![LITERATURE REVIEW
• Rajesh Yerneni [1] proposed a method is proposed called Secure-Ad hoc On demand
Distance Vector (SAODV) algorithm that mitigates black hole attack by analyzing
destination sequence number and validating the destination by random value. Simulation
results show that the proposed protocol provides better security by increasing the packet
delivery ratio when compared to AODV in presence of black hole attacks.
• Hesiri Weerasinghe [2] proposed a solution to identifying and preventing the
cooperative black hole attack. Presented solution discovers the secure route between
source and destination by identifying and isolating cooperative black hole nodes. In this
paper, via simulation, Author evaluate the proposed solution and compare it with other
existing solutions in terms of throughput, packet loss percentage, average end-toend
delay and route request overhead.
• Mehdi Medadian [3] an approach is proposed to combat the Cooperative/ Multiple
Blackhole attack by using negotiation with neighbors who claim to have a route to
destination. The Simulation’s results show that the proposed protocol provides better
security and also better performance in terms of packet delivery than the conventional
AODV in the presence of Black holes with minimal additional delay and Overhead.](https://image.slidesharecdn.com/aadaptiveneighboranalysisapproachtodetectcooperativeselfishnodeinmanet-170801050848/85/A-adaptive-neighbor-analysis-approach-to-detect-cooperative-selfish-node-in-manet-13-320.jpg)
![• Sweta Jain [4] presents a review on a major category of coordinated attacks i.e. cooperative
blackhole / grayhole attack which are a serious threat to ad hoc network security. In
cooperative blackhole attack multiple nodes collude to hide the malicious activity of other
nodes; hence such attacks are more difficult to detect.
• Sanjay Ramaswamy [5] Author addresses the problem of coordinated attack by multiple black
holes acting in group. Author presents a technique to identify multiple black holes cooperating
with each other and a solution to discover a safe route avoiding cooperative black hole attack.
Varsha Patidar performed a work," Blackhole Attack and its Counter Measures in AODV
Routing Protocol".
• Mobile Ad-Hoc network is a collection of mobile node. In this network, a wireless node
usually moves randomly and dynamically forms a temporary network without a network
infrastructure. A malicious node send Route Response (RREP) incorrectly of having route to
destination with minimum hop count and when sender sends the data packet to this malicious
node, it drops all the packet in the network[6].
•
• Harsh Pratap[7] presents RBS (Reference Broadcast Synchronization) & Relative velocity
distance method for clock synchronization process in Mobile ad-hoc Network for removal of
cooperative black hole node. This paper evaluates the performance in NS2 network simulator
and Presented analysis indicates that this method is very suitable to remove black hole attack.](https://image.slidesharecdn.com/aadaptiveneighboranalysisapproachtodetectcooperativeselfishnodeinmanet-170801050848/85/A-adaptive-neighbor-analysis-approach-to-detect-cooperative-selfish-node-in-manet-14-320.jpg)
![REFERENCES
[1] Rajesh Yerneni," Enhancing performance of AODV against Black hole Attack",
• CUBE 2012, September 3–5, 2012, Pune, Maharashtra, India. ACM 978-1-4503-1185-4/12/09
[2] Hesiri Weerasinghe," Preventing Cooperative Black Hole Attacks in Mobile Ad Hoc
Networks:Simulation Implementation and Evaluation", International Journal of Software
Engineering and Its Applications Vol. 2, No. 3, July, 2008
[3] Mehdi Medadian," Detection and Removal of Cooperative and Multiple Black Hole
Attack in Mobile ADHOC Networks", 2011 International Conference on Computer and Software
Modeling IPCSIT vol.14 (2011) © (2011) IACSIT Press, Singapore
[4] Sweta Jain," A Review Paper on Cooperative Blackhole And Grayhole Attacks in Mobile Ad hoc
Networks", International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.2, No.3,
September 2011
[5] Sanjay Ramaswamy," Prevention of Cooperative Black Hole Attack in Wireless Ad Hoc Networks".
