Research Topic

Intelligent Defenses for Secure Mobile Software and Systems

About this Research Topic

Modern computing has been rapidly moving to mobile platforms. As a result, computer software and systems are increasingly gaining mobility. For instance, to most information technology users nowadays, software applications are mobile apps running on their smartphones, tablets, and other mobile devices. This is also true for today’s enterprises and government agencies. Meanwhile, accompanying the tremendous benefits of mobility has been the rising concern about the security of mobile apps and systems. Consequential instances of security breaches in this domain happen every day, causing catastrophic losses of monetary assets and even human lives. Despite significant advances being made in defending the security risks, threats, and attacks, the contemporary mobile ecosystem remains the major loophole in cybersecurity. The arms race between defenders and adversaries continues and new malware never stops emerging. Thus, there is an urgent need for more advanced understanding and techniques on mobile software and system security defenses. Along with this standing challenge, intelligent (e.g., data-driven) methodologies, such as machine learning, data mining, deep learning, have demonstrated exciting prospects for software and information assurance.

This Research Topic aims to disseminate hence promote innovative, cutting-edge research contributions on the security defense of modern mobile software and systems, with a focus on intelligent approaches that leverage the availability of big data and the power of artificial intelligence (AI) and machine/deep learning (ML/DL) that have achieved revolutionary progress in recent years. Significant advances in forensics and anti-forensics concerning mobile apps, systems, devices, and ecosystems are highly relevant, but equally important are empirical works aiming to understand the strengths and weaknesses of current mobile security solutions while informing improvement strategies and future research directions. Both theoretical foundations and practical tools are well suited, and relevant user studies and industrial cases would also well align with the goals of this special issue.

Accordingly, topics being solicited range from data-driven intrusion detection systems (IDS) and ML/DL-based digital forensics to social/economic issues and human factors in mobile security, including but not limited to the following:

• Malware detection and family attribution
• Mobile software vulnerability analysis
• Defenses against inter-app collusion
• Anomaly detection in mobile systems
• Malicious code analysis and reverse engineering
• App security certification and forensics
• Security policy engineering for mobile apps
• Anti-analysis and anti-forensics techniques
• Robustness and sustainability of app security defenses
• Machine/deep learning for app security classification and diagnosis
• App store mining and analysis for security
• Security-relevant data analytics for mobile software and systems
• Social, behavioral, economic issues in mobile app/system security
• Mobile accessibility with security
• Authentication and access control in mobile apps and systems
• Secure app/system development
• Secure mobile ecosystem


Keywords: Mobile App, Mobile System, Mobile Security, Robustness, Sustainability, Forensics, Adversary, Malware Defense, Anomaly Detection, Authentication, Secure Ecosystem, Machine Learning, Data Analytics, AI, Access Control, Accessibility


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Modern computing has been rapidly moving to mobile platforms. As a result, computer software and systems are increasingly gaining mobility. For instance, to most information technology users nowadays, software applications are mobile apps running on their smartphones, tablets, and other mobile devices. This is also true for today’s enterprises and government agencies. Meanwhile, accompanying the tremendous benefits of mobility has been the rising concern about the security of mobile apps and systems. Consequential instances of security breaches in this domain happen every day, causing catastrophic losses of monetary assets and even human lives. Despite significant advances being made in defending the security risks, threats, and attacks, the contemporary mobile ecosystem remains the major loophole in cybersecurity. The arms race between defenders and adversaries continues and new malware never stops emerging. Thus, there is an urgent need for more advanced understanding and techniques on mobile software and system security defenses. Along with this standing challenge, intelligent (e.g., data-driven) methodologies, such as machine learning, data mining, deep learning, have demonstrated exciting prospects for software and information assurance.

This Research Topic aims to disseminate hence promote innovative, cutting-edge research contributions on the security defense of modern mobile software and systems, with a focus on intelligent approaches that leverage the availability of big data and the power of artificial intelligence (AI) and machine/deep learning (ML/DL) that have achieved revolutionary progress in recent years. Significant advances in forensics and anti-forensics concerning mobile apps, systems, devices, and ecosystems are highly relevant, but equally important are empirical works aiming to understand the strengths and weaknesses of current mobile security solutions while informing improvement strategies and future research directions. Both theoretical foundations and practical tools are well suited, and relevant user studies and industrial cases would also well align with the goals of this special issue.

Accordingly, topics being solicited range from data-driven intrusion detection systems (IDS) and ML/DL-based digital forensics to social/economic issues and human factors in mobile security, including but not limited to the following:

• Malware detection and family attribution
• Mobile software vulnerability analysis
• Defenses against inter-app collusion
• Anomaly detection in mobile systems
• Malicious code analysis and reverse engineering
• App security certification and forensics
• Security policy engineering for mobile apps
• Anti-analysis and anti-forensics techniques
• Robustness and sustainability of app security defenses
• Machine/deep learning for app security classification and diagnosis
• App store mining and analysis for security
• Security-relevant data analytics for mobile software and systems
• Social, behavioral, economic issues in mobile app/system security
• Mobile accessibility with security
• Authentication and access control in mobile apps and systems
• Secure app/system development
• Secure mobile ecosystem


Keywords: Mobile App, Mobile System, Mobile Security, Robustness, Sustainability, Forensics, Adversary, Malware Defense, Anomaly Detection, Authentication, Secure Ecosystem, Machine Learning, Data Analytics, AI, Access Control, Accessibility


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

22 January 2022 Manuscript
21 February 2022 Manuscript Extension

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

22 January 2022 Manuscript
21 February 2022 Manuscript Extension

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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