Synthetic data generation is generally used in performance evaluation and function tests in data-intensive applications, as well as in various areas of data analytics, such as privacy-preserving data publishing (PPDP) and statistical disclosure…
Synthetic data generation is generally used in performance evaluation and function tests in data-intensive applications, as well as in various areas of data analytics, such as privacy-preserving data publishing (PPDP) and statistical disclosure…
Synthetic data generation is generally used in performance evaluation and function tests in data-intensive applications, as well as in various areas of data analytics, such as privacy-preserving data publishing (PPDP) and statistical disclosure…
Social networking websites have not only become the most prevalent communication tools in todays digital age but also one of the top big data sources. Big data advocates promote the promising benefits of big data applications to both users and…
Social networking websites have not only become the most prevalent communication tools in todays digital age but also one of the top big data sources. Big data advocates promote the promising benefits of big data applications to both users and…
as data size is growing up, cloud storage is becoming more familiar to store a significant amount of private information. Government and private organizations require transferring plenty of business files from one end to another. However, we will…
Synthetic data generation is generally used in performance evaluation and function tests in data-intensive applications, as well as in various areas of data analytics, such as privacy-preserving data publishing (PPDP) and statistical disclosure…
Synthetic data generation is generally used in performance evaluation and function tests in data-intensive applications, as well as in various areas of data analytics, such as privacy-preserving data publishing (PPDP) and statistical disclosure…
The wide adoption of mobile devices poses an imminent threat to preserving privacy. In order to prevent the leakage of sensitive information (such as the contact list, or private pictures) raised by inappropriate access, we propose a secure access…
Big data (BD) analytics is one of the critical components in the digitalization of the oil and gas (O&G) industry. Its focus is managing and processing a high volume of data to improve operational efficiency, enhance decision making and mitigate…
The importance of seismic big data exploration, especially in gas and oil industries, is indispensable. The processing of such complex data becomes more critical when its size is extremely large. These days the dispose of seismic big data over the…
There are millions of data been generated in various forms around us regularly which is approximately 2.5 quintillion bytes on the daily basis and most of the data are coming from social sites. Social sites are one of the biggest contributor of big…
Cloud deployment architectures have become a preferable computation model of Big Data (BD) operations. Their scalability, flexibility, and cost-effectiveness motivated this trend. In a such deployment model, the data are no longer physically…
The success of blockchain-based solutions, not only on a large scale, but since the beginning of the pilot phase, depends on a set of key factors such as performance, efficiency, usability, scalability. In particular, security, privacy and trust are…
The integration of new Information and Communication Technologies (ICT) within the heart of Industrial Control Systems (ICS) generated a large palette of innovative solutions. As such, the industry has undergone a new technological revolution, also…
Cloud computing technologies rely on powerful storage services to maintain massive data for users. Sensitive data are encrypted before outsourcing, but this limits the availability of data. Public-key encryption with keyword search (PEKS) contributes…
In real-world scenarios, in order to encourage one to report others crimes, judicial department usually rents independent cloud storage spaces to receive the precious evidences from whistleblowers. Since the uploaded data are not controlled by cloud…
The Internet of things (IoT) has certainly become one of the hottest technology frameworks of the year. It is deep in many industries, affecting people’s lives in all directions. The rapid development of the IoT technology accelerates the process of…
In this article, we analyze the inherent characteristics of smart grids, and point out that some electricity consumption data are very sensitive and should be encrypted. However, once the corresponding private key is compromised, the content of…
Wireless body area networks (WBANs) rely on powerful cloud storage services to manage massive medical data. As precise medical diagnosis analysis is heavily based on these medical data, any altered medical data may cause severe consequences, the…
Cloud computing technologies rely on powerful storage services to maintain massive data for users. Sensitive data are encrypted before outsourcing, but this limits the availability of data. Public-key encryption with keyword search (PEKS) contributes…
The importance of seismic big data exploration, especially in gas and oil industries, is indispensable. The processing of such complex data becomes more critical when its size is extremely large. These days the dispose of seismic big data over the…
Cooperative Intelligent Transport System (C-ITS) is a promising technology that aims to improve the traditional transport management systems. In C-ITS infrastructure Autonomous Vehicles (AVs) communicate wirelessly with other AVs, Road Side Units…