FlowJustifier

Sarwar, Muhammad Arslan; Hussain, Majid; Anwar, Muhammad U.; Ahmad, Mudassar

doi:10.1145/3341325.3342037

Cited by 10 publications

(5 citation statements)

References 14 publications

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“…However, multi-level authentication also has an impact on network performance. Sarwar et al [70] proposed a traffic forwarding method based on user trust. This method establishes user trust and directs traffic in the queue according to the level of user trust, while discarding unauthorized user traffic.…”

Section: Policy-based Ddos Attack Mitigation Techniquesmentioning

confidence: 99%

A Comprehensive Survey of Distributed Denial of Service Detection and Mitigation Technologies in Software-Defined Network

Su,

Xiong,

Qian

et al. 2024

Electronics

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The widespread adoption of software-defined networking (SDN) technology has brought revolutionary changes to network control and management. Compared to traditional networks, SDN enhances security by separating the control plane from the data plane and replacing the traditional network architecture with a more flexible one. However, due to its inherent architectural flaws, SDN still faces new security threats. This paper expounds on the architecture and security of SDN, analyzes the vulnerabilities of SDN architecture, and introduces common distributed denial of service (DDoS) attacks within the SDN architecture. This article also provides a review of the relevant literature on DDoS attack detection and mitigation in the current SDN environment based on the technologies used, including statistical analysis, machine learning, policy-based, and moving target defense techniques. The advantages and disadvantages of these technologies, in terms of deployment difficulty, accuracy, and other factors, are analyzed. Finally, this study summarizes the SDN experimental environment and DDoS attack traffic generators and datasets of the reviewed literature and the limitations of current defense methods and suggests potential future research directions.

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Section: Policy-based Ddos Attack Mitigation Techniquesmentioning

confidence: 99%

A Comprehensive Survey of Distributed Denial of Service Detection and Mitigation Technologies in Software-Defined Network

Su,

Xiong,

Qian

et al. 2024

Electronics

View full text Add to dashboard Cite

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“…Sarwar et al [71] present FlowJustifier, a request prioritization algorithm based on a trust return value list, which seeks to mitigate the DDoS attacks that target the SDN-based IoT infrastructure control plane. The list employs confidence values to classify users according to their level of confidentiality, which is established based on the records of each user's network activities.…”

Section: Request Prioritizationmentioning

confidence: 99%

“…Bull et al [72] Xu et al [55] Salva-Garcia et al [40] & Molina Zarca et al [57] Rafique et al [61] Bawany and Shamsi [31] Yang et al [60] Rafique et al [74] Nair et al [65] Galeano-Brajones et al [68] Ravi and Shalinie [64] Rate limiting Sharma et al [69] Traceback Chen et al [45] Request prioritization Sarwar et al [71] Flow filtering MTD Sahay et al [73] Honeypots MTD Luo et al [75] Hybrid SDN-Fog…”

Section: Flow Filteringmentioning

confidence: 99%

“…Xu et al [55] Krishnan et al [63] Rafique et al [61] Sarwar et al [71] Rafique et al [74] Smart Homes Bhunia and Gurusamy [25] Sharma et al [69] IoT Data Centers Bawany and Shamsi [31] Industrial IoT Yan et al [42] Ship communication systems Sahay et al [73] Generic Bull et al [72] Özçelik et al [56] Yin et al [54] Krishnan et al [70] Salva-Garcia et al [40] & Molina Zarca et al [57] Nguyen et al [58] Rathore et al [59] Yang et al [60] Houda et al [66] Luo et al [75] Chen et al [45] Nair et al [65] Galeano-Brajones et al [68] Ravi and Shalinie [64] The techniques that rely on the analysis of network flow statistics to detect anomalous actions are efficient in containing volumetric attacks, which are based on high traffic rates [80]. Concerning this, there are solutions based on the following strategies: rate limiting, cosine similarity, traceback, and flow prioritization, as outlined in Table 5.…”

Section: Sdn Control Planementioning

confidence: 99%

“…The SDN control plane can itself become the target of DDoS attacks that are aimed at exploiting vulnerabilities in its components and make the underlying IoT applications unavailable. In this scenario, the studies carried out in [55,61,63,71,74] put forward mechanisms that are capable of mitigating DDoS attacks that target both the data plane and the SDN control plane.…”

Section: Sdn Control Planementioning

confidence: 99%

See 2 more Smart Citations

A Taxonomy of DDoS Attack Mitigation Approaches Featured by SDN Technologies in IoT Scenarios

Silva

Neto

et al. 2020

Sensors

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The Internet of Things (IoT) has attracted much attention from the Information and Communication Technology (ICT) community in recent years. One of the main reasons for this is the availability of techniques provided by this paradigm, such as environmental monitoring employing user data and everyday objects. The facilities provided by the IoT infrastructure allow the development of a wide range of new business models and applications (e.g., smart homes, smart cities, or e-health). However, there are still concerns over the security measures which need to be addressed to ensure a suitable deployment. Distributed Denial of Service (DDoS) attacks are among the most severe virtual threats at present and occur prominently in this scenario, which can be mainly owed to their ease of execution. In light of this, several research studies have been conducted to find new strategies as well as improve existing techniques and solutions. The use of emerging technologies such as those based on the Software-Defined Networking (SDN) paradigm has proved to be a promising alternative as a means of mitigating DDoS attacks. However, the high granularity that characterizes the IoT scenarios and the wide range of techniques explored during the DDoS attacks make the task of finding and implementing new solutions quite challenging. This problem is exacerbated by the lack of benchmarks that can assist developers when designing new solutions for mitigating DDoS attacks for increasingly complex IoT scenarios. To fill this knowledge gap, in this study we carry out an in-depth investigation of the state-of-the-art and create a taxonomy that describes and characterizes existing solutions and highlights their main limitations. Our taxonomy provides a comprehensive view of the reasons for the deployment of the solutions, and the scenario in which they operate. The results of this study demonstrate the main benefits and drawbacks of each solution set when applied to specific scenarios by examining current trends and future perspectives, for example, the adoption of emerging technologies based on Cloud and Edge (or Fog) Computing.

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RETRACTED ARTICLE: Enhancement of security using optimized DoS (denial-of-service) detection algorithm for wireless sensor network

Suryaprabha

Kumar

2019

Soft Comput

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FlowJustifier

Cited by 10 publications

References 14 publications

A Comprehensive Survey of Distributed Denial of Service Detection and Mitigation Technologies in Software-Defined Network

A Comprehensive Survey of Distributed Denial of Service Detection and Mitigation Technologies in Software-Defined Network

A Taxonomy of DDoS Attack Mitigation Approaches Featured by SDN Technologies in IoT Scenarios

RETRACTED ARTICLE: Enhancement of security using optimized DoS (denial-of-service) detection algorithm for wireless sensor network

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