This book constitutes the post-conference proceedings of the 5th International Workshop on Attacks and Defenses for Internet-of-Things, ADIoT 2022, held in conjunction with ESORICS 2022, in Copenhagen, Denmark, in September 30, 2022, in hybrid mode. The 7 full papers and 3 short papers were carefully reviewed and selected from 18 submissions. This workshop focuses on IoT attacks and defenses and discusses either practical or theoretical solutions to identify IoT vulnerabilities and IoT security mechanisms.
This book constitutes the post-conference proceedings of the 5th International Workshop on Attacks and Defenses for Internet-of-Things, ADIoT 2022, held in conjunction with ESORICS 2022, in Copenhagen, Denmark, in September 30, 2022, in hybrid mode.
The 7 full papers and 3 short papers were carefully reviewed and selected from 18 submissions.
This workshop focuses on IoT attacks and defenses and discusses either practical or theoretical solutions to identify IoT vulnerabilities and IoT security mechanisms.
The Final Round: Benchmarking NIST LWC Ciphers on Microcontrollers.- Evolving a Boolean Masked Adder Using Neuroevolution.- Explainable AI and Deep Autoencoders Based Security Framework for IoT Network Attack Certainty.- Constraints and Evaluations on Signature Transmission Interval for Aggregate Signatures with Interactive Tracing Functionality.- Post-Quantum Secure Communication with IoT Devices Using Kyber and SRAM Behavioral and Physical Unclonable Functions.- Effective Segmentation of RSSI Timeseries Produced by Stationary IoT Nodes.- Consumer-friendly Methods for Privacy Protection Against Cleaning Robots.- Resource Efficient Federated Deep Learning for IoT Security Monitoring.- Man-in-the-OBD: A modular, Protocol Agnostic Firewall for Automotive Dongles to Enhance Privacy and Security.- Mapping the Security Events to the MITRE ATT&CK Attack Patterns to Forecast Attack Propagation.
The Final Round: Benchmarking NIST LWC Ciphers on Microcontrollers.- Evolving a Boolean Masked Adder Using Neuroevolution.- Explainable AI and Deep Autoencoders Based Security Framework for IoT Network Attack Certainty.- Constraints and Evaluations on Signature Transmission Interval for Aggregate Signatures with Interactive Tracing Functionality.- Post-Quantum Secure Communication with IoT Devices Using Kyber and SRAM Behavioral and Physical Unclonable Functions.- Effective Segmentation of RSSI Timeseries Produced by Stationary IoT Nodes.- Consumer-friendly Methods for Privacy Protection Against Cleaning Robots.- Resource Efficient Federated Deep Learning for IoT Security Monitoring.- Man-in-the-OBD: A modular, Protocol Agnostic Firewall for Automotive Dongles to Enhance Privacy and Security.- Mapping the Security Events to the MITRE ATT&CK Attack Patterns to Forecast Attack Propagation.
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