Parameter estimation of a susceptible–infected–recovered–dead computer worm model.
Saved in:
| Title: | Parameter estimation of a susceptible–infected–recovered–dead computer worm model. |
|---|---|
| Authors: | Deng, Yue1 (AUTHOR), Pei, Yongzhen2 (AUTHOR) peiyzh_team@sina.com, Li, Changguo3 (AUTHOR) |
| Source: | Simulation. Mar2022, Vol. 98 Issue 3, p209-220. 12p. |
| Subjects: | Computer worms, Parameter estimation, Kalman filtering, Markov chain Monte Carlo, Least squares, Computer simulation, Ordinary differential equations |
| Abstract: | Computer worms are serious threats to Internet security and have caused billions of dollars of economic losses during the past decades. In this study, we implemented a susceptible–infected–recovered–dead (SIRD) model of computer worms and analyzed the characteristics and mechanisms of worm transmission. We applied the ordinary differential equation model to simulate the transmission process of computer worms and estimated the unknown parameters of the SIRD model through the methods of least squares, Markov chain Monte Carlo, and ensemble Kalman filtering (ENKF). The results reveal that the proposed SIRD model is more accurate than the susceptible–exposed–infected–recovered–susceptible model with respect to parameter estimation. [ABSTRACT FROM AUTHOR] |
| Copyright of Simulation is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 155083111 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Parameter estimation of a susceptible–infected–recovered–dead computer worm model. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Deng%2C+Yue%22">Deng, Yue</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pei%2C+Yongzhen%22">Pei, Yongzhen</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> peiyzh_team@sina.com</i><br /><searchLink fieldCode="AR" term="%22Li%2C+Changguo%22">Li, Changguo</searchLink><relatesTo>3</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Simulation%22">Simulation</searchLink>. Mar2022, Vol. 98 Issue 3, p209-220. 12p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Computer+worms%22">Computer worms</searchLink><br /><searchLink fieldCode="DE" term="%22Parameter+estimation%22">Parameter estimation</searchLink><br /><searchLink fieldCode="DE" term="%22Kalman+filtering%22">Kalman filtering</searchLink><br /><searchLink fieldCode="DE" term="%22Markov+chain+Monte+Carlo%22">Markov chain Monte Carlo</searchLink><br /><searchLink fieldCode="DE" term="%22Least+squares%22">Least squares</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation%22">Computer simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Ordinary+differential+equations%22">Ordinary differential equations</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Computer worms are serious threats to Internet security and have caused billions of dollars of economic losses during the past decades. In this study, we implemented a susceptible–infected–recovered–dead (SIRD) model of computer worms and analyzed the characteristics and mechanisms of worm transmission. We applied the ordinary differential equation model to simulate the transmission process of computer worms and estimated the unknown parameters of the SIRD model through the methods of least squares, Markov chain Monte Carlo, and ensemble Kalman filtering (ENKF). The results reveal that the proposed SIRD model is more accurate than the susceptible–exposed–infected–recovered–susceptible model with respect to parameter estimation. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Simulation is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=155083111 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1177/00375497211009576 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 209 Subjects: – SubjectFull: Computer worms Type: general – SubjectFull: Parameter estimation Type: general – SubjectFull: Kalman filtering Type: general – SubjectFull: Markov chain Monte Carlo Type: general – SubjectFull: Least squares Type: general – SubjectFull: Computer simulation Type: general – SubjectFull: Ordinary differential equations Type: general Titles: – TitleFull: Parameter estimation of a susceptible–infected–recovered–dead computer worm model. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Deng, Yue – PersonEntity: Name: NameFull: Pei, Yongzhen – PersonEntity: Name: NameFull: Li, Changguo IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 00375497 Numbering: – Type: volume Value: 98 – Type: issue Value: 3 Titles: – TitleFull: Simulation Type: main |
| ResultId | 1 |
