The objective of the study is to design a heuristic supervised learning algorithm, that locates I... more The objective of the study is to design a heuristic supervised learning algorithm, that locates Intrusion and improves performance of network. In this paper we have proposed the algorithm using existing supervised learning approach and evaluated IDS for MANETs. The trained dataset of KDDCUP is loaded and known four attacks are taken for evaluation. We assume that discussed four attacks dominate the network traffic. The algorithm is iterative in nature to produce optimum results. The performance of proposed supervised algorithm is evaluated under different network traffic and mobility patterns for Dos, PRB, R2L and U2R attacks. The results indicate high accuracy for almost all the four attacks. The proposed algorithms, results show high accuracy on discussed four attacks of KDD 99. It also produces low high positive rate.
The objective of the study is to design a heuristic supervised learning algorithm, that locates I... more The objective of the study is to design a heuristic supervised learning algorithm, that locates Intrusion and improves performance of network. In this paper we have proposed the algorithm using existing supervised learning approach and evaluated IDS for MANETs. The trained dataset of KDDCUP is loaded and known four attacks are taken for evaluation. We assume that discussed four attacks dominate the network traffic. The algorithm is iterative in nature to produce optimum results. The performance of proposed supervised algorithm is evaluated under different network traffic and mobility patterns for Dos, PRB, R2L and U2R attacks. The results indicate high accuracy for almost all the four attacks. The proposed algorithms, results show high accuracy on discussed four attacks of KDD 99. It also produces low high positive rate.
The MANET (Mobile Adhoc Network) is vulnerable to several types of attacks. The most commonly cla... more The MANET (Mobile Adhoc Network) is vulnerable to several types of attacks. The most commonly classified attack is black hole attack, which is carried by single or multiple attackers, advertising itself of having a short fresh route to transmit data. The aim is to ensure security against the black hole attack and analyze the performance in geographical routing. The simple method is to send data as small blocks instead of entire data. The traffic is monitored independently in its neighborhood. The mechanism uses geographic information to detect variance in neighbor relations and node movements. We analyze the black hole attack in two popular location based protocol LAR and DREAM. It provides the stimulation study of black hole attack with the minimum attacker and also provides analysis on the parameters such as throughput, packet delivery and delay done with OMNET++ simulator. The simulation results show that packet loss increases and throughput decreases in the network with a black hole node in geographical routing. The proposed mechanism can be combined with existent routing protocols to defend against black hole attacks.
Most of the researches of sensor network work on terrain but there is lot of scope in transformin... more Most of the researches of sensor network work on terrain but there is lot of scope in transforming communications in underwater. The marine environment is heterogeneous and vast in both surface area and volume. The sensors equipped in oceans help in gathering of scientific data, monitoring disasters and pollution. The protocols developed face multiple challenges limited processing capability and memory, power conservation, marine fowling of equipment, communication difficulties and limited accessibility of updating sensors. The cost of deploying underwater sensor is high when compared to other regions. This makes deployment in underwater very challenging. This paper seek to identify the key issues and application aspects faced in marine based communication of sensor network platform, which are not much highlighted or emphasized in underwater survey.
The objective of the study is to design a heuristic supervised learning algorithm, that locates I... more The objective of the study is to design a heuristic supervised learning algorithm, that locates Intrusion and improves performance of network. In this paper we have proposed the algorithm using existing supervised learning approach and evaluated IDS for MANETs. The trained dataset of KDDCUP is loaded and known four attacks are taken for evaluation. We assume that discussed four attacks dominate the network traffic. The algorithm is iterative in nature to produce optimum results. The performance of proposed supervised algorithm is evaluated under different network traffic and mobility patterns for Dos, PRB, R2L and U2R attacks. The results indicate high accuracy for almost all the four attacks. The proposed algorithms, results show high accuracy on discussed four attacks of KDD 99. It also produces low high positive rate.
The objective of the study is to design a heuristic supervised learning algorithm, that locates I... more The objective of the study is to design a heuristic supervised learning algorithm, that locates Intrusion and improves performance of network. In this paper we have proposed the algorithm using existing supervised learning approach and evaluated IDS for MANETs. The trained dataset of KDDCUP is loaded and known four attacks are taken for evaluation. We assume that discussed four attacks dominate the network traffic. The algorithm is iterative in nature to produce optimum results. The performance of proposed supervised algorithm is evaluated under different network traffic and mobility patterns for Dos, PRB, R2L and U2R attacks. The results indicate high accuracy for almost all the four attacks. The proposed algorithms, results show high accuracy on discussed four attacks of KDD 99. It also produces low high positive rate.
The MANET (Mobile Adhoc Network) is vulnerable to several types of attacks. The most commonly cla... more The MANET (Mobile Adhoc Network) is vulnerable to several types of attacks. The most commonly classified attack is black hole attack, which is carried by single or multiple attackers, advertising itself of having a short fresh route to transmit data. The aim is to ensure security against the black hole attack and analyze the performance in geographical routing. The simple method is to send data as small blocks instead of entire data. The traffic is monitored independently in its neighborhood. The mechanism uses geographic information to detect variance in neighbor relations and node movements. We analyze the black hole attack in two popular location based protocol LAR and DREAM. It provides the stimulation study of black hole attack with the minimum attacker and also provides analysis on the parameters such as throughput, packet delivery and delay done with OMNET++ simulator. The simulation results show that packet loss increases and throughput decreases in the network with a black hole node in geographical routing. The proposed mechanism can be combined with existent routing protocols to defend against black hole attacks.
