Special lssues

Secure Big Data Analytics for Smart City

Submission Deadline: 20 December 2020 (closed)

Guest Editors

Dr. Mamoun Alazab, Charles Darwin University, Australia.
Dr. Ameer Al-Nemrat, University of East London, United Kingdom.
Dr. Mohammad Shojafar, University of Surrey, United Kingdom.


As most of the urban cities are extensively transformed into smart cities of recent times, the number of intelligent devices connected across this smart city networks has risen gradually. Also, it will continue to grow explicitly in the coming days. It is estimated that the amount of smart city enabled IoT devices may increase exponentially and will exceed more than 10 billion within a short period, which imposes a considerable security threat and traffic demand across the smart city communication networks. With these influences, data volume across these devices may also continue to multiply shortly with huge communication overheads and security vulnerabilities. Further, the process of provision of data-centric smart city services will diversely make the next generation smart city services to be extremely complex and challenging in nature. However, the traditional methods of security practices do not scale well with emerging requirements of the smart city applications and may create a higher risk of security and privacy concerns across the communication networks.


On the other hand, protection to hardware devices also becomes an emerging concern as it forms an integral part of edge assisted smart city communication networks. Without the use of novel cybersecurity assisted secure big data analytics approaches, it is highly critical to overcome the security and privacy constraints of big data-related smart city applications. Actually, the increasing security and privacy threats across big data assisted smart city form the key enabler of incorporating cybersecurity and computational intelligence practices across the smart city applications. However, the increasing complexity in the development, management, and deployment of smart city services it creates the requirement of advanced cybersecurity progresses. Hence, developing secure and privacy-preserving big data analytics applications form the crucial need of our time.


This special issue aims to bring academic researchers, practitioners, and data scientists from the background of computer science and information technology to share their novel and innovative cybersecurity assisted innovative solutions for smart city applications. It further intends to explore recent advances and future trends of converging advanced security practices across big data applications.


Cyber security, big data solutions, Cloud-driven secure big data analytics, smart cities, deep learning and computer vision

Published Papers

  • Open Access


    Sentiment Analysis for Arabic Social Media News Polarity

    Adnan A. Hnaif, Emran Kanan, Tarek Kanan
    Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 107-119, 2021, DOI:10.32604/iasc.2021.015939
    (This article belongs to this Special Issue: Secure Big Data Analytics for Smart City)
    Abstract In recent years, the use of social media has rapidly increased and developed significant influence on its users. In the study of the behavior, reactions, approval, and interactions of social media users, detecting the polarity (positive, negative, neutral) of news posts is of considerable importance. This proposed research aims to collect data from Arabic social media pages, with the posts comprising the main unit in the dataset, and to build a corpus of manually-processed data for training and testing. Applying Natural Language Processing to the data is crucial for the computer to understand and easily manipulate the data. Therefore, Stop-Word… More >

Share Link