  With an exponential growth in the use of digital image data, the need for
efficient transmission methods has become imperative. Traditional image
compression techniques often sacrifice image fidelity for reduced file sizes,
presenting a challenge in maintaining both quality and efficiency. They also
tend to compromise on security, leaving images vulnerable to threats such as
man-in-the-middle attacks. This paper proposes an autoencoder architecture for
image compression so as to not only help in dimensionality reduction but also
inherently encrypt the images. The paper also introduces the use of a composite
loss function that combines reconstruction loss and residual loss for improved
performance. The autoencoder architecture is designed to achieve optimal
dimensionality reduction and regeneration accuracy while safeguarding the
compressed data during transmission or storage. Images regenerated by the
autoencoder are evaluated against three key metrics: reconstruction quality,
compression ratio, and one-way delay during image transfer. The experiments
reveal that the proposed architecture achieves an SSIM of 97.5% over the
regenerated images and an average latency reduction of 87.5%, indicating its
effectiveness as a secure and efficient solution for compressed image transfer.
