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Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2854567
Abstract: With the prosperity of wireless networks, vehicular networks (VNs) have been extensively studied in recent years. It is deployed to ensure road safety, enhance the driving experience, and reduce traffic congestion. However, VNs are vulnerable…
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Keywords:
flow table;
vehicular networks;
attack detection;
platform ... See more keywords
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Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2896783
Abstract: Software-defined networking (SDN) is the key outcome of extensive research efforts over the past few decades toward transforming the Internet infrastructure to be more programmable, configurable, and manageable. However, critical cyber-threats in the SDN-based cloud…
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Keywords:
based cloud;
ddos attack;
sdn based;
service ... See more keywords
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Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3021435
Abstract: While software defined network (SDN) brings more innovation to the development of future networks, it also faces a more severe threat from DDoS attacks. In order to deal with the single point of failure on…
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Keywords:
detection defense;
ddos attacks;
sdn environment;
ddos attack ... See more keywords
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Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3182818
Abstract: In an application-layer distributed denial of service (App-DDoS) attack, zombie computers bring down the victim server with valid requests. Intrusion detection systems (IDS) cannot identify these requests since they have legal forms of standard TCP…
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Keywords:
layer;
cuckoo search;
application layer;
app ddos ... See more keywords
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Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3197283
Abstract: Multi-microgrid systems can improve the resiliency and reliability of the power system network. Secure communication for multi-microgrid operation is a crucial issue that needs to be investigated. This paper proposes a multi-controller software defined networking…
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Keywords:
attack storage;
software defined;
defined networking;
architecture ... See more keywords
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Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3553742
Abstract: DDoS attacks are still one of the primary sources of problems on the Internet and continue to cause significant financial losses for organizations. To mitigate their impact, detection should preferably occur close to the attack…
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Keywords:
detection;
lightweight ddos;
attack;
attack detection ... See more keywords
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Published in 2023 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3199712
Abstract: The dynamic nature of the vehicular space exposes it to distributed malicious attacks irrespective of the integration of enabling technologies. The software-defined network (SDN) represents one of these enabling technologies, providing an integrated improvement over…
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Keywords:
sdn;
sdn based;
detection;
grid search ... See more keywords
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Published in 2018 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2017.2766636
Abstract: A Slow HTTP distributed denial of service (DDoS) attack causes a Web server to be unavailable, but it is difficult to detect in a network, because its traffic patterns are similar to those of legitimate…
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Keywords:
slow http;
http ddos;
ddos attack;
http ... See more keywords
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Published in 2022 at "PLoS ONE"
DOI: 10.1371/journal.pone.0273681
Abstract: Software-defined networks offer a new approach that attracts the attention of most academic and industrial circles due to the features it contains. However, some loopholes make such modern networks vulnerable to many types of attacks.…
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Keywords:
software defined;
defined networks;
trust;
attack ... See more keywords
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2
Published in 2023 at "Future Internet"
DOI: 10.3390/fi15020076
Abstract: Distributed denial of service (DDoS) attacks pose an increasing threat to businesses and government agencies. They harm internet businesses, limit access to information and services, and damage corporate brands. Attackers use application layer DDoS attacks…
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Keywords:
ddos;
layer;
deep learning;
ddos attacks ... See more keywords
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Published in 2024 at "Future Internet"
DOI: 10.3390/fi16120458
Abstract: The increasing threat of Distributed DDoS attacks necessitates robust, big data-driven methods to detect and mitigate complex Network and Transport Layer (NTL) attacks. This paper proposes EffiGRU-GhostNet, a deep-learning ensemble model for high-accuracy DDoS detection…
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Keywords:
deep learning;
detection;
effigru ghostnet;
data driven ... See more keywords