An optimal and efficient data security technique through crypto-stegano for E-commerce.

Area of Science:

• Computer Science
• Information Security
• Cryptography

Background:

• E-commerce transactions are vulnerable to various security attacks due to inadequate security infrastructure.
• Data security is crucial for protecting confidential information during electronic commerce.
• Existing security measures often fall short in providing comprehensive protection against sophisticated threats.

Purpose of the Study:

• To propose an optimal and efficient data security technique for e-commerce transactions.
• To enhance the security of online commercial transactions using a hybrid approach.
• To address the vulnerabilities in current e-commerce security protocols.

Main Methods:

• A novel approach combining the Elgamal cryptosystem for encryption and Least Significant Bit (LSB) image steganography for data hiding.
• Implementation of Elgamal encryption at the merchant side to secure sensitive transaction data.
• Application of LSB steganography to embed encrypted data into images, creating stego-images, followed by Discrete Cosine Transform (DCT) using an autoencoder for optimization.

Main Results:

• The proposed method successfully encrypts sensitive data using Elgamal and hides it within images using LSB steganography.
• The DCT technique with an autoencoder optimizes the stego-image for efficient transmission.
• Performance metrics such as Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index (SSIM) were evaluated, alongside image entropy, demonstrating high-level performance.

Conclusions:

• The integrated Elgamal encryption and LSB image steganography technique provides a robust and efficient solution for securing e-commerce transactions.
• The proposed method significantly enhances data confidentiality and transaction security in the e-commerce environment.
• The experimental results validate the effectiveness and efficiency of the proposed security framework.