AI Based Periodic Forecasting Rate Prediction with Secured Optimized Cryptographic Method Sales Forecasting in Retail Business Sector

Artificial intelligence is the recent development in security and data analysis 8n business sector for maximize profits using data processing technology. Today's business is managing huge databases to store more information need to safety. The amount of data is expected to increase further base...

Full description

Saved in:
Bibliographic Details
Published in2022 International Interdisciplinary Humanitarian Conference for Sustainability (IIHC) pp. 1040 - 1046
Main Authors Ronaldo, Reza, Arora, Tarun Kumar, Agarwal, Seema, Lobanova, Alina, Vladimirovna, Vasko Tatyana, Yadav, Ajay Singh
Format Conference Proceeding
LanguageEnglish
Published IEEE 18.11.2022
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Artificial intelligence is the recent development in security and data analysis 8n business sector for maximize profits using data processing technology. Today's business is managing huge databases to store more information need to safety. The amount of data is expected to increase further based on the business needs to forecasting the developing trends. The retail business sectors need new data processing technologies and intelligent forecast models of sales trends with greater potential accuracy in security and reliability. This is an important prerequisite for planning and decision making of a company is a big issue. To resolve this problem, we propose a security surveillance and sales forecasting in the retail business sector based on periodic forecasting rate (PFR) and advanced encryption security (AES) to protect the data. This provides decision making based data forecasting based on the previous data detains which is applied beads n successive feature prediction rate. Then the prediction result processed in business sector in secure cryptography using advance verified authentication to protect the data. This proposed system produces higher prediction rate in forecasting rate and security in higher level as well than other methods.
DOI:10.1109/IIHC55949.2022.10059792