Despite extensive research efforts in Facial Expression Recognition (FER), achieving consistent performance across diverse datasets remains challenging. This challenge stems from variations in imaging conditions such as head pose, illumination, and background, as well as demographic factors like age, gender, and ethnicity. This paper introduces NIFER, a novel facial expression database designed to address this issue by enhancing racial diversity in existing datasets. NIFER comprises 3,481 images primarily featuring individuals with dark skin tones, collected in real-world settings. These images underwent preprocessing through face detection and histogram equalization before being categorized into five basic facial expressions using a deep learning model. Experiments conducted on both NIFER and FER-2013 datasets revealed a decrease in performance in multiracial FER compared to single-race FER, underscoring the importance of incorporating diverse racial representations in FER datasets to ensure accurate recognition across various ethnicities.

Mobile Cloud Computing (MCC) is a paradigm that integrates Cloud Computing and Mobile Computing to deliver a better Quality of Experience (QoE) and Quality of Service (QoS) to mobile users and cloud subscribers. Mobile Cloud Computing (MCC) inherited resource limitation from Mobile Computing which was solved with Cloud Computing. Meanwhile, Cloud Computing has inherent problems such as privacy of user’s data stored on cloud, intrusion detection, platform reliability, and security threats caused by multiple virtual machines. Thus, hindering the growth and the full acceptance of Mobile Cloud Computing (MCC) by subscribers. However, using a signature based hybrid cryptography ensures confidentiality, integrity, authentication and non-repudiation on resource-poverty devices used in Mobile Cloud Computing. This paper presents a data protection scheme where data is encrypted using a hybrid cryptographic algorithm which is composed of Advanced Encryption Standard (AES), Blake2b and Schnorr signature before being stored in the cloud storage (Amazon Simple Storage Server). Thus, data confidentiality, integrity, authentication and non-repudiation are ensured.