Biblio
Filters: Keyword is FDI [Clear All Filters]
Computational Intelligence Technologies Stack for Protecting the Critical Digital Infrastructures against Security Intrusions. 2021 Fifth World Conference on Smart Trends in Systems Security and Sustainability (WorldS4). :118–122.
.
2021. Over the past decade, an infotelecommunication technology has made significant strides forward. With the advent of new generation wireless networks and the massive digitalization of industries, the object of protection has changed. The digital transformation has led to an increased opportunity for cybercriminals. The ability of computational intelligence to quickly process large amounts of data makes the intrusions tailored to specific environments. Polymorphic attacks that have mutations in their sequences of acts adapt to the communication environments, operating systems and service frameworks, and also try to deceive the defense tools. The poor protection of most Internet of Things devices allows the attackers to take control over them creating the megabotnets. In this regard, traditional methods of network protection become rigid and low-effective. The paper reviews a computational intelligence (CI) enabled software- defined network (SDN) for the network management, providing dynamic network reconfiguration to improve network performance and security control. Advanced machine learning and artificial neural networks are promising in detection of false data injections. Bioinformatics methods make it possible to detect polymorphic attacks. Swarm intelligence detects dynamic routing anomalies. Quantum machine learning is effective at processing the large volumes of security-relevant datasets. The CI technology stack provides a comprehensive protection against a variative cyberthreats scope.
Method of Detecting FDI Attacks on Smart Grid. 2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S T). :132–136.
.
2020. Nowadays energy systems in many countries improve and develop being based on the concept of deep integration of energy as well as infocomm grids. Thus, energy grids find the possibility to analyze the state of the whole system in real time, to predict the processes in it, to have interactive cooperation with the clients and to run the appliance. Such concept has been named Smart Grid. This work highlights the concept of Smart Grid, possible vectors of attacks and identification of attack of false data injection (FDI) into the flow of measuring received from the sensors. Identification is based on the use of spatial and temporal correlations in Smart Grids.