Detecting DDoS Attack on SDN Due to Vulnerabilities in OpenFlow
Not on the map. Why?
Abstract (arXiv)
Software Defined Networking (SDN) is a network paradigm shift that facilitates comprehensive network programmability to cope with emerging new technologies such as cloud computing and big data. SDN facilitates simplified and centralized network management enabling it to operate in dynamic scenarios. Further, SDN uses the OpenFlow protocol for communication between the controller and its switches. The OpenFlow creates vulnerabilities for network attacks especially Distributed Denial of Service (DDoS). DDoS attacks are launched from the compromised hosts connected to the SDN switches. In this paper, we introduce a time- and space-efficient solution for the identification of these compromised hosts. Our solution consumes less computational resources and space and does not require any special equipment.
Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). First posted on arXiv 27 Dec 2019.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 7; 2022: 6; 2023: 0; 2024: 0; 2025: 1.
14 papers.
Sort:
- 2021Spike2Vec: An Efficient and Scalable Embedding Approach for COVID-19 Spike Sequencescited by 30
- 2021A k-mer Based Approach for SARS-CoV-2 Variant Identificationcited by 23
- 2022PWM2Vec: An Efficient Embedding Approach for Viral Host Specification from Coronavirus Spike Sequencescited by 22
- 2022Efficient Approximate Kernel Based Spike Sequence Classificationcited by 18
- 2021Effective and scalable clustering of SARS-CoV-2 sequencescited by 15
- 2021Robust Representation and Efficient Feature Selection Allows for Effective Clustering of SARS-CoV-2 Variantscited by 14
- 2022Reads2Vec: Efficient Embedding of Raw High-Throughput Sequencing Reads Datacited by 7
- 2021Computing Graph Descriptors on Edge Streamscited by 4
- 2022Evaluating COVID-19 Sequence Data Using Nearest-Neighbors Based Network Modelcited by 3
- 2025A Survey on Cloud-Edge-Terminal Collaborative Intelligence in AIoT Networkscited by 3
- 2021Characterizing SARS-CoV-2 Spike Sequences Based on Geographical Locationcited by 2
- 2021Locally Weighted Mean Phase Angle (LWMPA) Based Tone Mapping Quality Index (TMQI-3)cited by 1
- 2025A Survey on Cloud-Edge-Terminal Collaborative Intelligence in AIoT Networks26 Aug 2025
- 2022Evaluating COVID-19 Sequence Data Using Nearest-Neighbors Based Network Model19 Nov 2022
- 2022Reads2Vec: Efficient Embedding of Raw High-Throughput Sequencing Reads Data15 Nov 2022
- 2022Learning Failure-Inducing Models for Testing Software-Defined Networks27 Oct 2022
- 2022Efficient Approximate Kernel Based Spike Sequence Classification11 Sep 2022
- 2022Information We Can Extract About a User From 'One Minute Mobile Application Usage'27 Jul 2022
- 2022PWM2Vec: An Efficient Embedding Approach for Viral Host Specification from Coronavirus Spike Sequences6 Jan 2022
- 2021Robust Representation and Efficient Feature Selection Allows for Effective Clustering of SARS-CoV-2 Variants18 Oct 2021
- 2021Characterizing SARS-CoV-2 Spike Sequences Based on Geographical Location2 Oct 2021
- 2021Locally Weighted Mean Phase Angle (LWMPA) Based Tone Mapping Quality Index (TMQI-3)17 Sep 2021
- 2021Spike2Vec: An Efficient and Scalable Embedding Approach for COVID-19 Spike Sequences12 Sep 2021
- 2021Computing Graph Descriptors on Edge Streams2 Sep 2021
2 more
- 2021Spike2Vec: An Efficient and Scalable Embedding Approach for COVID-19 Spike Sequencescited by 30
- 2021A k-mer Based Approach for SARS-CoV-2 Variant Identificationcited by 23
- 2022PWM2Vec: An Efficient Embedding Approach for Viral Host Specification from Coronavirus Spike Sequencescited by 22
- 2022Efficient Approximate Kernel Based Spike Sequence Classificationcited by 18
- 2021Effective and scalable clustering of SARS-CoV-2 sequencescited by 15
- 2021Robust Representation and Efficient Feature Selection Allows for Effective Clustering of SARS-CoV-2 Variantscited by 14
- 2022Reads2Vec: Efficient Embedding of Raw High-Throughput Sequencing Reads Datacited by 7
- 2021Computing Graph Descriptors on Edge Streamscited by 4
- 2022Evaluating COVID-19 Sequence Data Using Nearest-Neighbors Based Network Modelcited by 3
- 2025A Survey on Cloud-Edge-Terminal Collaborative Intelligence in AIoT Networkscited by 3
- 2021Characterizing SARS-CoV-2 Spike Sequences Based on Geographical Locationcited by 2
- 2021Locally Weighted Mean Phase Angle (LWMPA) Based Tone Mapping Quality Index (TMQI-3)cited by 1
12 most cited of 14 All 14 (JSON)
- 2025A Survey on Cloud-Edge-Terminal Collaborative Intelligence in AIoT Networks26 Aug 2025
- 2022Evaluating COVID-19 Sequence Data Using Nearest-Neighbors Based Network Model19 Nov 2022
- 2022Reads2Vec: Efficient Embedding of Raw High-Throughput Sequencing Reads Data15 Nov 2022
- 2022Learning Failure-Inducing Models for Testing Software-Defined Networks27 Oct 2022
- 2022Efficient Approximate Kernel Based Spike Sequence Classification11 Sep 2022
- 2022Information We Can Extract About a User From 'One Minute Mobile Application Usage'27 Jul 2022
- 2022PWM2Vec: An Efficient Embedding Approach for Viral Host Specification from Coronavirus Spike Sequences6 Jan 2022
- 2021Robust Representation and Efficient Feature Selection Allows for Effective Clustering of SARS-CoV-2 Variants18 Oct 2021
- 2021Characterizing SARS-CoV-2 Spike Sequences Based on Geographical Location2 Oct 2021
- 2021Locally Weighted Mean Phase Angle (LWMPA) Based Tone Mapping Quality Index (TMQI-3)17 Sep 2021
- 2021Spike2Vec: An Efficient and Scalable Embedding Approach for COVID-19 Spike Sequences12 Sep 2021
- 2021Computing Graph Descriptors on Edge Streams2 Sep 2021
12 newest of 14 All 14 (JSON)