scholarly journals RANDOM-AODV: Efficient Adhoc on Demand Distance Vector Routing Protocol using Fuzzy Logic during Black Hole Attack

2019 ◽  
Vol 9 (2) ◽  
pp. 2730-2734
Keyword(s):  
Black Hole ◽  
Fuzzy Logic ◽  
Packet Delivery Ratio ◽  
Delivery Ratio ◽  
Black Hole Attack ◽  
Node Selection ◽  
Packet Dropping ◽  
Packet Delivery ◽  
Random Node ◽  
The Impact

However the black hole attack prevention has been proposed earlier but it is observed that the packet dropping increases constantly as the number of black hole attack are increased. The proposed work is making use of fuzzy logic. This mechanism allows the random node selection so it is supposed to maintain the packet delivery ratio. Results of this research show that the proposed mechanisms do not allow packet dropping on constant rate. Many studies are made that are simulating influence of attack made by .black .hole in the network based on .AODV. It has been observed that there is constant fall in the packet dropping ratio if number of malicious packet increases. This paper has represented the Black Hole attack over AODV routing when random node selection mechanism is applied. Proposed work is allowing selection of nodes on random basis. Such mechanism is supposed to improve the ratio of delivery of packet. Results of Simulation indicates the impact of black hole attack over packet delivery ratio , packet .loss .ratio, .Average .end to .end delivery, and .routing over head. Moreover the comparative analysis of .traditional and .proposed model is made considering packet delivery ratio.

scholarly journals Comparative Performance AODV-ANT and AOMDV-ANT in BlackHole

2018 ◽  
Vol 7 (4.34) ◽  
pp. 358
Author(s):  
Ajeng Mayang ◽  
Savitri Galih
Keyword(s):  
Black Hole ◽  
Delivery Ratio ◽  
Node Mobility ◽  
Black Hole Attack ◽  
Comparative Performance ◽  
Packet Delivery ◽  
Blackhole Attack ◽  
Random Node ◽  
The Impact ◽  
Better Than

In this paper, we simulate the black hole attack to compare performance AODV-ANT and AOMDV-ANT to support the advance of the node communications to deliver a good management. In our simulation, the result shows AODV-ANT has decrease packets receive in Blackhole attack comparing without black hole until 0.03%, and while in AOMDV-ANT decrease until 0.47%. But, in throughput, AOMDV-ANT is better than AODV-ANT. The result is AOMDV-ANT has decrease throughput in Blackhole attack comparing without black hole until 0.93%, and while in AODV-ANT decrease until 1.85%. Then, in packet delivery ratio (PDR), AODV-ANT has decrease PDR in Blackhole attack comparing without black hole until 10.357%, and while in AOMDV-ANT decrease until 13.57%. In simulation performed, the impact of the black hole can be seen in the PDR. This occurs because of the random node mobility. For our simulations using NS-2:35 as a tool. 

scholarly journals Host based Detection and Prevention of Black Hole attacks by AODV-ICCSO Algorithm for security in MANETs

2021 ◽  
Author(s):  
Sathyaraj P ◽  
Rukmani Devi D ◽  
K Kannan
Keyword(s):  
Black Hole ◽  
Performance Measures ◽  
Ad Hoc ◽  
Packet Delivery Ratio ◽  
Delivery Ratio ◽  
Black Hole Attack ◽  
Swarm Optimization ◽  
Packet Delivery ◽  
Node Routing ◽  
Chicken Swarm Optimization

