Attacklets to Test Anomaly Detectors for Critical Infrastructure

2021 ◽  
pp. 209-227
Author(s):  
Salimah Liyakkathali ◽  
Gayathri Sugumar ◽  
Aditya Mathur
Keyword(s):  
Critical Infrastructure

5G Mobile Communication, Challenges: A Survey

2020 ◽  
Vol 2 (1) ◽  
pp. 35-42
Author(s):  
Hemalatha R ◽  
Rhesa M.J. ◽  
Revathi S
Keyword(s):  
Mobile Communication ◽  
Traffic Management ◽  
Radiation Effects ◽  
Critical Infrastructure ◽  
Security Threats ◽  
Technological Advancement ◽  
Data Traffic ◽  
Communication Challenges ◽  
5G Mobile Communication ◽  
Living Organisms

The hest for technological advancement in mobile communication is due to augmentation of wireless user. The deployment of 5G mobile communication is less than 4G mobile communication due to challenges in security like cyberwarfare, espionage, critical infrastructure threats. Nevertheless, critic of neurological discomforts, tissue damage in living organisms occur in the existence of EMF radiation. Also, physical scarcity for spectral efficiency arises due to ubiquitous data traffic. Inspite of these disputes data rate, low latency, device to device communication is also a challenge. In this paper we provide a survey on radiation effects, security threats, traffic management.

Critical Infrastructure Assurance: Electric Power Reliability

1999 ◽  
Author(s):  
Maximilian K. Bremer ◽  
Daniel Feliz ◽  
Troy Perry
Keyword(s):  
Electric Power ◽  
Critical Infrastructure ◽  
Power Reliability

scholarly journals Attack Categorisation for IoT Applications in Critical Infrastructures, a Survey

2021 ◽  
Vol 11 (16) ◽  
pp. 7228
Author(s):  
Edward Staddon ◽  
Valeria Loscri ◽  
Nathalie Mitton
Keyword(s):  
Critical Infrastructure ◽  
Attack Detection ◽  
Critical Infrastructures ◽  
Cyber Attack ◽  
Specific System ◽  
Iot Applications ◽  
War Zone ◽  
Clear Vision ◽  
The Internet Of Things ◽  
Do So

With the ever advancing expansion of the Internet of Things (IoT) into our everyday lives, the number of attack possibilities increases. Furthermore, with the incorporation of the IoT into Critical Infrastructure (CI) hardware and applications, the protection of not only the systems but the citizens themselves has become paramount. To do so, specialists must be able to gain a foothold in the ongoing cyber attack war-zone. By organising the various attacks against their systems, these specialists can not only gain a quick overview of what they might expect but also gain knowledge into the specifications of the attacks based on the categorisation method used. This paper presents a glimpse into the area of IoT Critical Infrastructure security as well as an overview and analysis of attack categorisation methodologies in the context of wireless IoT-based Critical Infrastructure applications. We believe this can be a guide to aid further researchers in their choice of adapted categorisation approaches. Indeed, adapting appropriated categorisation leads to a quicker attack detection, identification, and recovery. It is, thus, paramount to have a clear vision of the threat landscapes of a specific system.

scholarly journals Quantifying Road-Network Robustness toward Flood-Resilient Transportation Systems

2021 ◽  
Vol 13 (6) ◽  
pp. 3172
Author(s):  
Suchat Tachaudomdach ◽  
Auttawit Upayokin ◽  
Nopadon Kronprasert ◽  
Kriangkrai Arunotayanun
Keyword(s):  
Road Network ◽  
Critical Infrastructure ◽  
Policy Issue ◽  
Analytical Framework ◽  
Transportation Systems ◽  
Network Robustness ◽  
System Response ◽  
Chiang Mai ◽  
Protection Measures ◽  
Response And Recovery

Amidst sudden and unprecedented increases in the severity and frequency of climate-change-induced natural disasters, building critical infrastructure resilience has become a prominent policy issue globally for reducing disaster risks. Sustainable measures and procedures to strengthen preparedness, response, and recovery of infrastructures are urgently needed, but the standard for measuring such resilient elements has yet to be consensually developed. This study was undertaken with an aim to quantitatively measure transportation infrastructure robustness, a proactive dimension of resilience capacities and capabilities to withstand disasters; in this case, floods. A four-stage analytical framework was empirically implemented: 1) specifying the system and disturbance (i.e., road network and flood risks in Chiang Mai, Thailand), 2) illustrating the system response using the damaged area as a function of floodwater levels and protection measures, 3) determining recovery thresholds based on land use and system functionality, and 4) quantifying robustness through the application of edge- and node-betweenness centrality models. Various quantifiable indicators of transportation robustness can be revealed; not only flood-damaged areas commonly considered in flood-risk management and spatial planning, but also the numbers of affected traffic links, nodes, and cars are highly valuable for transportation planning in achieving sustainable flood-resilient transportation systems.

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