Most of the researches of sensor network work on terrain but there is lot of scope in transformin... more Most of the researches of sensor network work on terrain but there is lot of scope in transforming communications in underwater. The marine environment is heterogeneous and vast in both surface area and volume. The sensors equipped in oceans help in gathering of scientific data, monitoring disasters and pollution. The protocols developed face multiple challenges limited processing capability and memory, power conservation, marine fowling of equipment, communication difficulties and limited accessibility of updating sensors. The cost of deploying underwater sensor is high when compared to other regions. This makes deployment in underwater very challenging. This paper seek to identify the key issues and application aspects faced in marine based communication of sensor network platform, which are not much highlighted or emphasized in underwater survey.
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performance of network. In this paper we have proposed the algorithm using existing supervised learning approach and
evaluated IDS for MANETs. The trained dataset of KDDCUP is loaded and known four attacks are taken for evaluation. We
assume that discussed four attacks dominate the network traffic. The algorithm is iterative in nature to produce optimum
results. The performance of proposed supervised algorithm is evaluated under different network traffic and mobility
patterns for Dos, PRB, R2L and U2R attacks. The results indicate high accuracy for almost all the four attacks. The proposed
algorithms, results show high accuracy on discussed four attacks of KDD 99. It also produces low high positive rate.
performance of network. In this paper we have proposed the algorithm using existing supervised learning approach and
evaluated IDS for MANETs. The trained dataset of KDDCUP is loaded and known four attacks are taken for evaluation. We
assume that discussed four attacks dominate the network traffic. The algorithm is iterative in nature to produce optimum
results. The performance of proposed supervised algorithm is evaluated under different network traffic and mobility
patterns for Dos, PRB, R2L and U2R attacks. The results indicate high accuracy for almost all the four attacks. The proposed
algorithms, results show high accuracy on discussed four attacks of KDD 99. It also produces low high positive rate.
attack is black hole attack, which is carried by single or multiple attackers, advertising itself of having a short
fresh route to transmit data.
The aim is to ensure security against the black hole attack and analyze the performance in geographical routing.
The simple method is to send data as small blocks instead of entire data. The traffic is monitored independently
in its neighborhood. The mechanism uses geographic information to detect variance in neighbor relations and
node movements. We analyze the black hole attack in two popular location based protocol LAR and DREAM. It
provides the stimulation study of black hole attack with the minimum attacker and also provides analysis on the
parameters such as throughput, packet delivery and delay done with OMNET++ simulator. The simulation
results show that packet loss increases and throughput decreases in the network with a black hole node in
geographical routing. The proposed mechanism can be combined with existent routing protocols to defend
against black hole attacks.
in underwater. The marine environment is heterogeneous and vast in both surface area and volume. The sensors
equipped in oceans help in gathering of scientific data, monitoring disasters and pollution. The protocols developed
face multiple challenges limited processing capability and memory, power conservation, marine fowling of
equipment, communication difficulties and limited accessibility of updating sensors. The cost of deploying
underwater sensor is high when compared to other regions. This makes deployment in underwater very challenging.
This paper seek to identify the key issues and application aspects faced in marine based communication of sensor
network platform, which are not much highlighted or emphasized in underwater survey.
performance of network. In this paper we have proposed the algorithm using existing supervised learning approach and
evaluated IDS for MANETs. The trained dataset of KDDCUP is loaded and known four attacks are taken for evaluation. We
assume that discussed four attacks dominate the network traffic. The algorithm is iterative in nature to produce optimum
results. The performance of proposed supervised algorithm is evaluated under different network traffic and mobility
patterns for Dos, PRB, R2L and U2R attacks. The results indicate high accuracy for almost all the four attacks. The proposed
algorithms, results show high accuracy on discussed four attacks of KDD 99. It also produces low high positive rate.
performance of network. In this paper we have proposed the algorithm using existing supervised learning approach and
evaluated IDS for MANETs. The trained dataset of KDDCUP is loaded and known four attacks are taken for evaluation. We
assume that discussed four attacks dominate the network traffic. The algorithm is iterative in nature to produce optimum
results. The performance of proposed supervised algorithm is evaluated under different network traffic and mobility
patterns for Dos, PRB, R2L and U2R attacks. The results indicate high accuracy for almost all the four attacks. The proposed
algorithms, results show high accuracy on discussed four attacks of KDD 99. It also produces low high positive rate.
attack is black hole attack, which is carried by single or multiple attackers, advertising itself of having a short
fresh route to transmit data.
The aim is to ensure security against the black hole attack and analyze the performance in geographical routing.
The simple method is to send data as small blocks instead of entire data. The traffic is monitored independently
in its neighborhood. The mechanism uses geographic information to detect variance in neighbor relations and
node movements. We analyze the black hole attack in two popular location based protocol LAR and DREAM. It
provides the stimulation study of black hole attack with the minimum attacker and also provides analysis on the
parameters such as throughput, packet delivery and delay done with OMNET++ simulator. The simulation
results show that packet loss increases and throughput decreases in the network with a black hole node in
geographical routing. The proposed mechanism can be combined with existent routing protocols to defend
against black hole attacks.
in underwater. The marine environment is heterogeneous and vast in both surface area and volume. The sensors
equipped in oceans help in gathering of scientific data, monitoring disasters and pollution. The protocols developed
face multiple challenges limited processing capability and memory, power conservation, marine fowling of
equipment, communication difficulties and limited accessibility of updating sensors. The cost of deploying
underwater sensor is high when compared to other regions. This makes deployment in underwater very challenging.
This paper seek to identify the key issues and application aspects faced in marine based communication of sensor
network platform, which are not much highlighted or emphasized in underwater survey.