CyberPulse++: A machine learning‐based security framework for detecting link flooding attacks in software defined networks

Rasool, Raihan Ur; Ahmed, Khandakar; Anwar, Zahid; Wang, Hua; Ashraf, Usman; Rafique, Wajid

doi:10.1002/int.22442

Cited by 13 publications

(4 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The packet metadata describes the content length and type, enabling network service providers to optimize network behaviours accordingly. OpenFlow channel and its north and southbound interfaces are prone to attacks [61]. In this case, ICN can protect the content itself, securing the overall network.…”

Section: Software-defined Information-centric Networking For Iotmentioning

confidence: 99%

Complementing IoT Services Using Software-Defined Information Centric Networks: A Comprehensive Survey

Rafique

Hafid

Cherkaoui

2022

IEEE Internet Things J.

Self Cite

View full text Add to dashboard Cite

IoT connects a large number of physical objects with the Internet that capture and exchange real-time information for service provisioning. Traditional network management schemes face challenges to manage vast amounts of network traffic generated by IoT services. Software-Defined Networking (SDN) and Information-Centric Networking (ICN) are two complementary technologies that could be integrated to solve the challenges of different aspects of IoT service provisioning. ICN offers a clean-slate design to accommodate continuously increasing network traffic by considering content as a network primitive. It provides a novel solution for information propagation and delivery for large-scale IoT services. On the other hand, SDN allocates overall network management responsibilities to the central controller, where network elements act merely as traffic forwarding components. An SDN-enabled network flexibly supports ICN without deploying ICN-capable hardware. Therefore, the integration of SDN and ICN provides benefits for large-scale IoT services. This paper provides a comprehensive survey on Software-Defined Information-Centric Internet of Things (SDIC-IoT) for IoT services provisioning. We present critical enabling technologies of SDIC-IoT, discuss its architecture, and elaborate its benefits for IoT services provisioning. We elaborate on key IoT service provisioning requirements and discuss how SDIC-IoT supports different aspects of IoT services. We develop different taxonomies of SDIC-IoT literature based on various performance parameters. Furthermore, an extensive discussion on different use cases, synergies, and advances is presented to envision the SDIC-IoT concept. Finally, we provide current challenges, causes, and future research directions of IoT services provisioning using SDIC-IoT.

show abstract

Section: Software-defined Information-centric Networking For Iotmentioning

confidence: 99%

Complementing IoT Services Using Software-Defined Information Centric Networks: A Comprehensive Survey

Rafique

Hafid

Cherkaoui

2022

IEEE Internet Things J.

Self Cite

View full text Add to dashboard Cite

show abstract

“…At the same time, in the field of network security, the technology and means of network attackers are constantly being updated, and the traditional Network Security Defense (NSD) method also appears inadequate. Deep Reinforcement Learning (DRL), as an important technology in the field of AI, has the ability to autonomously learn and make decisions in complex environments, providing new possibilities for solving game enemy design and NSD [4][5]. By introducing DRL into the field of game enemy design and NSD, we can achieve intelligent behavior generation of game enemies and adaptive defense strategies against unknown attacks, thereby improving the gaming experience and network security level.…”

Section: Introductionmentioning

confidence: 99%

Collaborative Optimization of Game Enemy Design and Network Security Defense Based on Deep Reinforcement Learning

Liu

2024

TCSISR

View full text Add to dashboard Cite

The purpose of this paper is to explore the cooperative optimization strategy of game enemy design based on Deep Reinforcement Learning (DRL) and Network Security Defense (NSD). By analyzing the correlation between game enemy design and NSD, this paper puts forward a method of integrating DRL technology to improve the game experience and protect the security of the game system. Firstly, the paper introduces the basic concepts and existing research progress of game enemy design and NSD. Then, the paper introduces the design method of game enemies based on DRL in detail, including the training and behavior generation of enemy agents. Then, the paper discusses the application of DRL in NSD, including network traffic analysis and monitoring and intelligent defense strategy generation. Through experimental design and result analysis, the paper verifies the effectiveness and performance of collaborative optimization strategy, and shows its potential in improving game experience and protecting network security. Finally, the paper summarizes the research results and discusses the future research direction and development trend. This paper provides important reference and guidance for deeply understanding and applying DRL technology to game enemy design and NSD.

show abstract

“…An indirect DDoS 23 attack which is novel due to its design for cutting off internet connection for the entire region (cities, or even countries) after instantaneous selection for set of targeted links is Crossfire DDoS attack 24,25 . It mainly consists of:Link Map Construction; Target Links Selection; Botnet Coordination; …”

Section: Introductionmentioning

confidence: 99%

Countering crossfire DDoS attacks through moving target defense in SDN networks using OpenFlow traffic modification

Hyder,

Fatima,

Khan

et al. 2023

Trans Emerging Tel Tech

View full text Add to dashboard Cite

Software‐Defined Networking (SDN) is an evolving networking technique due to its flexibility and programmability. OpenFlow is the primary protocol behind SDN. Moving Target Defense (MTD) is an emerging security technique to counter attacks by dynamically changing the attack surface. SDN‐based MTD security solutions are gaining popularity due to the centralized control and monitoring capabilities of the SDN control plane. Crossfire is a type of indirect Distributed Denial of Service (DDoS) attack intending to impact the neighbors of the actual target. Crossfire DDoS attacks are gaining momentum in recent times. In this paper, a mechanism for the protection of crossfire DDoS attacks is proposed by exploiting OpenFlow‐based traffic modifications. We employed the Moving Target Defense scheme to redirect the traffic from the actual host to the shadow host to counter the crossfire DDoS attack and from the default domain name system port to another predefined port. Traffic redirection helps in diverting the attacker to shadow host and thus getting the incorrect network path and subsequently crossfire attack was unable to be executed properly. The proposed scheme utilized the ONOS cluster with Mininet. The results showed successful traffic redirection for countering the Crossfire DDoS attacks at a low computational cost.

show abstract

CyberPulse++: A machine learning‐based security framework for detecting link flooding attacks in software defined networks

Cited by 13 publications

References 43 publications

Complementing IoT Services Using Software-Defined Information Centric Networks: A Comprehensive Survey

Complementing IoT Services Using Software-Defined Information Centric Networks: A Comprehensive Survey

Collaborative Optimization of Game Enemy Design and Network Security Defense Based on Deep Reinforcement Learning

Countering crossfire DDoS attacks through moving target defense in SDN networks using OpenFlow traffic modification

Contact Info

Product

Resources

About