Analytical Survey on the Security Framework of Cyber-Physical Systems for Smart Power System Networks

AL-Jumaili, Ahmed Hadi Ali; Muniyandi, Ravie Chandren; Hasan, Mohammad Kamrul; Singh, Mandeep Jit; Paw, Johnny Koh Siaw

doi:10.1109/iccr56254.2022.9995780

Cited by 10 publications

(10 citation statements)

References 71 publications

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“…The services provided by each layer are as follows: Application layer The application layer provides users with various application software and services required by a friendly user interface [ 201 ]. The application layer directly faces customer needs and provides enterprise customers with enterprise applications such as enterprise resource planning (ERP) and customer relationship management (CRM) [ 202 ], and office automation (OA) [ 203 ]. Platform layer The platform layer provides services for users who can use the platform to realize the value they want to achieve [ 204 ].…”

Section: The Application Basis Of Cloud Computing In a Power Systemmentioning

confidence: 99%

“…The application layer provides users with various application software and services required by a friendly user interface [ 201 ]. The application layer directly faces customer needs and provides enterprise customers with enterprise applications such as enterprise resource planning (ERP) and customer relationship management (CRM) [ 202 ], and office automation (OA) [ 203 ].…”

Section: The Application Basis Of Cloud Computing In a Power Systemmentioning

confidence: 99%

See 1 more Smart Citation

Big Data Analytics Using Cloud Computing Based Frameworks for Power Management Systems: Status, Constraints, and Future Recommendations

AL-Jumaili

Muniyandi

Hasan

et al. 2023

Sensors

Self Cite

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Traditional parallel computing for power management systems has prime challenges such as execution time, computational complexity, and efficiency like process time and delays in power system condition monitoring, particularly consumer power consumption, weather data, and power generation for detecting and predicting data mining in the centralized parallel processing and diagnosis. Due to these constraints, data management has become a critical research consideration and bottleneck. To cope with these constraints, cloud computing-based methodologies have been introduced for managing data efficiently in power management systems. This paper reviews the concept of cloud computing architecture that can meet the multi-level real-time requirements to improve monitoring and performance which is designed for different application scenarios for power system monitoring. Then, cloud computing solutions are discussed under the background of big data, and emerging parallel programming models such as Hadoop, Spark, and Storm are briefly described to analyze the advancement, constraints, and innovations. The key performance metrics of cloud computing applications such as core data sampling, modeling, and analyzing the competitiveness of big data was modeled by applying related hypotheses. Finally, it introduces a new design concept with cloud computing and eventually some recommendations focusing on cloud computing infrastructure, and methods for managing real-time big data in the power management system that solve the data mining challenges.

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Section: The Application Basis Of Cloud Computing In a Power Systemmentioning

confidence: 99%

Section: The Application Basis Of Cloud Computing In a Power Systemmentioning

confidence: 99%

Big Data Analytics Using Cloud Computing Based Frameworks for Power Management Systems: Status, Constraints, and Future Recommendations

AL-Jumaili

Muniyandi

Hasan

et al. 2023

Sensors

Self Cite

View full text Add to dashboard Cite

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“…It was recommended that the ASCAD public dataset be used to evaluate DLSCA and other SCA methods for profiling in a fair manner. In addition, emphasis was placed on reproducibility by providing hyperparameters to share the results of previous studies [10]- [14].…”

Section: Literature Reviewmentioning

confidence: 99%

Deep Learning Method for Power Side-Channel Analysis on Chip Leakages

Ahmed,

Salim,

Hasan

2023

ELEKTRON ELEKTROTECH

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Power side channel analysis signal analysis is automated using deep learning. Signal processing and cryptanalytic techniques are necessary components of power side channel analysis. Chip leakages can be found using a classification approach called deep learning. In addition to this, we do this so that the deep learning network can automatically tackle signal processing difficulties such as re-alignment and noise reduction. We were able to break minimally protected Advanced Encryption Standard (AES), as well as masking-countermeasure AES and protected elliptic-curve cryptography (ECC). These results demonstrate that the attacker knowledge required for side channel analysis, which had previously placed a significant emphasis on human abilities, is decreasing. This research will appeal to individuals with a technical background who have an interest in deep learning, side channel analysis, and security.

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“…The network applications are widely utilised, whether it is a large hotspot such as blockchain [17][18][19], IoT [20][21][22], 5G [23][24][25] the healthcare area [26][27][28][29] or a specialised Software define network [30][31][32][33][34]. The use of a particular technology [35][36][37][38] and the researcher of network security have made a lot of contributions to the advancement of technology and the development of secure network [39,40].…”

Section: Existing Work Reviewmentioning

confidence: 99%

Data security in smart devices: Advancement, constraints and future recommendations

et al. 2023

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Network security protocols are implemented to address network security challenges. Computer networks and applications have advanced and developed significantly in recent years, but consumers ‘excitement for network technology and high‐tech devices has been dampened by continual exposure to data security vulnerabilities. As of now, some individuals refuse to use smart devices due to concerns about the authenticity, confidentiality and integrity of data security leaks. This not only prompts Internet service providers to follow market protection mechanisms but also requires software developers to apply appropriate security protocols to protect computer network security. These applications’ dependability and integrity are dependent not just on the effectiveness of cryptographic algorithms, but also on key management protocols. Understanding network security protocols and implementing high‐quality standards to govern the transmission of data in the network are critical components of guaranteeing network security. The article explores data security, primarily at the application layer, various attack methods for different network security protocols and highlights the potential security implications. The study also looks at the corresponding, practical security measures and future research prospects for certain kinds of attacks. Finally, some technical challenges that remain unsolved at the time of writing are summarised, and future trends in cybersecurity are discussed.

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Analytical Survey on the Security Framework of Cyber-Physical Systems for Smart Power System Networks

Cited by 10 publications

References 71 publications

Big Data Analytics Using Cloud Computing Based Frameworks for Power Management Systems: Status, Constraints, and Future Recommendations

Big Data Analytics Using Cloud Computing Based Frameworks for Power Management Systems: Status, Constraints, and Future Recommendations

Deep Learning Method for Power Side-Channel Analysis on Chip Leakages

Data security in smart devices: Advancement, constraints and future recommendations

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