Users' privacy is vulnerable at all stages of the deep learning process. Sensitive information
of users may be disclosed during data collection, during training, or even after releasing the …

Anonymization is a practical solution for preserving user's privacy in data publishing. Data
owners such as hospitals, banks, social network (SN) service providers, and insurance …

This article will highlight negative personal privacy and informational security outcomes that
may arise from development programs currently pursued in smart cities. It aims to illustrate …

With the widespread adoption of various mobile applications, the amount of traffic in wireless
networks is growing at an exponential rate, which exerts a great burden on mobile core …

The development of Internet of Things (IoT) brings new changes to various fields.
Particularly, industrial IoT (IIoT) is promoting a new round of industrial revolution. With more …

Graph theory (GT) concepts are potentially applicable in the field of computer science (CS)
for many purposes. The unique applications of GT in the CS field such as clustering of web …

Differential privacy provides strong privacy preservation guarantee in information sharing.
As social network analysis has been enjoying many applications, it opens a new arena for …

Social media has transformed the mode of communication globally by providing an
extensive system for exchanging ideas, initiating business contracts, and proposing new …

The increasing popularity of social media has attracted a huge number of people to
participate in numerous activities on a daily basis. This results in tremendous amounts of …

Intelligent data handling techniques are beneficial for users; to store, process, analyze and
access the vast amount of information produced by electronic and automated devices. The …