Node Clone Detection Protocols for Protect the WSNs: A Survey
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
The aim of this survey is to limit the largest number of these techniques in one place in the form of tables in order for the researcher to distinguish between them and know the extent of their benefits and disadvantages, as well as in order for the researcher to avoid falling into these defects as much as possible when he makes his own cloned contract detection system.In this paper, we have conducted a comprehensive review of the collection of several techniques for detecting centralized and distributed replication attacks, where nodes can be static or mobile sensor nodes, and tables were made summarizing what was mentioned in these techniques, each according to the results reached by the researchers.A Wireless Sensor Network (WSN) is a system of self-contained sensor nodes that monitor environmental (or physical) parameters with limitations on battery life, memory capacity, and computational power.WSNs are open to several types of attacks due to their use in unmoderated and insecure contexts.Cloning attacks, or (replication attacks), are a type of physical attack.A network adversary can quickly control a single node and collect data from it.Then reprogram it to make a copy of the captured node.Identifying a duplicate node becomes difficult once these clones are spread throughout the network and are accepted as original nodes.A technology or (protocol) must be found that ideally prevents the node from being cloned, as researchers have not been able to create a 100% secure system to prevent the effects of node cloning, which include network traffic monitoring, sensor spoofing, mock data injection, sabotage of data collection, signal jamming, denial-ofservice attacks, and disrupting network tasks.Creating a comparison table between techniques for preventing node cloning provides many benefits, including quickly finding the appropriate technique.It is considered a comprehensive and quick-access reference.It facilitates the decision-making process and prevents making mistakes that researchers made previously.It provides visual assistance for analyzing the strengths and weaknesses of each technique in an easier and faster way.The researcher was able to choose the most appropriate technology to develop and improve the quality of its performance to reach the ideal technology in future works.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,004 | 0,007 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle