REAL-TIME INTRUSION DETECTION SYSTEM FOR E-COMMERCE USING QR CODE

May 2022
Vol-8, Issue-3
Paper ID: 16745
ISSN: 2395-4396
Downloads: 0

Abstract & Details

Research Area
computer science
Keywords
QR Code E-Commerce Real time IDS Encryption techniques
Abstract
The major issues faced by ecommerce today are security, integrity and protection of the ecommerce products at the point of sales. The fake product claims by customers are generally affecting the entire system leading to financial losses. Intrusion detection system enhance the security of ecommerce systems using the QR code encryption techniques with alarming system. The project work provides solution to the existing system by encrypting a unique product ID with an image known as the QR code system. The system provides a counter attack by raising alarm. The problems of ecommerce conventional transaction processes have been identified to exist with loophole thereby causing financial damages by return of a fake product QR code. The system reacts according to the failures of the existing system. It is a web based platform that generates unique identifier for each products and making payment transaction for products after successful adding to cart. The new system will have the advantages over the existing and very advance method of product integrity. A real time response system is activated once an unrecognized QRcode is flipped before camera (displays product details or raise alarm for fake product).

Author Information

# Name Institute / Affiliation
1 Ezeh Kingsley Ikechukwu Enugu State University of Science and technology, Esut.
2 MOSUD Y. OLUMOYE caleb university, lagos State. Nigeria
3 OLUSOJI SOLOMON ADEYEMO caleb university, lagos State. Nigeria
4 EZE SHEDRACK CHUKWUEBUKA University of Nigeria.
5 FAMUYIWA, KOLAWOLE SAMUEL A Itori.computer science, D.S Adegbenro ICT

How to Cite

Use the following formats to cite this article in your research.

APA Style
Ikechukwu, Ezeh Kingsley, OLUMOYE, MOSUD Y., ADEYEMO, OLUSOJI SOLOMON, CHUKWUEBUKA, EZE SHEDRACK, & A, FAMUYIWA, KOLAWOLE SAMUEL (2022). REAL-TIME INTRUSION DETECTION SYSTEM FOR E-COMMERCE USING QR CODE. International Journal of Advance Research and Innovative Ideas In Education, 8(3), 1362-1369.
MLA Style
Ikechukwu, Ezeh Kingsley, et al. "REAL-TIME INTRUSION DETECTION SYSTEM FOR E-COMMERCE USING QR CODE." International Journal of Advance Research and Innovative Ideas In Education, vol. 8, no. 3, 2022, pp. 1362-1369.
IEEE Style
Ezeh Kingsley Ikechukwu, MOSUD Y. OLUMOYE, OLUSOJI SOLOMON ADEYEMO, EZE SHEDRACK CHUKWUEBUKA, and FAMUYIWA, KOLAWOLE SAMUEL A, "REAL-TIME INTRUSION DETECTION SYSTEM FOR E-COMMERCE USING QR CODE," International Journal of Advance Research and Innovative Ideas In Education, vol. 8, no. 3, pp. 1362-1369, 2022.
Vancouver Style
Ikechukwu Ezeh Kingsley, OLUMOYE MOSUD Y., ADEYEMO OLUSOJI SOLOMON, CHUKWUEBUKA EZE SHEDRACK, A FAMUYIWA, KOLAWOLE SAMUEL. REAL-TIME INTRUSION DETECTION SYSTEM FOR E-COMMERCE USING QR CODE. International Journal of Advance Research and Innovative Ideas In Education. 2022;8(3):1362-1369.
Harvard Style
Ikechukwu, Ezeh Kingsley, OLUMOYE, MOSUD Y., ADEYEMO, OLUSOJI SOLOMON, CHUKWUEBUKA, EZE SHEDRACK, & A, FAMUYIWA, KOLAWOLE SAMUEL (2022) 'REAL-TIME INTRUSION DETECTION SYSTEM FOR E-COMMERCE USING QR CODE', International Journal of Advance Research and Innovative Ideas In Education, 8(3), pp. 1362-1369.
Chicago Style
Ikechukwu, Ezeh Kingsley, et al. "REAL-TIME INTRUSION DETECTION SYSTEM FOR E-COMMERCE USING QR CODE." International Journal of Advance Research and Innovative Ideas In Education 8, no. 3 (2022): 1362-1369.
Turabian Style
Ikechukwu, Ezeh Kingsley, et al. "REAL-TIME INTRUSION DETECTION SYSTEM FOR E-COMMERCE USING QR CODE." International Journal of Advance Research and Innovative Ideas In Education 8, no. 3 (2022): 1362-1369.

Export Citation

Related Research

CYBERSECURITY WITH AI
SAHANA MURTHY 2026 Computer Science
PDF Unavailable
A NOVEL HYBRID IMAGE STEGANOGRAPHY TECHNIQUE BASED ON LSB AND CRYPTOGRAPHIC SECURITY
Pankaj Nandan et al. 2026 Computer Science
PDF Unavailable
AnimalAid AI: A Deep Learning Powered Early Warning System for Detecting Skin Infections and Diseases in Stray Dogs
Sharan Subhas Savalagi et al. 2026 Computer Science and Engineering
PDF Unavailable
LiverCare AI: Intelligent Medical Imaging Platform for Liver Tumor Detection and Clinical Guidance
Sheshank et al. 2026 Computer Science and Engineering
PDF Unavailable