Please use this identifier to cite or link to this item:
https://rda.sliit.lk/handle/123456789/1604
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Amarasinghe, A.M.S.N. | - |
dc.contributor.author | Wijesinghe, W.A.C.H. | - |
dc.contributor.author | Nirmana, D.L.A. | - |
dc.contributor.author | Jayakody, A. | - |
dc.contributor.author | Priyankara, A.M.S. | - |
dc.date.accessioned | 2022-03-14T07:20:30Z | - |
dc.date.available | 2022-03-14T07:20:30Z | - |
dc.date.issued | 2019-12-05 | - |
dc.identifier.isbn | 978-1-7281-4170-1/19 | - |
dc.identifier.uri | http://rda.sliit.lk/handle/123456789/1604 | - |
dc.description.abstract | Security of the computer systems is the most important factor for single users and businesses, because an attack on a system can cause data loss and considerable harm to the businesses. Due to the increment of the range of the cyber-attacks, anti-virus scanners cannot fulfil the need for protection. Hence, the increment of the skill level that required for the development of cyber threats and the availability of the attacking tools on the internet, the need for Artificial Intelligence-based systems, is a must to the users. The proposed approach is an automated system that consists of a mechanism to deploy vulnerabilities and a rich database with known vulnerabilities. The Convolutional Neural Networks detects the vulnerabilities and the artificial intelligence-based generative models do the prevention process and improves reliability. The prediction procedure implemented using the algorithm called “Time Series” and the model called “SARIMA”. These implementations give an output with considerable accuracy. | en_US |
dc.language.iso | en | en_US |
dc.publisher | 2019 1st International Conference on Advancements in Computing (ICAC), SLIIT | en_US |
dc.relation.ispartofseries | Vol.1; | - |
dc.subject | cyber-attacks | en_US |
dc.subject | cyber-attack prediction | en_US |
dc.subject | cyber-attack detection | en_US |
dc.subject | data mining | en_US |
dc.subject | Malware | en_US |
dc.title | AI Based Cyber Threats and Vulnerability Detection,Prevention and Prediction System | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1109/ICAC49085.2019.9103372 | en_US |
Appears in Collections: | 1st International Conference on Advancements in Computing (ICAC) | 2019 Research Papers - Dept of Computer Systems Engineering Research Papers - IEEE |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
AI_Based_Cyber_Threats_and_Vulnerability_Detection_Prevention_and_Prediction_System.pdf Until 2050-12-31 | 422.62 kB | Adobe PDF | View/Open Request a copy |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.