In any era, communication is very important. In today's era effective data communication is important in all the fields. Here effectiveness was used in terms of secure communication. So, communication in the way that it is secure from any unauthorized access is important. In this paper a study and analysis were performed in the direction of image data security. This paper explores the current trends in the direction of image data security. It covers methods for image data security, tools and techniques, current challenges along with suggestive measures. It also explores the mitigating ways and directions to achieve high level image data security in the means of data communication.Cryptography and steganography methods were also being discussed, so that better methods can be selected for achieving high level data security.

Face recognition techniques play a crucial role in numerous disciplines of data security, verification, and authentication. The face recognition algorithm selects a face attribute from an image datasets. Recognize identification is an authentication device for verification as well as validation having both data analysis and feasible significance. The facerecognizing centered authentication framework can further be considered an AI technology implementation for instantly identifying a particular image. In this research, we are presenting a hybrid face recognition model (HFRM) using machine learning methods with “Speed Up Robust Features” (SURF), “scale-invariant feature transform” (SIFT), Locality Preserving Projections (LPP) &Principal component analysis (PCA) method. In the proposed HFRM model SURF method mainly detects the local feature efficiently. SIFT method mainly utilizes to detect the local features and recognize them. LPP retains the local framework of facial feature area which is generally quite meaningful than on the sequence kept by a 'principal component analysis (PCA) as well as “linear discriminate analysis” (LDA). The proposed HFRM method is compared with the existing (H. Zaaraoui et al., 2020) method and the experimental result clearly shows the outstanding performance in terms of detection rate and accuracy % over existing methods.