MalSEIRS: Forecasting Malware Spread Based on Compartmental Models in Epidemiology
Over the last few decades, the Internet has brought about a myriad of benefits to almost every aspect of our daily lives. However, malware attacks have also widely proliferated, mainly aiming at legitimate network users, resulting in millions of dollars in damages if proper protection and response m...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/5415724 |
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| _version_ | 1832551976449081344 |
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| author | Isabella Martínez Martínez Andrés Florián Quitián Daniel Díaz-López Pantaleone Nespoli Félix Gómez Mármol |
| author_facet | Isabella Martínez Martínez Andrés Florián Quitián Daniel Díaz-López Pantaleone Nespoli Félix Gómez Mármol |
| author_sort | Isabella Martínez Martínez |
| collection | DOAJ |
| description | Over the last few decades, the Internet has brought about a myriad of benefits to almost every aspect of our daily lives. However, malware attacks have also widely proliferated, mainly aiming at legitimate network users, resulting in millions of dollars in damages if proper protection and response measures are not settled and enforced. In this context, the paper at hand proposes MalSEIRS, a novel dynamic model, to predict malware distribution in a network based on the SEIRS epidemiological model. As a result, the time-dependent rates of infection, recovery, and loss of immunity enable us to capture the complex dynamism of malware spreading behavior, which is influenced by a variety of external circumstances. In addition, we describe both offensive and defensive techniques, based on the proposed MalSEIRS model, through extensive experimentation, as well as disclosing real-life malware campaigns that can be better understood by using the suggested model. |
| format | Article |
| id | doaj-art-c2e6ec2fcf114382899eb6cf9c2ea832 |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-c2e6ec2fcf114382899eb6cf9c2ea8322025-02-03T05:59:57ZengWileyComplexity1099-05262021-01-01202110.1155/2021/5415724MalSEIRS: Forecasting Malware Spread Based on Compartmental Models in EpidemiologyIsabella Martínez Martínez0Andrés Florián Quitián1Daniel Díaz-López2Pantaleone Nespoli3Félix Gómez Mármol4School of EngineeringSchool of EngineeringSchool of EngineeringFaculty of Computer ScienceFaculty of Computer ScienceOver the last few decades, the Internet has brought about a myriad of benefits to almost every aspect of our daily lives. However, malware attacks have also widely proliferated, mainly aiming at legitimate network users, resulting in millions of dollars in damages if proper protection and response measures are not settled and enforced. In this context, the paper at hand proposes MalSEIRS, a novel dynamic model, to predict malware distribution in a network based on the SEIRS epidemiological model. As a result, the time-dependent rates of infection, recovery, and loss of immunity enable us to capture the complex dynamism of malware spreading behavior, which is influenced by a variety of external circumstances. In addition, we describe both offensive and defensive techniques, based on the proposed MalSEIRS model, through extensive experimentation, as well as disclosing real-life malware campaigns that can be better understood by using the suggested model.http://dx.doi.org/10.1155/2021/5415724 |
| spellingShingle | Isabella Martínez Martínez Andrés Florián Quitián Daniel Díaz-López Pantaleone Nespoli Félix Gómez Mármol MalSEIRS: Forecasting Malware Spread Based on Compartmental Models in Epidemiology Complexity |
| title | MalSEIRS: Forecasting Malware Spread Based on Compartmental Models in Epidemiology |
| title_full | MalSEIRS: Forecasting Malware Spread Based on Compartmental Models in Epidemiology |
| title_fullStr | MalSEIRS: Forecasting Malware Spread Based on Compartmental Models in Epidemiology |
| title_full_unstemmed | MalSEIRS: Forecasting Malware Spread Based on Compartmental Models in Epidemiology |
| title_short | MalSEIRS: Forecasting Malware Spread Based on Compartmental Models in Epidemiology |
| title_sort | malseirs forecasting malware spread based on compartmental models in epidemiology |
| url | http://dx.doi.org/10.1155/2021/5415724 |
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