Atnaujinkite slapukų nuostatas

El. knyga: Internet of Things: 7th IFIP WG 5.5 International Cross-Domain Conference, IFIPIoT 2024, Nice, France, November 6-8, 2024, Proceedings

Edited by , Edited by , Edited by

DRM apribojimai

  • Kopijuoti:

    neleidžiama

  • Spausdinti:

    neleidžiama

  • El. knygos naudojimas:

    Skaitmeninių teisių valdymas (DRM)
    Leidykla pateikė šią knygą šifruota forma, o tai reiškia, kad norint ją atrakinti ir perskaityti reikia įdiegti nemokamą programinę įrangą. Norint skaityti šią el. knygą, turite susikurti Adobe ID . Daugiau informacijos  čia. El. knygą galima atsisiųsti į 6 įrenginius (vienas vartotojas su tuo pačiu Adobe ID).

    Reikalinga programinė įranga
    Norint skaityti šią el. knygą mobiliajame įrenginyje (telefone ar planšetiniame kompiuteryje), turite įdiegti šią nemokamą programėlę: PocketBook Reader (iOS / Android)

    Norint skaityti šią el. knygą asmeniniame arba „Mac“ kompiuteryje, Jums reikalinga  Adobe Digital Editions “ (tai nemokama programa, specialiai sukurta el. knygoms. Tai nėra tas pats, kas „Adobe Reader“, kurią tikriausiai jau turite savo kompiuteryje.)

    Negalite skaityti šios el. knygos naudodami „Amazon Kindle“.

This book constitutes the refereed proceedings of the 7th IFIP WG 5.5 International Cross-Domain Conference on Internet of Things, IFIPIoT 2024, in Nice, France, in November 2024.737





The 13 full papers and 4 short papers presented were carefully reviewed and selected from a total of 28 submissions to the main conference. They were organized in topical sections as follows: Hardware/Software Solutions for IoT and CPS; Electronics and Signal Processing for IoT ; Networking and Communications Technology for IoT; Artificial Intelligence and Machine Learning Technologies for IoT; Cyber Security/Privacy/Trust for IoT and CPS and IoT or CPS Applications and Use cases.
.- Hardware/Software Solutions for IoT and CPS .



.- Relocation of container-based services in a MEC-NFV orchestrated
environment.



.- The Good, the Bad and the Ugly: Investigating the Effectiveness of Graph
Deep Neural Networks for Anomaly Detection in Industrial Control Systems.



.- Programmable and Scalable Bit-Sliced VLSI Architecture for Decision
Tree-Based Machine Learning Edge Inference.



.- Electronics and Signal Processing for IoT.



.- Efficient Implementation of Authenticated Encryption on 16-bit MSP430
Microcontrollers.



.- Networking and Communications Technology for IoT.



.- Multi-layered Model for Performance Evaluation of oneM2M-based IoT
Solution.



.- An Information-Theoretic Approach for Anomaly Detection in RPL-based
Internet of Things.



.- Formal Development of a Delay-Tolerant Multicast Protocol for Wireless
Sensors.



.- Artificial Intelligence and Machine Learning Technologies for IoT.



.- Graph-based Classification of IoT Malwarev Families Enhanced by Fuzzy
Hashing.



.- Error Resiliency and Adversarial Robustness in Convolutional Neural
Networks: an Empirical Analysis.



.- Cyber Security/Privacy/Trust for IoT and CPS.



.- A Blockchain and IPFS-Enhanced Model for Attack Detection and Resource
Efficiency.



.- Hardware Trojan Key-Corruption Detection with Automated Neural
Architecture Search.



.- IoT or CPS Applications and Use cases.



.- Actuation Conflict Management in Internet of Things Systems DevOps: A
Discrete Event Modeling And Simulation Approach.



.- Leveraging Task-Specific VAEs for Efficient Exemplar Generation in HAR.



.- The Role of Ethics in Smart Homes A Workshop-Based Approach.



.- Digital Twin-based Security Orchestration, Automation and Response for IoT
and CPS.



.- GreenMov: a Fiware based Interoperable Solution to Reduce the
Environmental Impact of Mobility.



.- Dynamic IoT Determination of Overall Heat Transfer Coefficient in a
Portable Cabin in Kuwait.