Abstract Background: Mobile Ad-hoc Networks (i.e.) MANETs are gaining rapid fame in recent days and are considered as very significant because of their easier implementation and growing property. Various types of attacks are prone to damage the networks due to the elastic property possessed by the network. And among different categories of attacks that can affect MANETs, black hole attack is considered as the commonly occurring one within a MANET. Chicken Swarm Optimization (CSO) algorithm is one among the technique used for the detection of black hole attacks occurring in the MANETs. But the CSO algorithm possesses some disadvantages and necessity rises for overcoming the weakness in the CSO algorithm. Objective: Therefore, in this research paper, to address the black hole attack in MANET, an Improved Crossover Chicken Swarm Optimization (ICCSO) algorithm and the concept of Enhanced Partially-Mapped Crossover operation proposed and the best fitness values obtained. Methods: In ICCSO algorithm, parameter initialization is carried out in step 1 of the algorithm, where the attacked nodes and non-attack nodes are created separately with the aid of parameters like PDR (i.e.) Packet Delivery Ratio and RSSI (i.e.) Received Signal Strength Indicator. Further, If the node is affected by any attack, then the nodes are discarded and the data is transmitted through the non-attacked node. Routing is carried by a protocol of AODV.Results: The effectiveness of the algorithm proposed in the work is evaluated using various performance measures like packet delivery ratio (PDR), end-to-end delay (EED) and throughput. The performance measures are compared with a different state of the art routing protocols and it can be inferred that the proposed methodology comes up with improved results.

scholarly journals Effect on Packet Delivery Ratio (PDR) & Throughput in Wireless Sensor Networks Due to Black Hole Attack

2019 ◽  
Vol 8 (12S) ◽  
pp. 428-432
Keyword(s):  
Wireless Sensor Networks ◽  
Black Hole ◽  
Sensor Networks ◽  
Packet Delivery Ratio ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Network Simulator ◽  
Sybil Attack ◽  
Black Hole Attack ◽  
Packet Delivery

Wireless Sensor Networks are in rapid advance occupying every field of our lives. They are in great demand and are widely used in transmission of data like temperature, pressure, humidity, speed etc. As these networks are wireless and are easily prone to intrusion by the attackers. Hence the basic concern is security of data. The nodes in the network will be sending information between the nodes, and in between the nodes intrusion takes place with attack like wormhole attack, black hole attack, sybil attack, hello flood attack etc. which corrupts data. These attacks effect the efficiency of the network and the parameters like packet delivery ratio and throughput of the network is affected. Black hole is a severe attack in network which alters most of the data before it is received at the sink, hence has to be detected and prevented. In this paper, Adhoc on demand distance vector (AODV) protocol is used to detect and prevent the black hole attack using Network Simulator (NS-2.3)

Random Black Hole Attack Modelling and Mitigation Using Trust- Confidence Aware OLSR in MANETs for Private Data Communications

2020 ◽  
Vol 10 (2) ◽  
pp. 112-122
Author(s):  
Kirti A. Adoni ◽  
Anil S. Tavildar ◽  
Krishna K. Warhade
Keyword(s):  
Black Hole ◽  
Energy Consumption ◽  
Average Energy ◽  
Packet Delivery Ratio ◽  
Delivery Ratio ◽  
Black Hole Attack ◽  
Malicious Nodes ◽  
Packet Delivery ◽  
Routing Strategy ◽  
Average Energy Consumption

Background and Objective: Random Black Hole (BH) attack significantly degrades MANET’s performance. For strategic applications, the performance parameters like Packet Delivery Ratio, Routing Overheads, etc. are important. The objectives are: (a) To model random BH attack, (b) To propose a routing strategy for the protocol to mitigate random BH attack, (c) To evaluate and compare the network performance of modified protocol with the standard protocol. Methods: The random BH attack is modelled probabilistically. The analysis is carried out by varying Black Hole Attack (BHA) time as Early, Median, Late occurrences and mix of these three categories. The blocking performance is also analysed by varying the percentages of malicious presence in the network. Normal Optimized Link State Routing (OLSR) protocol is used to simulate the MANET performance using a typical medium size network. The protocol has then been modified using Trust- Confidence aware routing strategy, named as TCAOLSR, with a view to combat the degradations due to the random BH attack. Results: The random behavior of Black Hole attack is analyzed with all the possible random parameters, like deployment of mobile nodes, number of malicious nodes and timing instances at which these nodes change their state. From the results of individual type- Early, Median and Late, it is observed that the TCAOLSR protocol gives stable performance for Packet Delivery Ratio (PDR) and Routing Overheads (RO), whereas for OLSR protocol PDR gradually reduces and RO increases. For individual and mix type, Average Energy Consumption (AEC) per node increases marginally for TCAOLSR protocol. For the mix type, PDR for TCAOLSR is 40-60% better whereas RO for TCAOLSR is very less compared to OLSR protocol. The efficacy of the TCAOLSR protocol remains stable for different categories of BH attack with various percentages of malicious nodes compared to OLSR with the same environment. Conclusion: Simulations reveal that the modified protocol TCAOLSR, effectively mitigates the network degradation for Packet Delivery Ratio and Routing Overheads considerably, at the cost of a slight increase in Average Energy Consumption per node of the network. Efficacy of the OLSR and TCAOLSR protocols has also been defined and compared to prove robustness of the TCAOLSR protocol.

