Classical machine learning modeling demands considerable computing power for internal
calculations and training with big data in a reasonable amount of time. In recent years …

Deep learning and its variant techniques have surpassed classical machine algorithms due
to their high performance gaining remarkable results and are used in a broad range of …

Ensuring reliable data storage in a cloud environment is a challenging problem. One of the
efficient mechanisms used to solve it is the Redundant Residue Number System (RRNS) …

Logistic regression is a data statistical technique, which is used to predict the probability that
an event occurs. For some scenarios where the storage capabilities and computing …

The security issues that arise in public cloud environments raise several concerns about
privacy-preserving. Conventional security practices successfully protect stored and …

Fully Homomorphic Encryption (FHE) permits processing information in the form of
ciphertexts without decryption. It can ensure the security of information in common …

The protection of data processing is emerging as an essential aspect of data analytics,
machine learning, delegation of computation, Internet of Things, medical and financial …

Current security cloud practices can successfully protect stored data and data in transit, but
they do not keep the same protection during data processing. The data value extraction …

Abstract Intrusion Detection Systems (IDS) frequently employ Machine Learning (ML)
techniques for anomaly detection. Due to the time-consuming nature of detecting anomalies …

The water demand to achieve the food production for a growing population and the scarcity
of this resource, implies evaluating different strategies to increase crop water productivity …