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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)
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Authors
M. Preetha,Ashwin Kumar P J,Dinesh D,Harish Suriya S
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Keywords
DATA MISMATCH AND ERROR DETECTION USING CLOUD
Abstract
In today's interconnected world, ensuring the security of cloud-based systems is paramount. Traditional intrusion detection systems (IDS) often struggle to keep pace with the evolving landscape of cyber threats. This project proposes a novel approach to enhancing cloud security through the integration of machine learning techniques into intrusion detection. By harnessing the power of machine learning algorithms, our system can adapt and learn from patterns in network traffic data, enabling it to detect anomalous behavior indicative of potential intrusions. Leveraging the scalability and flexibility of cloud computing, our solution offers real-time monitoring and analysis of network traffic across distributed cloud environments. Key features of our cloud-based intrusion detection system include automated threat detection, rapid response mechanisms, and customizable alerting capabilities. Through continuous learning and refinement, the system improves its detection accuracy over time, bolstering the resilience of cloud infra structures against emerging cyber threats. In summary, our project presents a proactive and adaptive approach to safeguarding cloud-based systems, combining the strengths of machine learning and cloud computing to create a robust Defense mechanism against intrusions. Protecting cloud-based systems from unauthorized access, data breaches, and other malicious activities is a critical concern for organizations worldwide. Traditional intrusion detection systems (IDS) often fall short in effectively identifying and mitigating these threats in dynamic cloud environments .To address this gap, our project focuses on leveraging the Random Forest algorithm to enhance cloud-based intrusion detection capabilities. High Accuracy Random Forest excels in handling complex, high- dimensional data and can effectively distinguish between normal and malicious network activities with high accuracy.
IJCRT's Publication Details
Unique Identification Number - IJCRTAM02045
Paper ID - 266411
Author type - Indian Author
Page Number(s) - 279-286
Pubished in - Volume 12 | Issue 8 | August 2024
DOI (Digital Object Identifier) -
No Of Downloads - 260
Author Country - India, -, -, -, -, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Published Paper PDF : - http://www.ijcrt.org/papers/IJCRTAM02045
Published Paper URL: : - http://ijcrt.org/viewfull.php?&p_id=IJCRTAM02045
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M. Preetha,Ashwin Kumar P J,Dinesh D,Harish Suriya S, "DATA MISMATCH AND ERROR DETECTION USING CLOUD", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 8, pp.279-286, August 2024, Available at :http://www.ijcrt.org/papers/IJCRTAM02045.pdf
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The International Journal of Creative Research Thoughts (IJCRT) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies.
The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world.
IJCRT is Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 7.97 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool), Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
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International Journal of Creative Research Thoughts (IJCRT)
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February 2026
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Last Date :
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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