Paper Title
Modeling And Predicting Cyber Hacking Breaches
Article Identifiers
Registration ID: IJNRD_181821
Published ID: IJNRD2206072
: http://doi.one/10.1729/Journal.30690
Keywords
Abstract
Using cyber occurrence informational indexes, we can better understand the development of the danger situation. However, numerous investigations need to be completed. Using a break event informational collection (2005-2017), we compare it to 12 years of cyber hacking activities, including malware assaults, in this paper. As opposed to the findings of the writing, we demonstrate that both hacking break occurrence between appearance times and penetration sizes ought to be visualized by stochastic procedures instead of conveyances, since they show autocorrelations. In order to fit the appearance times and break sizes separately, we propose specific stochastic procedure models. We also demonstrate that these models can also predict the appearance times and penetration sizes in advance. Using the informational index, we conduct both subjective and quantitative pattern analyses in order to gain additional insight into hacking attacks. Although cyber hacking risks are declining in terms of their recurrence, they are not decreasing in terms of their impact on society. This is based on a number of cybersecurity experiences we draw from.
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How To Cite (APA)
Ranjit Patnaik Sekharamantri & GRANDHI AVINASH (June-2022). Modeling And Predicting Cyber Hacking Breaches. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 7(6), 635-638. http://doi.one/10.1729/Journal.30690
Issue
Volume 7 Issue 6, June-2022
Pages : 635-638
Other Publication Details
Paper Reg. ID: IJNRD_181821
Published Paper Id: IJNRD2206072
Downloads: 000122030
Research Area: Computer Science & TechnologyÂ
Author Type: Indian Author
Country: Payakaraopeta, Andhra Pradesh, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2206072.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2206072
Crossref DOI: http://doi.one/10.1729/Journal.30690
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