Cross centric intrusion detection system for secure routing over black hole attacks in MANETs

2019 ◽  
Vol 148 ◽  
pp. 129-135 ◽  
Author(s):  
N. Rajendran ◽  
P.K. Jawahar ◽  
R. Priyadarshini
Keyword(s):  
Black Hole ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection System ◽  
Secure Routing

scholarly journals PDTB-IDS: A Parameter and Distributed Trust Based Intrusion Detection System for Wireless Sensor Network

2019 ◽  
Vol 8 (4) ◽  
pp. 11730-11737
Keyword(s):  
Wireless Sensor Network ◽  
Intrusion Detection ◽  
Sensor Network ◽  
Intrusion Detection System ◽  
Detection System ◽  
Research Work ◽  
Trust Model ◽  
Secure Routing ◽  
Wireless Sensor ◽  
General Trust

Wireless sensor network (WSN) is a noteworthy division in present day correspondence frameworks and faith detecting steering convention is utilized to improve security in WSN. Already, Trust Sensing based Secure Routing Mechanism (TSSRM) was projected which will diminish the overhead steering and improve the unwavering quality of information transmission over the system. In any case, the security tool of this technique might be invalid, if the system steering convention is modified. Hence, in this work, a Parameter and Distributed Trust Based Intrusion Detection System (PDTB-IDS) with a safe correspondence structure with a trust the board framework for remote sensor systems are proposed. The significant commitment is to distinguish different parameters and trust factors that impact trust in WSN is conveyed among different factors, for example, vitality, unwavering quality, information, and so on. Subsequently coordinate believe, proposal believe and circuit trust from those components are determined and the general trust estimation of the sensor hub is evaluated by joining the individual trust esteems. The trust model can decide whether or not the specific hub is pernicious or not by looking at trust got from the proposed method. The numerical assessment of the research work is completed with the help of NS2 simulation environment from which it is proved that the projected strategy provides enhanced outcome than the present TSSRM method.

scholarly journals Study of Intrusion Detection System

2021 ◽  
Vol 9 (VI) ◽  
pp. 788-792
Author(s):  
Miss. Manoshri A. Ghawade
Keyword(s):  
Intrusion Detection ◽  
Key Management ◽  
Intrusion Detection System ◽  
Detection System ◽  
Denial Of Service ◽  
Secure Routing ◽  
Abnormal Behavior ◽  
Sybil Attack ◽  
Malicious Activity ◽  
Network Intrusion

An intrusion detection system (IDS) could be a device or software application that observes a network for malicious activity or policy violations. Any malicious activity or violation is often reported or collected centrally employing a security information and event management system. Some IDS’s are proficient of responding to detected intrusion upon discovery. These are classified as intrusion prevention systems (IPS). A system that analyzes incoming network traffic is thought as Network intrusion detection system (NIDS). A system that monitors important software files is understood as Host intrusion detection system (HIDS). Wireless sensor networks (WSNs) are vulnerable to different kinds of security threats which will degenrate the performance of the entire network; that may lead to fatal problems like denial of service (DoS) attacks, direction attacks, Sybil attack etc. Key management protocols, authentication protocols and secure routing cannot provide security to WSNs for these varieties of attacks. Intrusion detection system (IDS) could be a solution to the present problem. It analyzes the network by collecting sufficient amount of knowledge and detects abnormal behavior of sensor node(s).

scholarly journals Network Security Analysis in Vanet Against Black Hole and Jellyfish Attack with Intrusion Detection System Algorithm

2017 ◽  
Vol 11 (2) ◽  
pp. 77
Author(s):  
Elsa Mustikawati ◽  
Doan Perdana ◽  
Ridha Muldina Negara
Keyword(s):  
Black Hole ◽  
Intrusion Detection ◽  
Intelligent Transportation Systems ◽  
Intrusion Detection System ◽  
Detection System ◽  
Security Analysis ◽  
Transportation Systems ◽  
Delivery Ratio ◽  
Node Mobility ◽  
Network Simulator

VANET is the key to the Intelligent Transportation Systems (ITS), where vehicles can communicate with others to exchange information in real time. VANET is an ad-hoc that has no fixed infrastructure and rapidly changing network topology. As the result, the network is insecure and vulnerable to various attacks both from within and outside the network. This research analyzes AODV routing protocol comparing the conditions without the attacks and with the attacks with the of black hole and jellyfish using the algorithm of Intrusion Detection System with the number of nodes changing from 10 to 100 nodes at the change speeds of 70, 80, 90, 100, 110, and 120 km/h. This research is simulated using Network Simulator 2 to model the network and ONESimulator to model node mobility. The analyzed QoS parameters are packet delivery ratio (PDR), throughput, and end-to-end delay. The results of the simulation show that changing the number of nodes and node velocity affects the performance in the network. On the number of nodes scenario with attacks, the average value of PDR decreases by 48.03%, throughput decreases by 50.23%, and delay, for black hole, decreases by 80.18% but increases by 47.87% for jellyfish. Whereas in the node velocity scenario, the average values of PDR, throughput, and delay decrease by 58.52%, 60.34%, 13.81% for blackhole attack, respectively. However, the delay increases by 123.91% for jellyfish attack.

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