SummaryCloud computing (CC) refers to the on‐demand availability of network resources, particularly data storage and processing power, without requiring special or direct administration by users. CC, which just made its debut as a collection of public and private data centers, provides clients with a unified platform throughout the Internet. Cloud computing has revolutionized the world, opening up new horizons with bright potential due to its performance, accessibility, low cost, and many other benefits. Due to the exponential rise of cloud computing, systems based on cloud computing now require an effective data security mechanism. Comprehensive security policies, corporate security culture, and cloud security solutions are used to ensure the level of cloud data security. Many techniques exist to protect data communication in the cloud environment, including encryption. Encryption algorithms play an important role in information security systems and various cloud computing‐based systems. Current researchers have focused on lightweight cryptography, genetics‐based cryptography, and machine learning (ML) algorithms for security in CC. This review study analyses CC security threats, problems, and solutions that use one or more algorithms. The work discusses several lightweight cryptographies, genetics‐based cryptography and different ML algorithms that are used to overcome cloud security issues, including supervised, unsupervised, semi‐supervised, and reinforcement learning. Moreover, we enlist future research directions to secure CC models.

The Internet of Things (IoT) is a rapidly expanding network of interconnected things that use embedded sensors to gather and share data in real-time. IoT technologies have given rise to many networking applications in our everyday life such as smart homes, smart cities, smart transport, etc. Smart healthcare is one such application that has been revolutionized by the IoT, introducing a new branch of IoT known as the Internet of Medical Things (IoMT). IoMT encompasses an entire ecosystem consisting of smart wearable, implantable sensing equipment’s or devices, transmitters that are critical for monitoring the patients remotely and continuing the real-time and has opened the door to new innovative smart healthcare approaches while improving patient care outcomes. IoMT wearable and embedded sensing devices are commonly utilized in smart healthcare to capture medical data and transmit the medical data in a communication network stored in the cloud. The large volume of data generated and transmitted by these IoMT devices is rising at an exponential rate, resulting in an increase in security and privacy vulnerabilities of healthcare data. In order to ensure the Confidentiality and integrity of the IoMT devices and the Medical data, there should be proper security and privacy measures such as access control, passwords, multifactor authentication, and encryption of data generated, transmitted, or processed in the IoMT framework. In this paper, we identified the internet of things and its applications in smart healthcare systems. Additionally, the paper focuses on the architecture of IoMT, and several challenges, including the IoMT security and privacy requirements, and attack taxonomy. Finally, the review focuses on current security and privacy-enhancing techniques for IoMT or healthcare systems. The conclusion and future work are then discussed.