INTRUSION DETECTION SYSTEM FOR CLOUD BASED ON NAIVE BAYES AND HASHING
Amruta Deshmukh
, Kirti Girdhani , Nayan Keskar , Prajakta Gite
Cloud computing, Data security, encryption and decryption, data storage in cloud.
Network traffic in the cloud computing environment is characterized by large scale, high dimensionality, and high redundancy, these characteristics pose serious challenges to the development of cloud intrusion detection systems. Deep learning technology has shown considerable potential for intrusion detection. Therefore, this study aims to use deep learning to extract essential feature representations automatically and realize high detection performance efficiently. An effective stacked contractive autoencoder (SCAE) method is presented for unsupervised feature extraction. By using the SCAE method, better and robust low-dimensional features can be automatically learned from raw network traffic. We are creating a system that allows user to provide security to their files and protect them from hacker and avoid the malicious attacks, we are encrypting the password by hash and also if the hacker break are hash code it will get only the dummy data, OTP will also will there for authentication.
"INTRUSION DETECTION SYSTEM FOR CLOUD BASED ON NAIVE BAYES AND HASHING", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.7, Issue 5, page no.74 - 79, May-2022, Available :https://ijsdr.org/papers/IJSDR2205014.pdf
Volume 7
Issue 5,
May-2022
Pages : 74 - 79
Paper Reg. ID: IJSDR_200348
Published Paper Id: IJSDR2205014
Downloads: 000347204
Research Area: Engineering
Country: -, -, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
