Detection of Hardware Attacks and Security-Oriented Design in IoT Systems
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".
Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 15357
Special Issue Editors
Interests: hardware security; third-party IP protection; formal verification and program analysis; language-based security
Special Issue Information
Dear Colleagues,
The growing capabilities of sensing, computing, and communication devices are leading to an explosion in the use of IoT devices. IoT applications follow stringent demands, such as timing and function correctness, disturbances’ resilience, data integrity and confidentiality, etc. Thus, the disturbance sources and attack surfaces are growing and becoming more diversified, while IoT systems are scaling up and becoming more heterogeneous. Due to the significant effects of security vulnerabilities and attacks, IoT system development and deployment are facing significant challenges, such as sensitive data leakage, malicious intrusions of power grid, car hijacking, etc. Further, as a type of infrastructure, hardware trustworthiness and security are of crucial significance to IoT systems. Therefore, the purpose of this Special Issue is to seek contributions that exploit hardware attacks, detect hardware-related anomalies, follow a security-oriented hardware design (or hardware and software co-design), and use automated tools in IoT systems. Topics of interest include but are not limited to the following IoT security areas:
- Side-channel and fault attack, and resilience/countermeasures;
- Intrusion and anomaly detection;
- CPS security;
- Smart grid security;
- Hardware security and privacy;
- Formal method-based security verification, program analysis, and fuzzing;
- Security tool development;
- Security-oriented hardware design, or hardware and software co-design;
- Physical unclonable functions (PUFs), random number generators, cryptographic units, and key storage technologies;
- IoT devices and protocol security;
- Machine learning for IoT Security.
Dr. Xiaolong Guo
Dr. Dean Sullivan
Guest Editors
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