Artificial Intelligence for Security and Privacy in Ad Hoc and Sensor Networks (AI-SPASN)
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".
Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 3993
Please contact the Guest Editor or the Section Managing Editor at (ava.jiang@mdpi.com) for any queries.
Special Issue Editors
Interests: trust, privacy, and security in open computing systems; ad hoc and opportunistic computing systems; software system architecture
Special Issue Information
Dear Colleagues,
The world—both living and inanimate—is becoming more and more interconnected via a complex web of networks and sensors, collecting rapidly growing volumes of increasingly complex multimodal data and serving wider varieties of smart entities—from smartwatches to smart cities.
The immense scope and value of collected data provides motivation for attackers to invest in vastly more capable hardware and software—the latter including AI-based means of attack. The exponential increase in attack capabilities calls for countering them with the smartest software that can be built: AI-based controls.
These AI-based defenses must be deployed to increase the security and privacy of users, networks, applications, and data by eliminating or at least reducing vulnerabilities, recognizing threats, and preventing attacks or at least detecting them at the earliest available opportunity.
This Special Issue “Artificial Intelligence for Security and Privacy in Ad Hoc and Sensor Networks” (AI-SPASN) concentrates on new methodologies, techniques, and tools for identifying vulnerabilities and threats to the security and privacy of ad hoc and sensor networks and countering attacks on them while using the power of AI.
AI-SPASN invites high-quality contributions detailing novel, significant, and otherwise unpublished results. Solicited topics are limited to applications of Artificial Intelligence for improving security and privacy in ad hoc and sensor networks. The topics include, but are not limited to the following subareas and topics:
- AI-based methodologies improving security and privacy in ad hoc and sensor networks:
- Machine learning, adversarial machine learning, deep learning, and automated reasoning
- Privacy-preserving methodologies for networks, applications, and data
- Predictive network modeling
- Blockchain-based approaches
- Human–computer interactions
- AI-based techniques and tools improving security and privacy in ad hoc and sensor networks:
- Code and data obfuscation
- Prevention of network data leakage
- Network activity analysis and visualization
- Communication protocols
- Network data processing
- Application areas for ad hoc and sensor networks with AI-based security and privacy controls:
- Autonomous vehicles
- Biosensors
- Healthcare systems
- Internet of Things
- MANETs
- Opportunistic systems
- Space systems
- Transportation systems
Prof. Leszek T. Lilien
Dr. Ganapathy Mani
Guest Editors
Manuscript Submission Information
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Keywords
- adversarial machine learning
- autonomous vehicles
- biosensor networks
- blockchain
- cybersecurity
- deep learning
- human–computer interaction
- Internet of Things
- machine learning
- MANETs
- privacy
- opportunistic networks
- sensor networks
- smart sensors
- space networks
- transportation networks
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