A Mathematically Generated Noise Technique for Ultrasound Systems
DC Field | Value | Language |
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dc.contributor.author | Choi, Hojong | - |
dc.contributor.author | Shin, Seung-Hyeok | - |
dc.date.accessioned | 2023-01-15T01:40:07Z | - |
dc.date.available | 2023-01-15T01:40:07Z | - |
dc.date.created | 2022-12-16 | - |
dc.date.issued | 2022-12 | - |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/86539 | - |
dc.description.abstract | Ultrasound systems have been widely used for consultation; however, they are susceptible to cyberattacks. Such ultrasound systems use random bits to protect patient information, which is vital to the stability of information-protecting systems used in ultrasound machines. The stability of the random bit must satisfy its unpredictability. To create a random bit, noise generated in hardware is typically used; however, extracting sufficient noise from systems is challenging when resources are limited. There are various methods for generating noises but most of these studies are based on hardware. Compared with hardware-based methods, software-based methods can be easily accessed by the software developer; therefore, we applied a mathematically generated noise function to generate random bits for ultrasound systems. Herein, we compared the performance of random bits using a newly proposed mathematical function and using the frequency of the central processing unit of the hardware. Random bits are generated using a raw bitmap image measuring 1000 × 663 bytes. The generated random bit analyzes the sampling data in generation time units as time-series data and then verifies the mean, median, and mode. To further apply the random bit in an ultrasound system, the image is randomized by applying exclusive mixing to a 1000 × 663 ultrasound phantom image; subsequently, the comparison and analysis of statistical data processing using hardware noise and the proposed algorithm were provided. The peak signal-to-noise ratio and mean square error of the images are compared to evaluate their quality. As a result of the test, the min entropy estimate (estimated value) was 7.156616/8 bit in the proposed study, which indicated a performance superior to that of GetSystemTime. These results show that the proposed algorithm outperforms the conventional method used in ultrasound systems. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | MDPI | - |
dc.relation.isPartOf | Sensors | - |
dc.title | A Mathematically Generated Noise Technique for Ultrasound Systems | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000904356000001 | - |
dc.identifier.doi | 10.3390/s22249709 | - |
dc.identifier.bibliographicCitation | Sensors, v.22, no.24 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.scopusid | 2-s2.0-85144534634 | - |
dc.citation.title | Sensors | - |
dc.citation.volume | 22 | - |
dc.citation.number | 24 | - |
dc.contributor.affiliatedAuthor | Choi, Hojong | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | mathematical function | - |
dc.subject.keywordAuthor | mathematically generated noise | - |
dc.subject.keywordAuthor | ultrasound system | - |
dc.relation.journalResearchArea | Chemistry | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Instruments & Instrumentation | - |
dc.relation.journalWebOfScienceCategory | Chemistry, Analytical | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Instruments & Instrumentation | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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