critical infrastructures play a vital role in supporting modern society. The reliability, performance, continuous operation, safety, maintenance and protection of critical infrastructures are national priorities for countries around the world. This paper explores the vulnerabilities and threats facing modern critical infrastructures with special emphasis on industrial control systems, and describes a number of protection measures. The paper also discusses some of the challenging areas related to critical infrastructure protection such as governance and security management, secure network architectures, self-healing, modeling and simulation, wide-area situational awareness, forensics and learning, and trust management and privacy.

Industry 4.0 advent opens several cyber-threats scenarios originally designed for classic information technology, drawing the attention to the serious risks for the modern industrial control networks. To cope with this problem, in this paper we address the security issues related to covert channels applied to industrial networks, identifying the new vulnerability points when information technologies converge with operational technologies such as edge computing infrastructures. Specifically, we define two signaling strategies where we exploit the Modbus/TCP protocol as target to set up a covert channel. Once the threat channel is established, passive and active offensive attacks (i.e. data exfiltration and command an control, respectively) are further exploited by implementing and testing them on a real Industrial Internet of Things testbed. The experimental results highlight the potential damage of such specific threats, and the easy extrapolation of the attacks to other types of channels in order to show the new risks for Industry 4.0. Related to this, we discuss some countermeasures to offer an overview of possible mitigation and defense measures.
 

Anomaly-based detection applied in strongly interdependent systems, like Smart Grids, has become one of the most challenging research areas in recent years. Early detection of anomalies so as to detect and prevent unexpected faults or stealthy threats is attracting a great deal of attention from the scientific community because it offers potential solutions for context-awareness. These solutions can also help explain the conditions leading up to a given situation and help determine the degree of its severity. However, not all the existing approaches within the literature are equally effective in covering the needs of a particular scenario. It is necessary to explore the control requirements of the domains that comprise a Smart Grid, identify, and even select, those approaches according to these requirements and the intrinsic conditions related to the application context, such as technological heterogeneity and complexity. Therefore, this paper analyses the functional features of existing anomaly-based approaches so as to adapt them, according to the aforementioned conditions. The result of this investigation is a guideline for the construction of preventive solutions that will help improve the context-awareness in the control of Smart Grid domains in the near future.