Defense against flooding attacks using probabilistic thresholds in the internet of things ecosystem

Zarei, Seyed Meysam; Fotohi, Reza

doi:10.1002/spy2.152

Cited by 8 publications

(3 citation statements)

References 36 publications

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“…The authors compared different ML approaches to detect malicious activity and the proposed Hybrid KSVM algorithm for DDoS attack. Their Hybrid KSVM algorithms gave better results with accuracy (92.46%) and precision (95.31%) compared to other ML algorithms [13].…”

Section: Flood Attacks In Vanetmentioning

confidence: 93%

FA-AODV: Flooding Attacks Detection Based Ad Hoc On-Demand Distance Vector Routing Protocol for VANET

Tosunoglu

Koçak

2022

Sakarya University Journal of Computer and Information Sciences

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Vehicular Ad-Hoc Networks (VANET) is anticipated to be the most effective way of increasing performance and safety in transportation in the near future. VANETs are the sub-branch of Ad-Hoc Networks which provide safety and comfort features together with related services for the vehicle operators. RREQ flood attack mostly encountered in the literature for security of VANET. Due to the nature of the reactive protocols, the AODV routing protocol is quite open to attack types such as flood attack. Flood attacks occur in the network layer. The impact of flood attacks is not about victim nodes, it can be also affect the whole network. A malicious attack that could be carried out in VANET could cause accidents that would cause a serious disaster. A malicious node could penetrate into the IP addresses on a Flood Attack based User Datagram Protocol (UDP) to breakdown the data communication between two vehicles. The main purpose of this paper is to detect and prevent the flood attack, during the operation of the routing protocol and to decrease the end-to-end delay on the network.

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Section: Flood Attacks In Vanetmentioning

confidence: 93%

FA-AODV: Flooding Attacks Detection Based Ad Hoc On-Demand Distance Vector Routing Protocol for VANET

Tosunoglu

Koçak

2022

Sakarya University Journal of Computer and Information Sciences

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“…Based on the SDx paradigm, Zarei and Fotohi [21] presented a comprehensive framework for the internet of things software-defined (SD-IoT). In addition to the SD-IoT controller package, the frame contained SD-IoT switches coupled to an IoT gateway and IoT devices connected via an IoT gateway.…”

Section: Literature Surveymentioning

confidence: 99%

A Novel, Efficient, and Secure Anomaly Detection Technique Using DWU‐ODBN for IoT‐Enabled Multimedia Communication Systems

Sathya¹,

Jeyaselvi

Krishnasamy³

et al. 2021

Wireless Communications and Mobile Computing

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The Internet of Things (IoT) is enhancing our lives in a variety of structures, which consists of smarter cities, agribusiness, and e-healthcare, among others. Even though the Internet of Things has many features with the consumer Internet of Things, the open nature of smart devices and their worldwide connection make IoT networks vulnerable to a variety of assaults. Several approaches focused on attack detection in Internet of Things devices, which has the longest calculation times and the lowest accuracy issues. It is proposed in this paper that an attack detection framework for Internet of Things devices, based on the DWU-ODBN method, be developed to alleviate the existing problems. At the end of the process, the proposed method is used to identify the source of the assault. It comprises steps such as preprocessing, feature extraction, feature selection, and classification to identify the source of the attack. A random oversampler is used to preprocess the input data by dealing with NaN values, categorical features, missing values, and unbalanced datasets before being used to deal with the imbalanced dataset. When the data has been preprocessed, it is then sent to the MAD Median-KS test method, which is used to extract features from the dataset. To categorize the data into attack and nonattack categories, the features are classified using the dual weight updation-based optimal deep belief network (DWU-ODBN) classification technique, which is explained in more detail below. According to the results of the experimental assessment, the proposed approach outperforms existing methods in terms of detecting intrusions and assaults. The proposed work achieves 77 seconds to achieve the attack detection with an accuracy rate of 98.1%.

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“…Considering the structure of MANETs, packet transmission from source to destination in these networks is done in a step by step fashion and some packets might be destroyed along the route. [27][28][29][30] The packet delivery ratio in MANETs is very important. The packet delivery ratio in this type of network is calculated using Equation (6).…”

Section: Performance Metricsmentioning

confidence: 99%

A reliable and secure method for network‐layer attack discovery and elimination in mobile ad‐hoc networks based on a probabilistic threshold

Ebazadeh

Fotohi

2021

Security and Privacy

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The wireless nature of mobile networks makes it vulnerable to all kinds of attacks. Therefore, designing a secure method for detecting intrusive nodes in this type of network seems necessary. Among the types of attacks on mobile ad-hoc networks, the Grayhole attack is one of the most dangerous attacks. In this type of attack, a malicious node absorbs network traffic and then selectively deletes a number of received packets. In this paper, a method called RSA-GRAY HOLE is used to detect and isolate the Grayhole attack. The proposed method not only detects the malicious node, but also disconnects it from the network and does not allow it to participate in the next routing process. The proposed method detects a malicious node in two steps; in the first step, it examines the validity of the nodes of a route to select a valid route. In the second step, the destination node detects the presence of malicious nodes in the route and after detecting the malicious nodes, disconnects them from the network. To demonstrate the efficiency of the proposed RSA-GRAY HOLE method, the NS-2 simulator was used and this method was compared with the DSR protocol under Grayhole attack. The simulation results show the superior performance of the proposed RSA-GRAY HOLE method compared to the Grayhole DSR method in terms of throughput (23%), package delivery rate (26%), average delay (19%) and number of lost packets (20%).

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Defense against flooding attacks using probabilistic thresholds in the internet of things ecosystem

Cited by 8 publications

References 36 publications

FA-AODV: Flooding Attacks Detection Based Ad Hoc On-Demand Distance Vector Routing Protocol for VANET

FA-AODV: Flooding Attacks Detection Based Ad Hoc On-Demand Distance Vector Routing Protocol for VANET

A Novel, Efficient, and Secure Anomaly Detection Technique Using DWU‐ODBN for IoT‐Enabled Multimedia Communication Systems

A reliable and secure method for network‐layer attack discovery and elimination in mobile ad‐hoc networks based on a probabilistic threshold

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