The Impact of the Advanced Technologies over the Cyber Attacks Surface

Dimitrov, Willian

doi:10.1007/978-3-030-51971-1_42

Cited by 8 publications

(7 citation statements)

References 12 publications

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“…The data exchange between the VM1 and the PDU was secure. Other methods for secure data exchange are discussed in [46,47]. Figure 69 shows the Wireshark results verifying that the tunnel was functional while also exchanging traffic with other devices somewhere in the world.…”

Section: Using the Ip Network Modeling Platforms To Study Power Elect...mentioning

confidence: 91%

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Benefits of Using Network Modeling Platforms When Studying IP Networks and Traffic Characterization

Nedyalkov

2023

Computers

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This article addresses the benefits of using IP network modeling platforms to study IP networks. For the purposes of this study, several models of IP networks were created, through which various hypotheses were studied. Additionally, different operational variants of the modeled IP networks were created. The use of the GNS3 platform was proposed, as well as several tools for monitoring the processes in IP networks. The application of IP network modeling platforms to study power electronic devices was also addressed. IP network modeling platforms greatly facilitate both the process of studying IP networks and the process of training professionals to design, install, and maintain different types of IP network. Thanks to the GNS3 IP network modeling platform, it was possible to implement different models of IP networks with different functionalities. It was very easy to determine the answers to posed hypotheses/questions through the capabilities of the IP network modeling platforms. The questions posed by the hypotheses addressed in this paper were answered thanks to the results obtained from the research carried out with the IP network modeling platform GNS3. The present study confirmed that the use of these platforms, in particular the GNS3 platform, for the modeling of IP networks is an excellent substitute for expensive network equipment, and the IP network models created in the platform performed almost like networks made of real devices.

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Section: Using the Ip Network Modeling Platforms To Study Power Elect...mentioning

confidence: 91%

“…The data exchange between the VM1 and the PDU was secure. Other methods for secure data exchange are discussed in [46,47]. Finally, with the help of IP network modeling platforms, different hypotheses can be verified.…”

Section: Using the Ip Network Modeling Platforms To Study Power Elect...mentioning

confidence: 99%

Benefits of Using Network Modeling Platforms When Studying IP Networks and Traffic Characterization

Nedyalkov

2023

Computers

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“…Using new technologies to find and predict strange behavior that could be a sign of an attack early on could make systems more resilient. Without any formal programming, machine learning looks at very large datasets to find patterns and find outliers (Dimitrov, 2020). When reinforcement learning models are taught on normal infrastructure operations, they automatically report deviations so that they can be looked at again before they have a big effect (Xing et al, 2021).…”

Section: Advanced Detection Technologiesmentioning

confidence: 99%

“…It's easy for recurrent neural networks to work with time series data, which lets them look for problems in operational information (Xing et al, 2021). Training deep learning models needs a lot of different datasets, which can't be gathered without adding fake data (Dimitrov, 2020). Infrastructure providers can still have trouble getting good training data, but the federal government can help by coordinating data sharing programs.…”

Section: Advanced Detection Technologiesmentioning

confidence: 99%

Innovative solutions for critical infrastructure resilience against cyber-physical attacks

Bright Ojo,

Justine Chilenovu Ogborigbo,

Maureen Oluchukwuamaka Okafor

2024

World J. Adv. Res. Rev.

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Critical infrastructure must withstand cyber and physical assaults in today's interconnected world. This study explores innovative strategies to shield these systems from cyber-physical threats. As networks become more connected, cyberattacks grow more sophisticated, making it imperative to safeguard sectors like transportation, energy, water, and information. The paper analyzes the present and future threat landscape, identifying vulnerabilities within critical infrastructures and proposing targeted mitigation strategies to enhance security. The research leverages AI and machine learning to develop detection tools that identify and predict cyber-physical attacks, enhancing response times and preventive measures. Additionally, resilience engineering and architecture are crucial in fortifying infrastructure, enabling it to withstand and recover from attacks while maintaining essential functions. The study also reviews legislation and policies surrounding infrastructure protection, pinpointing shortcomings and recommending improvements to bolster national security. Effective countermeasures against cyber-physical threats require collaboration and information sharing among government bodies, industry stakeholders, and educational institutions. These partnerships facilitate the exchange of knowledge, best practices, and tools to address threats efficiently. Furthermore, the paper highlights the importance of training programs that equip professionals with skills to integrate cyber and physical security defenses. Exploring the integration of blockchain, IoT, and autonomous technologies could further enhance the resilience of critical systems. These technologies foster secure communications and automated responses to incidents. Lastly, community awareness initiatives play a vital role in preparing for and mitigating cyber-physical attacks, ensuring that public readiness and resilience are maintained. This comprehensive approach aims to fortify critical infrastructure against evolving cyber threats, ensuring continuous operation and security.

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“…As can be seen, it is accessing different content on the Internet that goes along with the encrypted data in the tunnel. Other ways to implement secure data exchange are presented in [39,40]. In the modeled "WAN" network (from Figure 2), a tunnel is created between R1 and R4 that passes through R1, R2, R3, R4, and vice versa.…”

Section: Security Of Data Exchangementioning

confidence: 99%

Application of GNS3 to Study the Security of Data Exchange between Power Electronic Devices and Control Center

Nedyalkov

2023

Computers

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This paper proposes the use of the GNS3 IP network modeling platform to study/verify whether the exchanged information between power electronic devices and a control center (Monitoring and Control Centre) is secure. For the purpose of this work, a power distribution unit (PDU) and a UPS (Uninterruptable Power Supply) that are used by internet service providers are studied. Capsa Free network analyzer and Wireshark network protocol analyzer were used as supporting tools. A working model of an IP network in GNS3 has been created through which this research has been carried out. In addition to checking whether the exchanged information is secure, a characterization of the generated traffic has been made, showing results for the generated traffic and which ports generate the most traffic. These carried-outstudies show that the exchanged information is not secure. As a way to secure the exchanged information, the use of VPN (Virtual Private Network) technology is proposed; thanks to a VPN, the exchange of information is secure. The obtained results confirm this and validate the applicability of GNS3 to test/study whether data exchange between power electronic devices and a control center is secure.

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The Impact of the Advanced Technologies over the Cyber Attacks Surface

Cited by 8 publications

References 12 publications

Benefits of Using Network Modeling Platforms When Studying IP Networks and Traffic Characterization

Benefits of Using Network Modeling Platforms When Studying IP Networks and Traffic Characterization

Innovative solutions for critical infrastructure resilience against cyber-physical attacks

Application of GNS3 to Study the Security of Data Exchange between Power Electronic Devices and Control Center

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