Hybrid IDS using SVM classifier for detecting DoS attack in MANET application

Justin, Vijin; Marathe, Nilesh; Dongre, Nilima

doi:10.1109/i-smac.2017.8058284

Cited by 11 publications

(7 citation statements)

References 3 publications

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“…In the last few years, data-driven methods have been employed to detect cyber attacks [18][19][20][21][22][23]25,41]. These methods have presented good performance to find models of processes that even present quite pronounced non-linear dynamics.…”

Section: Related Workmentioning

confidence: 99%

“…In Reference [18], an SVM-based algorithm was used to classify normal and abnormal behavior of data traffic that may be subjected to DoS attacks. This algorithm reaches good attacks predictions rate with less training time.…”

Section: Related Workmentioning

confidence: 99%

“…Within these can be highlighted: [17] the methods based on traditional information technologies, where network traffic analysis is used to detect anomalies [18][19][20][21][22][23][24][25][26]; and modelbased methods, where detection is performed by comparing the system actual output with an expected value [4,[27][28][29][30][31].…”

Section: Introductionmentioning

confidence: 99%

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Detection and Isolation of DoS and Integrity Cyber Attacks in Cyber-Physical Systems with a Neural Network-Based Architecture

et al. 2021

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New applications of industrial automation request great flexibility in the systems, supported by the increase in the interconnection between its components, allowing access to all the information of the system and its reconfiguration based on the changes that occur during its operations, with the purpose of reaching optimum points of operation. These aspects promote the Smart Factory paradigm, integrating physical and digital systems to create smarts products and processes capable of transforming conventional value chains, forming the Cyber-Physical Systems (CPSs). This flexibility opens a large gap that affects the security of control systems since the new communication links can be used by people to generate attacks that produce risk in these applications. This is a recent problem in the control systems, which originally were centralized and later were implemented as interconnected systems through isolated networks. To protect these systems, strategies that have presented acceptable results in other environments, such as office environments, have been chosen. However, the characteristics of these applications are not the same, and the results achieved are not as expected. This problem has motivated several efforts in order to contribute from different approaches to increase the security of control systems. Based on the above, this work proposes an architecture based on artificial neural networks for detection and isolation of cyber attacks Denial of Service (DoS) and integrity in CPS. Simulation results of two test benches, the Secure Water Treatment (SWaT) dataset, and a tanks system, show the effectiveness of the proposal. Regarding the SWaT dataset, the scores obtained from the recall and F1 score metrics was 0.95 and was higher than other reported works, while, in terms of precision and accuracy, it obtained a score of 0.95 which is close to other proposed methods. With respect to the interconnected tank system, scores of 0.96,0.83,0.81, and 0.83 were obtained for the accuracy, precision, F1 score, and recall metrics, respectively. The high true negatives rate in both cases is noteworthy. In general terms, the proposal has a high effectiveness in detecting and locating the proposed attacks.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Detection and Isolation of DoS and Integrity Cyber Attacks in Cyber-Physical Systems with a Neural Network-Based Architecture

et al. 2021

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“…It also provides some benefits in the area of MANETs to cater to security against various attacks. Like, Justin et al (3) proposed an SVM-based Hybrid Intrusion Detection System to detect DoS attacks in MANETs. This proposed approach reduces the training time and includes signature and anomaly-based methods to detect malicious nodes.…”

Section: Related Workmentioning

confidence: 99%

MOpt Shield: An Intrusion Detection System based on Meld Optimization Algorithm to mitigate Amalgam Attacks

Kaur¹,

nbsp²,

nbsp³

et al. 2021

IJST

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Background/Objectives: To mitigate network from amalgam attacks, this study is focussed on designing an efficient approach that can prevent the networks from intruders and secure the communication. Methods: A crossbreed approach, named 'MOpt Shield,' is proposed in this study. This proposed protocol utilizes the efficacy of the existing Cuckoo Search and Firefly Optimization Algorithm on basic AODV protocol along with the promising factors of the Intrusion Detection System. The proposed protocol is simulated using an NS-2 simulator with two different simulation scenarios, and PDR, Throughput, PLR, and Delay parameters are considered performance measures for the same. Findings: The proposed protocol finds the best selected nodes for communication and prepare separate list for the doubted nodes which further analyzed for attacker or non-attacker nodes. This will help to identify the best path with high energy and other capabilities for the efficient transmission of data. The performance of this proposed protocol is analyzed under 5 attacker nodes in which 2 are blackhole and 3 are DoS attacker nodes. For simulation, the scenario includes minimum 5 connections and maximum 25 connections between the 50 nodes with CBR traffic and 20m/s speed. The evaluated results show the astounding performance of the proposed protocol over the other existed protocols in terms of PDR, Throughput and Delay, and hence it reveals its capabilities. Novelty/Applications: The proposed protocol effectively handles the amalgam attacks and its novelty lie in its features of hybrid optimization and intrusion detection approach to find the route of transmission and the trusty nodes.

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“…• Support Vector Machines (SVM): SVM is a supervised learning ML method used for classification of data and is used to detect DDoS attacks with associated learning algorithms [22]. SVM has been extensively used to detect invasions as a classical pattern recognition tool where the principle of DoS attack generally utilizes the lack of effective authentication mechanism for management frames and control frames and the defects of Carrier-sense multiple access with collision avoidance (CSMA/CA) mechanism.…”

Section: Availabilitymentioning

confidence: 99%

A Survey on Securing IoT Ecosystems and Adaptive Network Vision

Goli¹,

Kim²

2021

IJNDC

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The rapid growth of Internet-of-Things (IoT) devices and the large network of interconnected devices pose new security challenges and privacy threats that would put those devices at high risk and cause harm to the affiliated users. This paper emphasizes such potential security challenges and proposes possible solutions in the field of IoT Security, mostly focusing on automated or adaptive networks. Considering the fact that IoT became widely adopted, the intricacies in the security field tend to grow expeditiously. Therefore, it is necessary for businesses to adopt new security protocols and to the notion of automated network security practices driven by analytic and intelligence, to ensure a prompt response to attacks there by protecting the privacy and data integrity of users. The main prospect of this paper is to highlight some extensive reviews on standardizing security solutions by means of adaptive networks, a programmable environment that is driven by analytical and intelligence which expands on the autonomous networking concepts and transforms static networks into a dynamic environment. Furthermore, this paper also inspects some of the Machine Learning techniques that can be used to enhance security and compares different techniques to find the best fit to IoT.

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Hybrid IDS using SVM classifier for detecting DoS attack in MANET application

Cited by 11 publications

References 3 publications

Detection and Isolation of DoS and Integrity Cyber Attacks in Cyber-Physical Systems with a Neural Network-Based Architecture

Detection and Isolation of DoS and Integrity Cyber Attacks in Cyber-Physical Systems with a Neural Network-Based Architecture

MOpt Shield: An Intrusion Detection System based on Meld Optimization Algorithm to mitigate Amalgam Attacks

A Survey on Securing IoT Ecosystems and Adaptive Network Vision

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