scholarly journals Impact of Black Hole Attack over Random Aodv Routing Protocol

2020 ◽  
Vol 9 (6) ◽  
pp. 1110-1115
Keyword(s):  
Black Hole ◽  
Routing Protocol ◽  
Network Performance ◽  
Research Work ◽  
Delivery Ratio ◽  
Black Hole Attack ◽  
Proposed Model ◽  
Random Node ◽  
The Impact ◽  
Selection Of

There are many researches in which the impact of black hole attacks at AODV networks is highlighted. In the research work, the impact of iBlack iHole iattack iover iAODV routing is calculated and random node selection technique is used. In addition, the simulation of black hole attacks’ impact on network performance is proposed in case of proposed model and traditional model. The selection of nodes is made randomly. The simulation of proposed selection based model is able to enhance the ratio of packet delivery. It is efficient to decrease the ratio of packet loss than traditional models. Comparative evaluation of the performance of existing and proposed model is made ion ithe ibase iof iPacket iDelivery iratio, iPacket iloss iratio, iPacket iDelivery iratio, iPacket iLoss iratio in case of 200 Node and 225 Node. This research paper also determined iAverage iEnd ito iEnd iDelivery iand iRouting iover head during comparative analysis. The proposed work can minimize the downfall in delivery ratio as the amount of malicious node increases.

scholarly journals ANALYSIS OF BLACK HOLE ATTACK DURING ROUTE DISCOVERY PHASE OF AODV IN MANET

2020 ◽  
Vol 4 (11) ◽  
pp. 75-80
Author(s):  
Lalit Tripathi ◽  
Kanojia Sindhuben
Keyword(s):  
Black Hole ◽  
Ad Hoc ◽  
Delivery Ratio ◽  
Route Discovery ◽  
Mobile Nodes ◽  
Black Hole Attack ◽  
Discovery Phase ◽  
Hoc Networks ◽  
Result Analysis ◽  
The Impact

MANET (Mobile ad hoc networks) is a collection of wireless mobile nodes dynamically forming an infrastructure less network. Several routing protocols are designed for routing of packets in MANET. One of them is AODV (Ad hoc on demand Distance Vector) protocol whose performance is better for higher mobile nodes. It is more vulnerable to black hole attack by the malicious node. Black hole attack is a network layer attack in MANET that tries to hamper the routing process. During route discovery phase it sends false reply to the nodes and dropped data packets. In this paper, first we have implemented black hole attack in AODV and then analyzed the impact of black hole attack under deferent metrics like throughput, packet delivery ratio and packet loss. Simulator NS-2.35 is used for implementation and result analysis.

scholarly journals Selfish Node Detection and Prevention Based on SDSR in Infrastructure-Less Networks

2021 ◽  
Author(s):  
Anusha Chintam ◽  
A. Sra ◽  
T.V. Madhusudhan Rao
Keyword(s):  
Black Hole ◽  
Packet Delivery Ratio ◽  
Mesh Network ◽  
Delivery Ratio ◽  
Performance Variables ◽  
Data Packets ◽  
Packet Delivery ◽  
Mobile Hosts ◽  
Wireless Mesh ◽  
Dynamic Source

