Analytical Modelling and Performance Evaluation of Security Issues for Cloud Computing

2019 ◽  
Author(s):  
Ersin Caglar ◽  
Yonal Kirsal
Keyword(s):  
Cloud Computing ◽  
Performance Evaluation ◽  
Analytical Modelling ◽  
Security Issues ◽  
And Performance

scholarly journals Robustness and Unpredictability for Double Arbiter PUFs on Silicon Data: Performance Evaluation and Modeling Accuracy

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 870 ◽  
Author(s):  
Meznah A. Alamro ◽  
Khalid T. Mursi ◽  
Yu Zhuang ◽  
Ahmad O. Aseeri ◽  
Mohammed Saeed Alkatheiri
Keyword(s):  
Performance Evaluation ◽  
Integrated Circuits ◽  
Security Analysis ◽  
Limited Resource ◽  
Security Issues ◽  
Non Volatile Memory ◽  
Secret Keys ◽  
Iot Devices ◽  
And Performance ◽  
Secure Authentication

Classical cryptographic methods that inherently employ secret keys embedded in non-volatile memory have been known to be impractical for limited-resource Internet of Things (IoT) devices. Physical Unclonable Functions (PUFs) have emerged as an applicable solution to provide a keyless means for secure authentication. PUFs utilize inevitable variations of integrated circuits (ICs) components, manifest during the fabrication process, to extract unique responses. Double Arbiter PUFs (DAPUFs) have been recently proposed to overcome security issues in XOR PUF and enhance the tolerance of delay-based PUFs against modeling attacks. This paper provides comprehensive risk analysis and performance evaluation of all proposed DAPUF designs and compares them with their counterparts from XOR PUF. We generated different sets of real challenge–response pairs CRPs from three FPGA hardware boards to evaluate the performance of both DAPUF and XOR PUF designs using special-purpose evaluation metrics. We show that none of the proposed designs of DAPUF is strictly preferred over XOR PUF designs. In addition, our security analysis using neural network reveals the vulnerability of all DAPUF designs against machine learning attacks.

scholarly journals Quantitative Analysis and Performance Evaluation of Target-Oriented Replication Strategies in Cloud Computing

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 672
Author(s):  
Quadri Waseem ◽  
Wan Isni Sofiah Wan Din ◽  
Sultan S. Alshamrani ◽  
Abdullah Alharbi ◽  
Amril Nazir
Keyword(s):  
Cloud Computing ◽  
Performance Evaluation ◽  
Quantitative Analysis ◽  
Performance Indicator ◽  
Data Replication ◽  
Future Research ◽  
Dynamic Data ◽  
Advantages And Disadvantages ◽  
Dynamic Data Replication ◽  
And Performance

Data replications effectively replicate the same data to various multiple locations to accomplish the objective of zero loss of information in case of failures without any downtown. Dynamic data replication strategies (providing run time location of replicas) in clouds should optimize the key performance indicator parameters, like response time, reliability, availability, scalability, cost, availability, performance, etc. To fulfill these objectives, various state-of-the-art dynamic data replication strategies has been proposed, based on several criteria and reported in the literature along with advantages and disadvantages. This paper provides a quantitative analysis and performance evaluation of target-oriented replication strategies based on target objectives. In this paper, we will try to find out which target objective is most addressed, which are average addressed, and which are least addressed in target-oriented replication strategies. The paper also includes a detailed discussion about the challenges, issues, and future research directions. This comprehensive analysis and performance evaluation based-work will open a new door for researchers in the field of cloud computing and will be helpful for further development of cloud-based dynamic data replication strategies to develop a technique that will address all attributes (Target Objectives) effectively in one replication strategy.

Sign in / Sign up

Export Citation Format

Share Document