[6] Varsha Patidar," Black Hole Attack and its Counter Measures in AODV Routing Protocol",
International Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 5
[7] Harsh Pratap Singh," Guard against cooperative black hole attack in Mobile Ad-Hoc Network",
International Journal of Engineering Science and Technology (IJEST) ISSN : 0975-5462 Vol. 3 No. 7
July 2011](https://image.slidesharecdn.com/aadaptiveneighboranalysisapproachtodetectcooperativeselfishnodeinmanet-170801050848/85/A-adaptive-neighbor-analysis-approach-to-detect-cooperative-selfish-node-in-manet-20-320.jpg)
![[8] Poonam," Eliminating Misbehaving nodes by Opinion Based Trust Evaluation Model in MANETs",
ICCCS’11, February 12–14, 2011, Rourkela, Odisha, India. ACM 978-1-4503-0464-1/11/02
[9] Poonam Gera," Trust Based Multi-Path Routing for End to End Secure Data Delivery in MANETs",
SIN’10, Sept. 7–11, 2010, Taganrog, Rostov-on-Don, Russian Federation. ACM 978-1-4503-0234-
0/10/09
[10] M.Shobana," GEOGRAPHIC ROUTING USED IN MANET FOR BLACK HOLE DETECTION", CCSEIT-12,
October 26-28, 2012, Coimbatore [Tamil nadu, India]
ACM 978-1-4503-1310-0/12/10
[11] Poonam," Misbehaving nodes Detection through Opinion Based Trust Evaluation Model in
MANETs", International Conference and Workshop on Emerging Trends in Technology (ICWET 2011)
– TCET, Mumbai, India ICWET’11, February 25–26, 2011, Mumbai, Maharashtra, India. ACM 978-1-
4503-0449-8/11/02
[12] Kamaljit Kaur," Comparative Analysis of Black Hole Attack over Cloud Network using AODV and
DSDV", CCSEIT-12, October 26-28, 2012, Coimbatore [Tamil nadu, India] ACM 978-1-4503-1310-
0/12/10
[13] B.Revathi," A Survey of Cooperative Black and Gray hole Attack in MANET", International Journal of
Computer Science and Management Research Vol 1 Issue 2 September 2012 ISSN 2278-733X
[14] Vishnu K," Detection and Removal of Cooperative Black/Gray hole attack in Mobile ADHOC
Networks", 2010 International Journal of Computer Applications (0975 - 8887) Volume 1 – No. 22
[15] Moumita Deb," A Cooperative Blackhole Node Detection Mechanism for ADHOC Networks",
Proceedings of the World Congress on Engineering and Computer Science 2008 WCECS 2008,
October 22 - 24, 2008, San Francisco, USA ISBN: 978-988-98671-0-2](https://image.slidesharecdn.com/aadaptiveneighboranalysisapproachtodetectcooperativeselfishnodeinmanet-170801050848/85/A-adaptive-neighbor-analysis-approach-to-detect-cooperative-selfish-node-in-manet-21-320.jpg)
A adaptive neighbor analysis approach to detect cooperative selfish node in manet
- 1. A Adaptive Neighbor Analysis Approach To Detect Cooperative Selfish Node In MANET
- 2. Index 1. Introduction of MANET 2. History of MANET 3. Need of MANET 4. Challenges of MANET 5. Security solution to MANET 6. Attacks on MANET 7. Problem Definition 8. Detect the Selfish Node 9. Trust Table 10. Literature Review 11. Objectives 12. Proposed Work 13. Reference
- 3. MANET MANET means mobile ad hoc network Ad Hoc means “for the purpose”. Mobile network is a set of wireless device called wireless nodes(mobile, Laptop) which are dynamically connect and transfer the information. In MANET nodes can be source, destination and intermediate node of data transmission. I S=Source Node S D I=Intermediate Node D=Destination (Simple Transmission) Node
- 4. HISTORY OF MANET Life cycle of mobile ad hoc network into first second and third generation First generation came into 1970’s Second generation came into 1980’s Third generation came into1990’s Present ad hoc network comes into third generation.
