Fast Strategies for the Implementation of SIKE Round 3 on ARM Cortex-M4

Anastasova, Mila; Azarderakhsh, Reza; Kermani, Mehran Mozaffari

doi:10.1109/tcsi.2021.3096916

Cited by 80 publications

(23 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Their contribution is especially relevant in environments with limited resources, such as embedded systems, where perimeter security is crucial. Furthermore, in Anastasova et al ( 2021 ), the authors propose fast strategies for the efficient implementation of the SIKE Round 3 cryptographic scheme on ARM Cortex-M4 devices. By optimizing the performance of this scheme in systems with resource constraints, perimeter security is strengthened in critical areas, guaranteeing adequate protection of communications.…”

Section: Methodsmentioning

confidence: 99%

Authentication, access, and monitoring system for critical areas with the use of artificial intelligence integrated into perimeter security in a data center

Villegas-Ch,

García-Ortiz

2023

Front. Big Data

View full text Add to dashboard Cite

Perimeter security in data centers helps protect systems and the data they store by preventing unauthorized access and protecting critical resources from potential threats. According to the report of the information security company SonicWall, in 2021, there was a 66% increase in the number of ransomware attacks. In addition, the message from the same company indicates that the total number of cyber threats detected in 2021 increased by 24% compared to 2019. Among these attacks, the infrastructure of data centers was compromised; for this reason, organizations include elements Physical such as security cameras, movement detection systems, authentication systems, etc., as an additional measure that contributes to perimeter security. This work proposes using artificial intelligence in the perimeter security of data centers. It allows the automation and optimization of security processes, which translates into greater efficiency and reliability in the operations that prevent intrusions through authentication, permit verification, and monitoring critical areas. It is crucial to ensure that AI-based perimeter security systems are designed to protect and respect user privacy. In addition, it is essential to regularly monitor the effectiveness and integrity of these systems to ensure that they function correctly and meet security standards.

show abstract

Section: Methodsmentioning

confidence: 99%

Authentication, access, and monitoring system for critical areas with the use of artificial intelligence integrated into perimeter security in a data center

Villegas-Ch,

García-Ortiz

2023

Front. Big Data

View full text Add to dashboard Cite

show abstract

“…To keep sensitive patient data private, we have used an efficient method called homomorphic message authentication code (MACs) along with a group signature called elliptic curves [22,23]. In light of the fact that patient data is shared with many healthcare workers, maintaining the identity anonymity of patient data during prescription process is appreciated.…”

Section: Privacy Preservationmentioning

confidence: 99%

An Intelligent Cardiovascular Diseases Prediction System Focused on Privacy

Kolhar¹,

Misfer²

2023

Intelligent Automation &Amp; Soft Computing

View full text Add to dashboard Cite

Machine learning (ML) and cloud computing have now evolved to the point where they are able to be used effectively. Further improvement, however, is required when both of these technologies are combined to reap maximum benefits. A way of improving the system is by enabling healthcare workers to select appropriate machine learning algorithms for prediction and, secondly, by preserving the privacy of patient data so that it cannot be misused. The purpose of this paper is to combine these promising technologies to maintain the privacy of patient data during the disease prediction process. Treatment of heart failure may be improved and expedited with this framework. We used the following machine learning algorithms to make predictions: Logistic Regression (LR), Naive Bayes (NB), K-Nearest Neighbors (KNN), Decision Tree (DT) and Support Vector Machines (SVM). These techniques, combined with cloud computing services, improved the process of deciding whether to treat a patient with cardiac disease. Using our classifiers, we classified cardiac patients according to their features, which are grouped into single features, combinations of selected features, and all features. In experiments using all clinical features, machine learning classifiers SVM, DT, and KNN outperformed the rest, whereas in experiments using minimal clinical features, SVM and KNN were the most accurate. Internet of Things (IoT) devices allow family physicians to share diagnostic reports on the cloud in a secure manner. Ring signatures are particularly useful for verifying the integrity of data exchange. Our system keeps the physician's identity confidential from all authorized users, who can still access medical reports publicly. Our proposed mechanism has been shown to be both effective and efficient when it comes to obtaining patient reports from cloud storage.

show abstract

“…1 means that the sample is qualified, it means that it has entered the interview process through the audition stage, and 0 means that the sample is eliminated. Compared with the reference [25][26][27], the artificial neural network used in this paper has a better nonlinear function. This quality evaluation project adopts various means such as knowledge examination, psychological quality test, interview and simulation performance technology to conduct a comprehensive quality investigation of the interviewees.…”

Section: Example Application and Analysismentioning

confidence: 99%

Research on Strategic Decision Model of Human Resource Management based on Biological Neural Network

2023

IJACSA

View full text Add to dashboard Cite

Human resource management system is an indispensable part of information strategy construction. Based on the theory of biological neural network, this paper constructs the strategic decision model of human resources management, then uses the micro-integration method to predict the demand for human resources, and solves the quantification problem of human resources supply prediction. In the simulation process, the model analyzes the current situation of the personnel management system and the necessity of research and plans and designs a computer-aided personnel management information system based on the Client/Server biological neural network structure. Personnel quality evaluation through the evaluation and analysis of the quality of the evaluated, to provide effective reference information for the enterprise personnel decision and index selection, the enterprise human resources allocation, use, training and development is of great significance. Neural networks rely on the powerful data storage, processing and computing capabilities of computers to help enterprises respond quickly to changes in external market conditions, improve the efficiency of decision-making, and create greater value for enterprises. Through experimental testing, it is found that when the iteration is 5, the network verification results have the best consistency. When the iterations reach 7, the standard of training target error set in this paper is reached. When the samples reached 60, the screening accuracy of the network reached 92.18%; when the samples increased to 80, the screening accuracy was further improved to 92.84%, indicating that the screening accuracy of the network increased with the training samples, which could be used to detect and classify samples quickly, objectively and accurately.

show abstract

Fast Strategies for the Implementation of SIKE Round 3 on ARM Cortex-M4

Cited by 80 publications

References 26 publications

Authentication, access, and monitoring system for critical areas with the use of artificial intelligence integrated into perimeter security in a data center

Authentication, access, and monitoring system for critical areas with the use of artificial intelligence integrated into perimeter security in a data center

An Intelligent Cardiovascular Diseases Prediction System Focused on Privacy

Research on Strategic Decision Model of Human Resource Management based on Biological Neural Network

Contact Info

Product

Resources

About