A strong construction of S-box using Mandelbrot set an image encryption scheme.

The substitution box (S-box) plays a vital role in creating confusion during the encryption process of digital data. The quality of encryption schemes depends upon the S-box. There have been several attempts to enhance the quality of the S-box by using fractal chaotic mechanisms.

A Deep Learning-Based Privacy-Preserving Model for Smart Healthcare in Internet of Medical Things Using Fog Computing.

With the emergence of COVID-19, smart healthcare, the Internet of Medical Things, and big data-driven medical applications have become even more important. The biomedical data produced is highly confidential and private. Unfortunately, conventional health systems cannot support such a colossal amount of biomedical data.

A Novel Privacy Paradigm for Improving Serial Data Privacy.

Protecting the privacy of individuals is of utmost concern in today's society, as inscribed and governed by the prevailing privacy laws, such as GDPR. In serial data, bits of data are continuously released, but their combined effect may result in a privacy breach in the whole serial publication. Protecting serial data is crucial for preserving them from adversaries.

MobChain: Three-Way Collusion Resistance in Witness-Oriented Location Proof Systems Using Distributed Consensus.

Smart devices have accentuated the importance of geolocation information. Geolocation identification using smart devices has paved the path for incentive-based location-based services (LBS). However, a user's full control over a smart device can allow tampering of the location proof.

F-Classify: Fuzzy Rule Based Classification Method for Privacy Preservation of Multiple Sensitive Attributes.

With the advent of smart health, smart cities, and smart grids, the amount of data has grown swiftly. When the collected data is published for valuable information mining, privacy turns out to be a key matter due to the presence of sensitive information. Such sensitive information comprises either a single sensitive attribute (an individual has only one sensitive attribute) or multiple sensitive attributes (an individual can have multiple sensitive attributes).

Anonymity-preserving Reputation Management System for health sector.

In health sector, trust is considered important because it indirectly influences the quality of health care through patient satisfaction, adherence and the continuity of its relationship with health care professionals and the promotion of accurate and timely diagnoses. One of the important requirements of TRSs in the health sector is rating secrecy, which mandates that the identification information about the service consumer should be kept secret to prevent any privacy violation. Anonymity and trust are two imperative objectives, and no significant explicit efforts have been made to achieve both of them at the same time.