- 5. NEED OF MANET Mobile are used for communication We can use anywhere Also used for email
- 6. CURRENT CHALLENGES Network size Limited range of wireless transmission Packet losses due to error transmission Some time route change
- 7. SECURITY SOLUTION TO MANET Authentication Confidentiality Integrity Non-Repudiation
- 8. ATTACKS IN MANET Due to dynamic nature, so no single security solution is enough because there are different types of attacks in MANET: Main attacks are: Active Attacks Passive Attacks Selfish node Attacks
- 9. PROBLEM DEFINITION Selfish Node Attack: Mobile network is widely, when we send data packets from source node to destination node, the intermediate node can be anyone because packets can use any route path. S D When intermediate node does not transfer packets to next node or change the data is called the selfish node attacks.
- 10. DETECT THE SELFISH NODE Selfish node will be detect by using the neighbor node. Neighbor node send the route request to next node for checkout the selfish node. If that node does not reply in the specified time interval it means that node is the selfish node. For ensure the status of the selfish node other neighbors nodes also send route requests to that node, if that node reply is less than the route request it means that node is the selfish node.
- 11. N N SELFISH S NODE N D N N N (Detect Selfish Node By Using the Neighbor Node)
- 12. TRUST TABLE The whole information will be maintained in the trust table with three fields: source node , Destination node and the Reply status like how many times route request is sended and their reply. Status of the node will be shown by using the bit like if the node is valid 1 will be used and if the node is selfish 0 will be used.
- 13. LITERATURE REVIEW • Rajesh Yerneni [1] proposed a method is proposed called Secure-Ad hoc On demand Distance Vector (SAODV) algorithm that mitigates black hole attack by analyzing destination sequence number and validating the destination by random value. Simulation results show that the proposed protocol provides better security by increasing the packet delivery ratio when compared to AODV in presence of black hole attacks. • Hesiri Weerasinghe [2] proposed a solution to identifying and preventing the cooperative black hole attack. Presented solution discovers the secure route between source and destination by identifying and isolating cooperative black hole nodes. In this paper, via simulation, Author evaluate the proposed solution and compare it with other existing solutions in terms of throughput, packet loss percentage, average end-toend delay and route request overhead. • Mehdi Medadian [3] an approach is proposed to combat the Cooperative/ Multiple Blackhole attack by using negotiation with neighbors who claim to have a route to destination. The Simulation’s results show that the proposed protocol provides better security and also better performance in terms of packet delivery than the conventional AODV in the presence of Black holes with minimal additional delay and Overhead.
- 14. • Sweta Jain [4] presents a review on a major category of coordinated attacks i.e. cooperative blackhole / grayhole attack which are a serious threat to ad hoc network security. In cooperative blackhole attack multiple nodes collude to hide the malicious activity of other nodes; hence such attacks are more difficult to detect. • Sanjay Ramaswamy [5] Author addresses the problem of coordinated attack by multiple black holes acting in group. Author presents a technique to identify multiple black holes cooperating with each other and a solution to discover a safe route avoiding cooperative black hole attack. Varsha Patidar performed a work," Blackhole Attack and its Counter Measures in AODV Routing Protocol". • Mobile Ad-Hoc network is a collection of mobile node. In this network, a wireless node usually moves randomly and dynamically forms a temporary network without a network infrastructure. A malicious node send Route Response (RREP) incorrectly of having route to destination with minimum hop count and when sender sends the data packet to this malicious node, it drops all the packet in the network[6]. • • Harsh Pratap[7] presents RBS (Reference Broadcast Synchronization) & Relative velocity distance method for clock synchronization process in Mobile ad-hoc Network for removal of cooperative black hole node. This paper evaluates the performance in NS2 network simulator and Presented analysis indicates that this method is very suitable to remove black hole attack.
