Biblio

Phasor measurement units (PMUs) are used in power grids across North America to measure the amplitude, phase, and frequency of an alternating voltage or current. PMU's use the IEEE C37.118 protocol to send telemetry to phasor data collectors (PDC) and human machine interface (HMI) workstations in a control center. However, the C37.118 protocol utilizes the internet protocol stack without any authentication mechanism. This means that the protocol is vulnerable to false data injection (FDI) and false command injection (FCI). In order to study different scenarios in which C37.118 protocol's integrity and confidentiality can be compromised, we created a testbed that emulates a C37.118 communication network. In this testbed we conduct FCI and FDI attacks on real-time C37.118 data packets using a packet manipulation tool called Scapy. Using this platform, we generated C37.118 FCI and FDI datasets which are processed by multi-label machine learning classifier algorithms, such as Decision Tree (DT), k-Nearest Neighbor (kNN), and Naive Bayes (NB), to find out how effective machine learning can be at detecting such attacks. Our results show that the DT classifier had the best precision and recall rate.

Modern critical infrastructures are increasingly turning into distributed, complex Cyber-Physical systems that need proactive protection and fast restoration to mitigate physical or cyber incidents or attacks. Addressing the need for early stage threat detection against physical intrusion, the paper presents two physical security sensors developed within the DEFENDER project for detecting the intrusion of drones and humans using video analytics. The continuous stream of media data obtained from the region of vulnerability and proximity is processed using Region based Fully Connected Neural Network deep-learning model. The novelty of the pro-posed system relies in the processing of multi-threaded media input streams for achieving real-time threat identification. The video analytics solution has been validated using NVIDIA GeForce GTX 1080 for drone detection and NVIDIA GeForce RTX 2070 Max-Q Design for detecting human intruders. The experimental test bed for the validation of the proposed system has been constructed to include environments and situations that are commonly faced by critical infrastructure operators such as the area of protection, tradeoff between angle of coverage against distance of coverage.

Critical infrastructures of all countries unites common cyberspace. In this space, there are many threats that can disrupt the security of critical infrastructure in one country, but also cause damage in other countries. This is a reality that makes it necessary to agree on intergovernmental national views on the composition of critical infrastructures, an assessment of their security and protection. The article presents an overview of views on critical infrastructures of the United States, the European Union, the United Kingdom, and the Russian Federation, the purpose of which is to develop common positions.