Enhanced secure communication over inter-domain routing in heterogeneous wireless networks based on analysis of BGP anomalies using soft computing techniques

Elamathi, N.; Jayashri, S.; Pitchai, R.

doi:10.1007/s00500-019-03836-4

Cited by 4 publications

(2 citation statements)

References 21 publications

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“…In 2020, Pradeepa & Pushpalatha et al [1] have developed an intelligent model in software-defined networks for DPPBGP. In software-defined networks, researchers created an intelligent model for DPPBGP.…”

Section: A Related Workmentioning

confidence: 99%

Parametric and Non-parametric Analysis on RHMFO based Optimal Detection of BorderGateway Protocol Anomalies

Mala

Chairperson

2022

Preprint

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For secure and effective Internet access, the Border Gateway Protocol (BGP) must be able to recognize and stop strange coincidences in real time. Regardless, over the past ten years, more study has focused on spotting BGP abnormalities; because of the rise of new bizarre behaviour from both hackers and network configuration errors, it continues to be more challenging. This work goes with the parametric and non parametric analysis of RHMFO based Optimal Detection of BGP Anomalieswith two major steps (i) Feature Extraction (ii) Anomaly Detection". Initially, extensive features such "statistical features, higher order statistical features, and correntropy features" are extracted during the feature extraction stage. For the detection process, an optimized DBN is proposed to define the presence of attack. Here, a hybrid optimization model known as RHMFO is introduced to fine-tune the weight of DBN in order to enhance the detection accuracy. The traditional Rider Optimization Method (ROA) and the MFO algorithm are conceptually combined to create the suggested RHMFO paradigm. Finally, in this paper, parametric and non-parametric analysis is performed. By varying the parameters of RHMFO, the performance of the suggested work is evaluated.

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Section: A Related Workmentioning

confidence: 99%

Parametric and Non-parametric Analysis on RHMFO based Optimal Detection of BorderGateway Protocol Anomalies

Mala

Chairperson

2022

Preprint

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“…In this case, the malicious AS falsifies the NLRI information in the BGP UPDATE message and advertises an illegal prefix [41]. As shown in Fig.…”

Section: ) Forging Nlri Informationmentioning

confidence: 99%

A Prefix Hijacking Detection Model Based on the Immune Network Theory

Zhang

Zhao

2019

IEEE Access

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The prefix hijacking problem is an urgent security issue that need to address in the Border Gateway Protocol (BGP) security research. In order to solve the problem of prefix hijacking in BGP, we propose (a) new (p)refix (h)ijacking (d)etection model based on the immune network theory in this paper, called aPHD. To be specific, aPHD uses real BGP UPDATE messages for pre-training and has the ability to detect UPDATE messages in real time after pre-training. The aPHD (1) can effectively detect prefix hijacking attacks with high accuracy; (2)is easy to deployment; and (3) has a low false positive rate and low overhead. Extensive performance evaluation shows that our solution is secure and feasible. The aPHD improved the accuracy rate by 6.2% and reduced the false positive rate by 85.7%. INDEX TERMS Immune network theory, prefix hijacking, BGP security, negative selection.

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Optimal detection of border gateway protocol anomalies with extensive feature set

Sunita,

Mallapur

2023

Multimed Tools Appl

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Enhanced secure communication over inter-domain routing in heterogeneous wireless networks based on analysis of BGP anomalies using soft computing techniques

Cited by 4 publications

References 21 publications

Parametric and Non-parametric Analysis on RHMFO based Optimal Detection of BorderGateway Protocol Anomalies

Parametric and Non-parametric Analysis on RHMFO based Optimal Detection of BorderGateway Protocol Anomalies

A Prefix Hijacking Detection Model Based on the Immune Network Theory

Optimal detection of border gateway protocol anomalies with extensive feature set

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