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https://ruomo.lib.uom.gr/handle/7000/1376
Πλήρης εγγραφή μεταδεδομένων
Πεδίο DC | Τιμή | Γλώσσα |
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dc.contributor.author | Segura, Gustavo A. Nunez | - |
dc.contributor.author | Skaperas, Sotiris | - |
dc.contributor.author | Chorti, Arsenia | - |
dc.contributor.author | Mamatas, Lefteris | - |
dc.contributor.author | Margi, Cintia Borges | - |
dc.date.accessioned | 2022-09-26T06:33:58Z | - |
dc.date.available | 2022-09-26T06:33:58Z | - |
dc.date.issued | 2020 | - |
dc.identifier | 10.1109/ICCWorkshops49005.2020.9145136 | en_US |
dc.identifier.isbn | 978-1-7281-7440-2 | en_US |
dc.identifier.uri | https://doi.org/10.1109/ICCWorkshops49005.2020.9145136 | en_US |
dc.identifier.uri | https://ruomo.lib.uom.gr/handle/7000/1376 | - |
dc.description.abstract | Software-defined networking (SDN) is a promising technology to overcome many challenges in wireless sensor networks (WSN), particularly with respect to flexibility and reuse. Conversely, the centralization and the planes' separation turn SDNs vulnerable to new security threats in the general context of distributed denial of service (DDoS) attacks. Stateof-the-art approaches to identify DDoS do not always take into consideration restrictions in typical WSNs e.g., computational complexity and power constraints, while further performance improvement is always a target. The objective of this work is to propose a lightweight but very efficient DDoS attack detection approach using change point analysis. Our approach has a high detection rate and linear complexity, so that it is suitable for WSNs. We demonstrate the performance of our detector in software-defined WSNs of 36 and 100 nodes with varying attack intensity (the number of attackers ranges from 5% to 20% of nodes). We use change point detectors to monitor anomalies in two metrics: the data packets delivery rate and the control packets overhead. Our results show that with increasing intensity of attack, our approach can achieve a detection rate close to 100% and that the type of attack can also be inferred. | en_US |
dc.language.iso | en | en_US |
dc.subject | FRASCATI::Engineering and technology | en_US |
dc.subject | FRASCATI::Natural sciences::Computer and information sciences | en_US |
dc.subject.other | computer network security | en_US |
dc.subject.other | IP networks | en_US |
dc.subject.other | software defined networking | en_US |
dc.subject.other | telecommunication security | en_US |
dc.subject.other | wireless sensor networks | en_US |
dc.subject.other | Computer crime | en_US |
dc.subject.other | Time series analysis | en_US |
dc.subject.other | Detectors | en_US |
dc.subject.other | Monitoring | en_US |
dc.subject.other | Measurement | en_US |
dc.title | Denial of Service Attacks Detection in Software-Defined Wireless Sensor Networks | en_US |
dc.type | Conference Paper | en_US |
dc.contributor.department | Τμήμα Εφαρμοσμένης Πληροφορικής | en_US |
local.identifier.firstpage | 1 | en_US |
local.identifier.lastpage | 7 | en_US |
local.identifier.volumetitle | 2020 IEEE International Conference on Communications Workshops (ICC Workshops) | en_US |
Εμφανίζεται στις Συλλογές: | Τμήμα Εφαρμοσμένης Πληροφορικής |
Αρχεία σε αυτό το Τεκμήριο:
Αρχείο | Περιγραφή | Μέγεθος | Μορφότυπος | |
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Σ40.pdf | 136,6 kB | Adobe PDF | Προβολή/Ανοιγμα |
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