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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Suciu, A. Marton, K. Cebuc, E. Dadarlat, V.T. Sebestyen, G. |
| Copyright Year | 2010 |
| Description | Author affiliation: Computer Science Department, Technical University of Cluj-Napoca, Romania (Suciu, A.; Marton, K.; Cebuc, E.; Dadarlat, V.T.; Sebestyen, G.) |
| Abstract | The HAVEGE algorithm [1,2] generates unpredictable random numbers by gathering entropy from internal processor states that are inheritably volatile and impossible to tamper with in a controlled fashion by any application running on the target system. The method used to gather the entropy implies that its main loop will almost monopolize the CPU; the output depends on the operating system and other running applications, as well as some internal mechanisms that stir the processor states to generate an enormous amount of entropy. The algorithm was designed with the idea of single-core CPUs in mind, and no parallelization; however the recent advances in Grid technologies and infrastructures justifies the need to research a gridified parallel version of HAVEGE, capable of running the same algorithm loop on each Grid worker node independently and transparently combine the results in one single output bitstream. This paper will demonstrate how such a gridification is possible and benchmark the quality of the resulting generator which we call GridHAVEGE. |
| Starting Page | 459 |
| Ending Page | 463 |
| File Size | 102437 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424482283 |
| e-ISBN | 9781424482306 |
| DOI | 10.1109/ICCP.2010.5606399 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-08-26 |
| Publisher Place | Romania |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Taxonomy random number generator Grid parallel implementation NIST Generators Entropy Hardware Security Pipeline processing HAVEGE |
| Content Type | Text |
| Resource Type | Article |
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