Security Infrastructure for Cyber Attack Targeted Networks and Services

Kumar, Anmol; Somani, Gaurav

doi:10.1007/978-981-19-2374-6_9

Cited by 2 publications

(2 citation statements)

References 2 publications

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“…This framework also contains a layered defense mechanism, which incorporates multiple security measures layers to prevent different types of threats. These measures guard the network, for instance, firewalls and intrusion alarms, endpoint protection like antivirus software and device management, and data security practices such as encryption and access controls Kumar & Somani (2022). However, by implementing these layers, the framework ensures comprehensive coverage, making it difficult for the attacker to penetrate the defenses.…”

Section: Holistic Framework For Enhancing Threat Mitigation In Digita...mentioning

confidence: 99%

Towards Improved Threat Mitigation in Digital Environments: A Comprehensive Framework for Cybersecurity Enhancement

Balisane,

Egho-Promise,

Lyada

et al. 2024

Int. J. Res. Granthaalayah

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In today's digital landscape, cybersecurity has become a critical concern due to the increasing sophistication of cyber threats. Traditional cybersecurity measures are often inadequate against evolving attacks, necessitating the development of comprehensive and adaptive threat mitigation frameworks. This study aims to address this gap by proposing a robust cybersecurity framework that integrates advanced technologies such as artificial intelligence (AI), machine learning (ML), and blockchain to enhance threat detection, response, and recovery capabilities. The framework adopts a layered defense mechanism, real-time monitoring, and proactive threat hunting to provide a holistic approach to cybersecurity. By examining current methodologies and identifying their limitations, this research highlights the necessity for enhanced threat mitigation strategies. Through a mixed-methods approach involving online surveys and literature review, the study develops a flexible, scalable, and adaptive framework capable of countering sophisticated cyber threats. Key recommendations include adopting advanced technologies, continuous training, enhancing threat intelligence sharing, implementing a layered defense strategy, and conducting regular security audits. This comprehensive framework aims to improve organizational resilience, ensuring the safety and integrity of digital environments in the face of an ever-evolving cyber threat landscape.

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Section: Holistic Framework For Enhancing Threat Mitigation In Digita...mentioning

confidence: 99%

Towards Improved Threat Mitigation in Digital Environments: A Comprehensive Framework for Cybersecurity Enhancement

Balisane,

Egho-Promise,

Lyada

et al. 2024

Int. J. Res. Granthaalayah

View full text Add to dashboard Cite

show abstract

“…There are many take place countermeasures to detect and prevent the cyber-attacks, such as encryption algorithm, VPN, Firewall, antivirus software, IDS, and access control. From a security management viewpoint, the countermeasures must hood risk estimate of resources at behind attack, exchange and manage of secret key, and vulnerability reporting [20]. Different security strategies to defense solution through AI, machine-learning (ML), certificate authenticity (CA), and proactive real-time IPS-IDS.…”

Section: Artificial Intelligence Techniques In Sgmentioning

confidence: 99%

Identification scheme of false data injection attack based on deep learning algorithms for smart grids

Merza

Hussein

Ali

2023

IJEECS

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This paper presents the artificial intelligence (AI) techniques based on the deep learning algorithms to diagnose false data injection (FDI) attacks to smart grids with the measurement data in real-time. The power and data flow between end-user consumers and all components of the advanced metering infrastructure (AMI) and supervisory control and data acquisition (SCADA) system in the SG is bidirectional flow by advanced communication networks. For all the advantages of the SG come with, they remain at risk to a series of many potential threats and ongoing attacks. The conditional-deep-belief-network (CDBN) architecture is employed to un-observable FDI attacks which pass the state-vector-estimator (SVE) mechanisms. The IEEE 118 bus, and IEEE 300 bus power system have been used to evaluate our detection scheme. Finally, the suggested CDBN scheme is compared with other detection such as artificial neural network (ANN) and support vector machine (SVM). It is observed that the simulation result shows that suggested detection methods can attain a high accuracy of unobservable FDI attacks.

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Security Infrastructure for Cyber Attack Targeted Networks and Services

Cited by 2 publications

References 2 publications

Towards Improved Threat Mitigation in Digital Environments: A Comprehensive Framework for Cybersecurity Enhancement

Towards Improved Threat Mitigation in Digital Environments: A Comprehensive Framework for Cybersecurity Enhancement

Identification scheme of false data injection attack based on deep learning algorithms for smart grids

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