Sybil Attack in RPL-Based Internet of Things: Analysis and Defenses

Pu, Cong

doi:10.1109/jiot.2020.2971463

“…Though GRU based deep learning model shows higher performance, it can detect only one attack. Pu [30] designed a Gini Index-based countermeasure (GINI) to protect the RPL based networks from Sybil attack. The performance of proposed GINI countermeasure is compared with two existing algorithms like two-step detection and SecRPL.…”

Section: Ids In Rpl Based Iotmentioning

confidence: 99%

A Novel Intrusion Detection System for RPL Based IoT Networks with Bio-Inspired Feature Selection and Ensemble Classifier

Prakash

¹

,

B

²

2021

Preprint

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Internet of Things (IoT) is the powerful latest trend that allows communications and networking of many sources over the internet. Routing protocol for low power and lossy networks (RPL) based IoT networks may be exposed to many routing attacks due to resource-constrained and open nature of the IoT nodes. Hence, there is a need for network intrusion detection system (NIDS) to protect RPL based IoT networks from routing attacks. The existing techniques for anomaly-based NIDS (ANIDS) subjects to high false alarm rate (FAR). Therefore, a novel bio-inspired voting ensemble classifier with feature selection technique is proposed in this paper to improve the performance of ANIDS for RPL based IoT networks. The proposed voting ensemble classifier combines the results of various base classifiers such as logistic Regression, support vector machine, decision tree, bidirectional long short-term memory and K-nearest neighbor to detect the attacks accurately based on majority voting rule. The optimized weights of base classifiers are obtained by using the feature selection method called simulated annealing based improved salp swarm algorithm (SA-ISSA), which is the hybridization of particle swarm optimization, opposition based learning and salp swarm algorithm. The experiments are performed with RPL-NIDDS17 dataset that contains seven types of attack instances. The performance of the proposed model is evaluated and compared with existing feature selection and classification techniques in terms of accuracy, attack detection rate (ADR), FAR and so on. The proposed ensemble classifier shows better performance with higher accuracy (96.4%), ADR (97.7%) and reduced FAR (3.6%).

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“…Over the last decade, the number of devices connected to the Internet has been rapidly increasing due to the proliferation of emerging technologies such as Internet of ings, artificial intelligence, and blockchain [1]. According to Cisco Annual Internet Report [2], there will be 29.3 billion networked devices by 2023.…”

Section: Introductionmentioning

confidence: 99%

${Pro}^{NDN}$ : MCDM-Based Interest Forwarding and Cooperative Data Caching for Named Data Networking

Pu

¹

2021

Journal of Computer Networks and Communications

Self Cite

4

0

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Named data networking (NDN), as a specific architecture design of information-centric networking (ICN), has quickly became a promising candidate for future Internet architecture, where communications are driven by data names instead of IP addresses. To realize the NDN communication paradigm in the future Internet, two important features, stateful forwarding and in-network caching, have been proposed to cope with drawbacks of host-based communication protocols. The stateful forwarding is designed to maintain the state of pending Interest packets to guide Data packets back to requesting consumers, while the in-network caching is used to reduce both network traffic and data access delay to improve the overall performance of data access. However, the conventional stateful forwarding approach is not adaptive and responsive to diverse network conditions because it fails to consider multiple network metrics to make Interest forwarding decision. In addition, the default in-network caching strategy relies on storing each received Data packet regardless of various caching constraints and criteria, which causes the routers in the vicinity of data producers to suffer from excessive caching overhead. In this paper, we propose the Pro NDN , a novel stateful forwarding and in-network caching strategy for NDN networks. The Pro NDN consists of multicriteria decision-making (MCDM) based interest forwarding and cooperative data caching. The basic idea of the MCDM-based interest forwarding is to employ Technique for Order Performance by Similarity to Idea Solution (TOPSIS) to dynamically evaluate outgoing interface alternatives based on multiple network metrics and objectively select an optimal outgoing interface to forward the Interest packet. In addition, the cooperative data caching consists of two schemes: CacheData, which caches the data, and CacheFace, which caches the outgoing interface. We conduct extensive simulation experiments for performance evaluation and comparison with prior schemes. The simulation results show that the Pro NDN can improve Interest satisfaction ratio and Interest satisfaction latency as well as reduce hop count and Content Store utilization ratio.

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“…In this study, IoT attacks has been carried out by exploiting the vulnerabilities of IoT devices. Subsequently, the network forensic packages of Flood Attack, which is one of the most important one on RPL-based attacks [6,7,8], has been analyzed by examining the effects of attacks on the system. WSNs have emerged as an important application of the paradigm of Ad-Hoc Networks such as physical environment monitoring.…”

Section: Introductionmentioning

confidence: 99%

RPL Tabanlı Atakların Ağ Adli Bilişimi

Karacayılmaz

¹

,

Gönen

²

,

Artuner

³

et al. 2020

Düzce Üniversitesi Bilim Ve Teknoloji Dergisi

0

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IoT devices, which are increasing in highly manner day by day, are now in everywhere in our life. WSNs are used together with IoT devices to monitor real environments. In this study, attacks against WSNs were carried out. The attack chosen for this study is a flood attack. In addition, solution suggestions for this attack are presented. In this context, firstly reference and attack packages have been collected, and then the collected packages have been compared with the reference packages and forensic investigations have been carried out. The result of the evaluation has shown the importance continuous monitoring on 24/7 basis and detecting abnormal behaviors in IoT traffic with forensics analysis for preventing attacks.

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Sybil Attack in RPL-Based Internet of Things: Analysis and Defenses

Cited by 82 publications

References 37 publications

A Novel Intrusion Detection System for RPL Based IoT Networks with Bio-Inspired Feature Selection and Ensemble Classifier

A Novel Intrusion Detection System for RPL Based IoT Networks with Bio-Inspired Feature Selection and Ensemble Classifier

${Pro}^{NDN}$ : MCDM-Based Interest Forwarding and Cooperative Data Caching for Named Data Networking

RPL Tabanlı Atakların Ağ Adli Bilişimi

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Sybil Attack in RPL-Based Internet of Things: Analysis and Defenses

Cited by 82 publications

References 37 publications

A Novel Intrusion Detection System for RPL Based IoT Networks with Bio-Inspired Feature Selection and Ensemble Classifier

A Novel Intrusion Detection System for RPL Based IoT Networks with Bio-Inspired Feature Selection and Ensemble Classifier

Pro NDN : MCDM-Based Interest Forwarding and Cooperative Data Caching for Named Data Networking

RPL Tabanlı Atakların Ağ Adli Bilişimi

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${Pro}^{NDN}$ : MCDM-Based Interest Forwarding and Cooperative Data Caching for Named Data Networking