Titlebook: Risks and Security of Internet and Systems; 18th International C Abderrahim Ait Wakrime,Guillermo Navarro-Arribas,R Conference proceedings

persistence

A Novel Software Defined Security Framework for SDNabstraction of the essential security features into a single software layer. SDS can be designed for traditional physical, virtualized, NFVs (Network Function Virtualization) and SDN (Software Defined Networking) based networks. This paper aims at developing an SDS framework for ONOS based SDN syste

宣稱

機密

Securing Autonomous Vehicles: Fundamentals, Challenges, and?Perspectives, enabling the proactive prevention of errors and attacks based on collected data. The overarching goal is to leverage data to not only prevent attacks but also rectify errors within autonomous vehicles.

瑪瑙

A New Efficient PUF-Based Mutual Authentication Scheme for?Dronese identity database into a single element, which reduces the amount of data that needs to be stored on a drone. Moreover, the proposed scheme is, in the worst case, equivalent to the most recent PUF-based mutual authentication schemes for drones in terms of communication data. Moreover, this paper give an implementation of the proposed scheme.

cloture

Painstaking

前面

0302-9743 eviewed and selected from 25 submissions. The papers detail security issues in internet-related applications, networks and systems.??.978-3-031-61230-5978-3-031-61231-2Series ISSN 0302-9743 Series E-ISSN 1611-3349

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0302-9743 S 2023, which took place in Rabat, Morocco, during December 6–8, 2023...The 13 full papers and 2 short papers included in this volume were carefully reviewed and selected from 25 submissions. The papers detail security issues in internet-related applications, networks and systems.??.978-3-031-61230-

Boycott

rded, transcribed, and analyzed with a two-stage thematic analysis, yielding in the end 76.8% inter-coders’ agreement..We identified six roles of PA, i.e., guide, interlocutor, safe box, lifesaver, secretary, and travel mate. We also break down the frequency with which each role is mentioned by the

Enthralling

Aisha Alansari,Razan Alfaqeer,Mohammad Hammoudeherage signal intensity), we use a 1D convolutional neural network (Conv1D) to learn bio-sensing features automatically. In experiments, we evaluate our method using DEAP and MAHNOB-HCI datasets. Our proposed multi-modal framework successfully outperforms both single- and multi-modal methods achievin