scholarly journals КІБЕРБЕЗПЕКА БЕЗПРОВОДОВИХ СМАРТ-СИСТЕМ: КАНАЛИ ВТРУЧАНЬ ТА РАДІОЧАСТОТНІ ВРАЗЛИВОСТІ

Author(s):  
Володимир Якович Певнев ◽  
Володимир Володимирович Торяник ◽  
Вячеслав Сергійович Харченко

The subject of this study is the radio frequency cyber vulnerability of information and control interaction technology in the wireless smart systems (WSS). WSS is the cyber-physical systems, that operate within the OSI model. The specificity and specialization of these systems are determined by radio technologies of the physical layer. For example, the Internet of Things (IoT, including medical IoMT), the Internet of Drones (IoD), systems for aviation monitoring ADS-B and traffic management ATM, and, in the future, the Internet of Everything (IoE) - all are types of WSS. The aim is to analyze the radio frequency parameters of information and control interaction in the WSS to identify possible radio frequency cyber vulnerabilities in the WSS. Objectives: summarize and systematize the physical and functional parameters of wireless technologies in the ISM (Industrial Scientific & Medical Band) and SRD (Short range devices) ranges, which are significant from the WSS radiofrequency cyber vulnerability perspective, including navigation technologies; analyze trends and methods of successful cyber attacks on the WSS; carry out expert assessments of potential WSSs cyber vulnerabilities depending on their architecture and application area. The methods used: analysis of trends in known radiofrequency incidents and expert assessments of the cyber vulnerability of the WSS information and control interaction channels. The following results were obtained: 12 actual WSS radio technologies were analyzed. 6 types of possible radio frequency cyber attacks on the WSS were typified. The expert assessment of the probability of exploiting vulnerabilities by ranges, radio technologies, and attack type was made. The special danger of high-tech targeted APT attacks, as well as the high potential radio vulnerability of cyber-physical systems, was shown. The cyber vulnerability of ADS-B aircraft systems was especially noted. Conclusions. The scientific novelty of the results obtained is as follows: a trend of APT attacks cost reduction and an increase in the probability of their implementation through the new capabilities of SDR technology (Software Defined Radio) were revealed. The possibility of a controlled SDR compromising of the security parameters of WSS channels in any radio range was shown. A promising direction of research was proposed - SDR-penetration testing of WSS.

Cyber is an integration of computation, communication, and control systems. Physical means natural and human-made systems that are managed and governed by the physics regulations and functioning in constant time. In Cyber Physical Systems, the cyber and physical systems are those firmly incorporated at all stages and dimensions. Starting in late 2006, the US National Science Foundation (NSF) and other United State federal agencies sponsored several workshops on CPSs. In 2007, the NSF identified CPSs as a key area of research. CPS uses embedded computers and networks to compute, communicate, and organize physical actions. Simultaneously, a CPS receives feedback on how physical events impact computations and vice versa. Through the Internet and how people communicate with each other, CPSs will change the way people interrelate with the world around them. This chapter explores CPSs.


Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 487 ◽  
Author(s):  
Mahmoud Elsisi ◽  
Karar Mahmoud ◽  
Matti Lehtonen ◽  
Mohamed M. F. Darwish

The modern control infrastructure that manages and monitors the communication between the smart machines represents the most effective way to increase the efficiency of the industrial environment, such as smart grids. The cyber-physical systems utilize the embedded software and internet to connect and control the smart machines that are addressed by the internet of things (IoT). These cyber-physical systems are the basis of the fourth industrial revolution which is indexed by industry 4.0. In particular, industry 4.0 relies heavily on the IoT and smart sensors such as smart energy meters. The reliability and security represent the main challenges that face the industry 4.0 implementation. This paper introduces a new infrastructure based on machine learning to analyze and monitor the output data of the smart meters to investigate if this data is real data or fake. The fake data are due to the hacking and the inefficient meters. The industrial environment affects the efficiency of the meters by temperature, humidity, and noise signals. Furthermore, the proposed infrastructure validates the amount of data loss via communication channels and the internet connection. The decision tree is utilized as an effective machine learning algorithm to carry out both regression and classification for the meters’ data. The data monitoring is carried based on the industrial digital twins’ platform. The proposed infrastructure results provide a reliable and effective industrial decision that enhances the investments in industry 4.0.


Author(s):  
Amir Namavar Jahromi ◽  
Hadis Karimipour ◽  
Ali Dehghantanha ◽  
Kim-Kwang Raymond Choo

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