Title :
Dynamic Selection of Optimal Cryptographic Algorithms in a Runtime Environment
Author_Institution :
Ph. D. student at the School of Computer and Information Sciences, Nova Southeastern University, Fort Lauderdale, FL 33314 USA, (phone: 770-521-4900; fax: 770-360-9657; e-mail: raissi@nova.edu)
Abstract :
This paper presents the results of research conducted by the author in support of dynamic selection of optimal cryptographic algorithms in a runtime environment (DSOCARE), the author´s doctoral dissertation. Based on DSOCARE framework, a first full-scale proof-of-concept prototype was developed by the author in Java and C#/VB. The prototype was used to perform collection, selection, and reporting functions on common symmetric block ciphers, where the collection function included running benchmark tests and storing the data in DBMS located on DSOCARE server. The runtime optimal cryptographic algorithm selector (ROCAS), based on a hybrid genetic algorithm (GA) method, was used to find Pareto-optimal solutions for a diverse array of client security requests with high and low security, speed, and priority quality of service (QoS) parameters. Finally, the reporting function was used to create the data and figures presented in this paper. This paper concludes that adaptive security used in DSOCARE framework mitigates the tradeoff between security, speed, and priority elegantly. It further reinforces the author´s thesis that selection of optimal cryptographic algorithms is possible only at runtime.
Keywords :
Java; Pareto optimisation; cryptography; genetic algorithms; quality of service; Java; Pareto-optimal solutions; doctoral dissertation; dynamic selection of optimal cryptographic algorithms in runtime environment; hybrid genetic algorithm; optimal cryptographic algorithms; proof-of-concept prototype; quality of service; runtime optimal cryptographic algorithm selector; Aerodynamics; Control systems; Cryptography; Data security; Genetic algorithms; Parallel processing; Prototypes; Quality of service; Runtime environment; Telecommunication control;
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9487-9
DOI :
10.1109/CEC.2006.1688307