33,931 research outputs found
Electric Power Grid Resilience to Cyber Adversaries: State of the Art
© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
The smart electricity grids have been evolving to a more complex cyber-physical ecosystem of infrastructures with integrated communication networks, new carbon-free sources of powergeneratio n, advanced monitoring and control systems, and a myriad of emerging modern physical hardware
technologies. With the unprecedented complexity and heterogeneity in dynamic smart grid networks comes additional vulnerability to emerging threats such as cyber attacks. Rapid development and deployment of advanced network monitoring and communication systems on one hand, and the growing interdependence of the electric power grids to a multitude of lifeline critical infrastructures on the other, calls for holistic defense strategies to safeguard the power grids against cyber adversaries. In order to improve the resilience of the power grid against adversarial attacks and cyber intrusions, advancements should be sought on
detection techniques, protection plans, and mitigation practices in all electricity generation, transmission,
and distribution sectors. This survey discusses such major directions and recent advancements from a lens
of different detection techniques, equipment protection plans, and mitigation strategies to enhance the
energy delivery infrastructure resilience and operational endurance against cyber attacks. This undertaking
is essential since even modest improvements in resilience of the power grid against cyber threats could lead
to sizeable monetary savings and an enriched overall social welfare
Assessing and augmenting SCADA cyber security: a survey of techniques
SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability
Improving SIEM for critical SCADA water infrastructures using machine learning
Network Control Systems (NAC) have been used in many industrial processes. They aim to reduce the human factor burden and efficiently handle the complex process and communication of those systems. Supervisory control and data acquisition (SCADA) systems are used in industrial, infrastructure and facility processes (e.g. manufacturing, fabrication, oil and water pipelines, building ventilation, etc.) Like other Internet of Things (IoT) implementations, SCADA systems are vulnerable to cyber-attacks, therefore, a robust anomaly detection is a major requirement. However, having an accurate anomaly detection system is not an easy task, due to the difficulty to differentiate between cyber-attacks and system internal failures (e.g. hardware failures). In this paper, we present a model that detects anomaly events in a water system controlled by SCADA. Six Machine Learning techniques have been used in building and evaluating the model. The model classifies different anomaly events including hardware failures (e.g. sensor failures), sabotage and cyber-attacks (e.g. DoS and Spoofing). Unlike other detection systems, our proposed work helps in accelerating the mitigation process by notifying the operator with additional information when an anomaly occurs. This additional information includes the probability and confidence level of event(s) occurring. The model is trained and tested using a real-world dataset
Security Evaluation of Cyber-Physical Systems in Society- Critical Internet of Things
In this paper, we present evaluation of security
awareness of developers and users of cyber-physical systems. Our
study includes interviews, workshops, surveys and one practical
evaluation. We conducted 15 interviews and conducted survey with
55 respondents coming primarily from industry. Furthermore, we
performed practical evaluation of current state of practice for a
society-critical application, a commercial vehicle, and reconfirmed
our findings discussing an attack vector for an off-line societycritical
facility. More work is necessary to increase usage of security
strategies, available methods, processes and standards. The security
information, currently often insufficient, should be provided in the
user manuals of products and services to protect system users. We
confirmed it lately when we conducted an additional survey of
users, with users feeling as left out in their quest for own security
and privacy. Finally, hardware-related security questions begin to
come up on the agenda, with a general increase of interest and
awareness of hardware contribution to the overall cyber-physical
security. At the end of this paper we discuss possible
countermeasures for dealing with threats in infrastructures,
highlighting the role of authorities in this quest
- …