SPECIAL ISSUE PROPOSAL

Towards Trustworthy Mobile Information Management: Cross-Disciplinary Perspectives on Security and Privacy Challenges

In the age of big data, mobile information management faces significant security and privacy challenges. With the increasing number of mobile devices and the volume of data they generate, there is a growing need for effective security measures to protect users' personal information and sensitive data. Some key security and privacy challenges in mobile information management include Data Breaches: Mobile devices are vulnerable to data breaches, which can result in the loss or theft of sensitive information, such as financial data, personal identification information (PII), and medical records. Cybercriminals use various techniques to access users' devices and data, including malware and phishing attacks. Third-Party Apps:

Many users rely on third-party apps to enhance the functionality of their mobile devices. However, these apps can pose significant security risks, as they may collect and transmit users' data to third-party servers without their consent or knowledge. Sometimes, these apps may contain malware that can compromise users' devices and data. Cloud Storage: Many mobile devices are linked to cloud storage services, which can provide convenient access to data from multiple devices. However, this also increases the risk of data breaches and unauthorized access to sensitive data. Lack of Encryption: Encryption is a critical security feature that helps protect users' data from unauthorized access. However, many mobile devices lack proper encryption, leaving users' data vulnerable to attack. Device Theft or Loss: The loss or theft of a mobile device can result in the loss of sensitive data. Thieves can easily access users' data without proper security measures and use it for malicious purposes.

To address these challenges, users and organizations must implement effective security measures, such as strong passwords, two-factor authentication, data encryption, and mobile device management (MDM) software. Additionally, users should be cautious when downloading and using third-party apps and regularly back up their data to prevent the loss of important information.

The special issue aims to bring together researchers and practitioners to share their latest research findings and insights on the security and privacy challenges in mobile information management in the age of big data. The objective is to provide a platform for discussions and exchanging ideas on the latest developments, emerging trends, and best practices in mobile information management.

Original research and review articles in this area are encouraged in the following topic areas, including but are not limited to:

→ Open-source mobile security tools and their effectiveness in securing mobile devices

→ Data security and privacy in mobile cloud computing

→ Security and privacy challenges in mobile cloud computing systems

→ Trust models for mobile information management

→ Data breaches and cyber attacks on mobile devices

→ Privacy concerns in mobile information management

→ Third-party apps and their impact on mobile security and privacy

→ Cloud storage and its security implications in mobile information management

→ Encryption and its role in mobile data security

→ Mobile device theft and loss prevention measures

→ Mobile device management (MDM) strategies and their effectiveness in securing mobile devices

→ Mobile security and privacy regulations and compliance

Our Guest Editor Team Members:

Dr. Shadi Mahmoud Faleh AlZu’bi

Associate Professor at Department of Computer Science,

Faculty of Science and Information Technology,

Al-Zaytoonah University of Jordan, Amman, Jordan.

E-mail: smalzubi@zuj.edu.jo, dr.shadi.alzubi@gmail.com

Google Scholar: https://scholar.google.com/citations?user=7QuybU4AAAAJ&hl=en

ResearchGate: https://www.researchgate.net/profile/Shadi-Alzubi

→ Short Biography: Dr. Shadi Mahmoud Faleh AlZu’bi received his Ph.D. (Electronic and Computer / Computer Science) in 2011 at Brunel University, West London, United Kingdom, M.Sc. (Telecommunication Networks Management) in 2008 from University of Technology, Sydney, Australia, and B.Sc. (Computer and Network Engineering) in 2007 from Jordan University of Science and Technology, Jordan. He is currently working as Associate Professor at Department of Computer Science, Faculty of Science and Information Technology, Al-Zaytoonah University of Jordan, Amman, Jordan.

→ Research Interests: His current research interests include the extreme learning machine for several applications such as computer vision (image processing, medical imaging, 3D volume processing, computation acceleration using parallel processing and image compression and archiving), intelligent systems (smart agriculture, autonomous driving, smart cities, and NLP).

Dr. Maysam Abbod

Professor at Department of Electronic and Electrical Engineering

Brunel University London, Uxbridge, UB8 3PH, UK.

E-mail: maysam.abbod@brunel.ac.uk

Google Scholar: https://scholar.google.com/citations?user=aY6hO_8AAAAJ&hl=en

ResearchGate: https://www.researchgate.net/profile/Maysam-Abbod

→ Short Biography: Dr. Maysam Abbod (MIET, CEng, SMIEEE, SFHEA) He received BSc degree in Electrical Engineering from University of Technology in 1987and PhD in Control Engineering from University of Sheffield in 1992. From 1993 to 2006 he was with the Department of Automatic Control and Systems Engineering at the University of Sheffield as a research associate and senior research fellow.

→ Research Interests: His main research areas are Intelligent systems biomedical applications, Modelling and control of electrical power quality, Stock exchange market modelling, Intelligent systems for credit scoring, Intelligent hybrid modelling and control of distillation column systems, Time series modelling, Hybrid modelling techniques (multivariate/time series), Developments of advanced process modelling, optimisation and control strategies and Data mining and data driven modelling techniques.

Dr. Ashraf Darwish

Professor of Computer Science,

Faculty of Science,

Helwan University, Cairo, Egypt

E-mail: ashraf.darwish.eg@ieee.org

Google Scholar: https://scholar.google.com/citations?user=JJF6Q3cAAAAJ&hl=en

ResearchGate: https://www.researchgate.net/profile/Ashraf-Darwish-3

→ Short Biography: Dr. Ashraf Darwish is an Associate Professor of Computer Science and Acting as the Head of Mathematics and Computer Science Department at Faculty of Science, Helwan University, Egypt. He received the PhD degree in computer science from Saint Petersburg State University, Russian Federation in 2006. He received B.Sc. and M.Sc. in Mathematics from Faculty of Science, Tanta University, Egypt. He keeps in touch with his mathematical background through his research.

→ Research Interests: His research interests include information security, data and web mining, intelligent computing, image processing (in particular image retrieval, medical imaging), modeling and simulation, computational intelligence, sensor networks, theoretical foundations of computer science, cloud computing, and internet of things.

Important Dates

→ Submission deadline: May 30, 2024

→ Author notification: August 25, 2024

→ Revised papers due: October 30, 2024

→ Final notification: January 05, 2025

→ Publication: As per the policy of journal