1. bookVolumen 22 (2022): Edición 3 (September 2022)
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Revista
eISSN
1314-4081
Primera edición
13 Mar 2012
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4 veces al año
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Mathematical Modelling of Malware Intrusion in Computer Networks

Publicado en línea: 22 Sep 2022
Volumen & Edición: Volumen 22 (2022) - Edición 3 (September 2022)
Páginas: 29 - 47
Recibido: 28 Dec 2021
Aceptado: 29 Apr 2022
Detalles de la revista
License
Formato
Revista
eISSN
1314-4081
Primera edición
13 Mar 2012
Calendario de la edición
4 veces al año
Idiomas
Inglés

1. Widyaninsih, P., D. R. S. Saputro, A. W. Nugroho. Susceptible Exposed Infected Recovery (SEIR) Model with Immigration: Equilibria Points and Its Application. – In: Proc. of ICSAS, 2018, AIP Conf. 2014, 020165-1-020165-7. https://doi.org/10.1063/1.5054569, https://aip.scitation.org/doi/pdf/10.1063/1.5054569 Search in Google Scholar

2. Chen, Z. Modeling and Defending against Internet Worm Attacks. Doctor of Philosophy Thesis, School of Electrical and Computer Engineering, Georgia Institute of Technology, May 2007. Search in Google Scholar

3. Mishra, B. K., A. Prajapati. Cyber Warfare: Worms’ Transmission Model. – International Journal of Advanced Science and Technology, Vol. 63, 2014, pp. 83-94. http://dx.doi.org/10.14257/ijast.2014.63.0810.14257/ijast.2014.63.08 Search in Google Scholar

4. Joseph, A. F., S. EAdewumi, Ih. Olalekan, K. Sunday. Computer Viruses: A Framework for Modeling Infection Susceptibility of Workstations. – Advances in Computer Science and Engineering, Vol. 14, 2015, No 2 pp. 97-109. DOI: 10.17654/ACSEMay2015_097_109. Abierto DOISearch in Google Scholar

5. Vetrivelan, P., M. Jagannath, T. S. Pradeep Kumar. Network Intrusion Detection and Prevention Systems on Flooding and Worm Attacks. Combating Security Breaches and Criminal Activity in the Digital Sphere Chapter: Network Intrusion Detection and Prevention Systems on Flooding and Worm Attacks, Publisher: IGI Global. Y. Asnath Victy Phamila, S. Geetha, Eds. June 2016. DOI: 10.4018/978-1-5225-0193-0. Abierto DOISearch in Google Scholar

6. Liu, L., R. K. L. Ko, G. Ren, X. Xu. Malware Propagation and Prevention Model for Time-Varying Community Networks within Software Defined Networks. – Security and Communication Networks, Vol. 2017, Article ID 2910310. 8 p. https://doi.org/10.1155/2017/291031010.1155/2017/2910310 Search in Google Scholar

7. Gowtham, K., N. Sricharan, R. Kisore. Mathematical Model to Study Propagation of Computer Worm in a Network. – In: Proc. of IEEE International Advance Computing Conference (IACC’15), June 2015, pp. 12-13. DOI: 10.1109/IADCC.2015.7154812. Abierto DOISearch in Google Scholar

8. Bradley, J. T., S. Gilamore. Analyzing Distributed Internet Worm Attacks Using Continuous State-Space Approximation of Process Algebra Models. – Journal of Computer and System Sciences, Vol. 74, 2008, pp. 1013-1032.10.1016/j.jcss.2007.07.005 Search in Google Scholar

9. Tang, Y., J. Luo, B. Xiao, G. Vei. Concept, Characteristics and Defending Mechanism of Worms, Special Section on Information and Communication System Security. – IEICE Trans. Inf. & Syst., Vol. E92–D, 2009, No 5. http://www4.comp.polyu.edu.hk/~csbxiao/paper/2009/IEICE-2009-worm.pdf10.1587/transinf.E92.D.799 Search in Google Scholar

10. Sidiroglou, St., A. D. Keromytis. A Network Worm Vaccine Architecture. – In: Proc. of 12th International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises, WETICE’03, June 2003. https://dl.acm.org/doi/10.5555/938984.939795 Search in Google Scholar

11. Kamal, S. U. M., R. J. A. Ali, H. K. Alani, E. S. Abdulmajed. Survey and Brief History on Malware in Network Security Case Study: Viruses, Worms, and Bots. – ARPN Journal of Engineering and Applied Sciences, Vol. 11, 2016, No 1, pp. 683-698. Search in Google Scholar

12. Masthan, M., R. Ravi. Detection and Prevention of Unknown Vulnerabilities on Enterprise IP Networks. – International Journal of Computer Science and Mobile Computing, Vol. 4, 2015, No 10, pp. 343-352. Search in Google Scholar

13. Souissi, S., A. Serhrouchni. AIDD: A Novel Generic Attack Modeling Approach. – In: Proc. of International Conference on High Performance Computing, Simulation (HPCS’14), July 2014, Bologne, Italy, 2014. 〈10.1109/HPCSim.2014.6903738〉. 〈hal01205824〉. Search in Google Scholar

14. Chapter 16 Attack Detection and Prevention. National Security Telecommunications Advisory Committee (NSTAC) Intrusion Detection Subgroup, [NetSec], WS 2006/2007. http://www.ccs-labs.org/~dressler/teaching/netzwerksicherheitws0607/16_AttackDetection-v2.pdf Search in Google Scholar

15. Bajaj, P., A. G. Roy. Source Code Analysis of Worms. http://www.micsymposium.org/mics_2004/Bajaj.pdf Search in Google Scholar

16. Mueller, P., B. Yadegari. The Stuxnet Worm. https://www2.cs.arizona.edu/~collberg/Teaching/466-566/2012/Resources/presentations/topic9-final/report.pdf Search in Google Scholar

17. Dimov, D., Y. Tzonev. Pass-the-Hash: One of the Most Prevalent Yet Underrated Attacks for Credentials Theft and Reuse. – In: Proc. of ACM International Conference Proceeding Series, Part F132086, 2017, pp. 149-154. ISBN 978-145035234-5. DOI: 10.1145/3134302.3134338. Abierto DOISearch in Google Scholar

18. Dimov, D., Y. Tzonev. Result Oriented Time Correlation between Security and Risk Assessments, and Individual Environment Compliance Framework. – In: Proc. of International Conference Europe Middle East & North Africa Information Systems and Technologies to Support Learning Smart Innovation, Systems and Technologies, 2019, pp. 373-383. ISBN 978-3-030-03576-1. DOI: 10.1007/978-3-030-03577-8_42. Abierto DOISearch in Google Scholar

19. Dimov, D., Y. Tzonev. Observing, Measuring and Collecting HDD Performance Metrics on a Physical Machine during Ransomware Attack. – Information & Security: An International Journal, Vol. 47, 2020, No 3, pp. 317-327. ISSN 0861-5160. DOI: 10.11610/isij.4723. Abierto DOISearch in Google Scholar

20. Popchev, I., D. Orozova. Towards Big Data Analytics in the e-Learning Space. – Cybernetics and Information Technologies, Vol. 19, 2019, No 3, pp. 16-24.10.2478/cait-2019-0023 Search in Google Scholar

21. Gnanaprasanambikai, L., N. Munusamy. Towards Big Data Analytics Data Pre-Processing and Classification for Traffic Anomaly Intrusion Detection Using NSLKDD Dataset. – Cybernetics and Information Technologies, Vol. 18, 2018, No 3, pp. 111-119.10.2478/cait-2018-0042 Search in Google Scholar

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