Abstract Wireless mesh network formed temporarily by using mobile hosts (nodes) without the help of any centralized and cooperate to dispatch the data packets through wireless links over the network. Due to this decentralization, each node act as both router as well as host for dispatching packets in the network. Because of a dynamic nature that is the mobility nature of the node in a network is vulnerable to various types of attacks. Some of the attacks are gray and black hole attacks. These attacks are advertised incorrect information regarding the shortest path to the sink node. This paper proposes a secure Dynamic Source Routing (SDSR) for providing a secure and safe route between the origin and sink nodes which identify and remove the gray and black hole nodes in the network. The proposed work is simulated by using the NS2 simulator tool and got the better performance for considered performance variables such as packet delivery ratio, throughput and node overhead. The simulation results give better performance compared to normal DSR and selfish DSR with increased packet delivery ratio and throughput and with decreased overhead of the network.

scholarly journals Fuzzy Logic and Bio-Inspired Firefly Algorithm Based Routing Scheme in Intrabody Nanonetworks

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5526 ◽  
Author(s):  
Hamza Fahim ◽  
Wei Li ◽  
Shumaila Javaid ◽  
Mian Muhammad Sadiq Fareed ◽  
Gulnaz Ahmed ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Firefly Algorithm ◽  
Fitness Function ◽  
Packet Delivery Ratio ◽  
Delivery Ratio ◽  
Packet Delivery ◽  
Routing Scheme ◽  
Region Selection ◽  
End To End Delay ◽  
Selection Of

An intrabody nanonetwork (IBNN) is composed of nanoscale (NS) devices, implanted inside the human body for collecting diverse physiological information for diagnostic and treatment purposes. The unique constraints of these NS devices in terms of energy, storage and computational resources are the primary challenges in the effective designing of routing protocols in IBNNs. Our proposed work explicitly considers these limitations and introduces a novel energy-efficient routing scheme based on a fuzzy logic and bio-inspired firefly algorithm. Our proposed fuzzy logic-based correlation region selection and bio-inspired firefly algorithm based nano biosensors (NBSs) nomination jointly contribute to energy conservation by minimizing transmission of correlated spatial data. Our proposed fuzzy logic-based correlation region selection mechanism aims at selecting those correlated regions for data aggregation that are enriched in terms of energy and detected information. While, for the selection of NBSs, we proposed a new bio-inspired firefly algorithm fitness function. The fitness function considers the transmission history and residual energy of NBSs to avoid exhaustion of NBSs in transmitting invaluable information. We conduct extensive simulations using the Nano-SIM tool to validate the in-depth impact of our proposed scheme in saving energy resources, reducing end-to-end delay and improving packet delivery ratio. The detailed comparison of our proposed scheme with different scenarios and flooding scheme confirms the significance of the optimized selection of correlated regions and NBSs in improving network lifetime and packet delivery ratio while reducing the average end-to-end delay.

Effect of Black Hole Attacks on Wireless Sensor Networks

2017 ◽  
Vol 7 (7) ◽  
pp. 146
Author(s):  
Sachin Lalar ◽  
. Monika ◽  
Arun Kumar Yadav
Keyword(s):  
Wireless Sensor Networks ◽  
Black Hole ◽  
Sensor Networks ◽  
Packet Loss ◽  
Performance Metrics ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Black Hole Attack ◽  
Packet Delivery ◽  
Overall Performance

Wireless sensor networks (WSNs) establish a new popular of ambient supervision with many latent packages. The environment of wireless sensor networks prone to different forms of attacks as networks are prepared in open and unsecured surroundings. This paper analyses the overall performance of AODV whilst attacked by black hole, through varying the mobility of the nodes within the community. The overall performance metrics which can be used to do the analysis are LPR, packet delivery ratio & Packet loss. The simulation consequences display that the overall performance of each AODV degrades in the presence of black hole attack.

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