- 15. OBJECTIVES This work will give an efficient and reliable transmission over the network. The research objectives are: The main objective of the work is identifying the selfish node over the active path by performing a nearest neighbor analysis. As the selfish node will be identified a status set will be performed by using bit change. The difference objective of the work is to define a eventual process to identify all the passive selfish attack over the network that are not the part of active communication path. The analysis of the work will be performed under different communication parameters such as network throughput, error rate etc.
- 16. PURPOSED WORK Purposed work is about to detect the selfish node from both active and passive path in the chain. N P P P P PP S A P A P D N P P P P P P N (Active and Passive Path) The selfish node is detected by send route request to the neighbor node, if the node does not reply, is selfish node. For ensure the status of node all node all neighbor node of the selfish node send route request, if maximum node not get the reply, the node is declared the selfish node. The step by step work of the given research proposal is shown as:
- 17. Establish a mobile network with n number of nodes Define a source and destination node and perform the communication Identify the next communicating node over the path and send route request to that node If the reply is not in the specified time interval is known as selfish node
- 18. (Process of Research) Define a source and destination node and perform the communication Perform Nearest neighbor check to ensure the safe node A safe path is identified to perform the secure transmission Generate a separate process to identify all cooperative Selfish Node
- 19. RESEARCH METHODOLOGIES The fundamental idea behind this research is to increase the Efficient and reliable transmission over the network. The tools and techniques used in the study will be: • Study of Literature • Analysis the selfish node by the neighbor node from the network • On line Interpretation results • Development of Inferential framework • Change order upon interrupts in form of feedback and publications • Overall outcome processing, development of related facts
- 20. REFERENCES [1] Rajesh Yerneni," Enhancing performance of AODV against Black hole Attack", • CUBE 2012, September 3–5, 2012, Pune, Maharashtra, India. ACM 978-1-4503-1185-4/12/09 [2] Hesiri Weerasinghe," Preventing Cooperative Black Hole Attacks in Mobile Ad Hoc Networks:Simulation Implementation and Evaluation", International Journal of Software Engineering and Its Applications Vol. 2, No. 3, July, 2008 [3] Mehdi Medadian," Detection and Removal of Cooperative and Multiple Black Hole Attack in Mobile ADHOC Networks", 2011 International Conference on Computer and Software Modeling IPCSIT vol.14 (2011) © (2011) IACSIT Press, Singapore [4] Sweta Jain," A Review Paper on Cooperative Blackhole And Grayhole Attacks in Mobile Ad hoc Networks", International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.2, No.3, September 2011 [5] Sanjay Ramaswamy," Prevention of Cooperative Black Hole Attack in Wireless Ad Hoc Networks". [6] Varsha Patidar," Black Hole Attack and its Counter Measures in AODV Routing Protocol", International Journal Of Computational Engineering Research (ijceronline.com) Vol. 2 Issue. 5 [7] Harsh Pratap Singh," Guard against cooperative black hole attack in Mobile Ad-Hoc Network", International Journal of Engineering Science and Technology (IJEST) ISSN : 0975-5462 Vol. 3 No. 7 July 2011
- 21. [8] Poonam," Eliminating Misbehaving nodes by Opinion Based Trust Evaluation Model in MANETs", ICCCS’11, February 12–14, 2011, Rourkela, Odisha, India. ACM 978-1-4503-0464-1/11/02 [9] Poonam Gera," Trust Based Multi-Path Routing for End to End Secure Data Delivery in MANETs", SIN’10, Sept. 7–11, 2010, Taganrog, Rostov-on-Don, Russian Federation. ACM 978-1-4503-0234- 0/10/09 [10] M.Shobana," GEOGRAPHIC ROUTING USED IN MANET FOR BLACK HOLE DETECTION", CCSEIT-12, October 26-28, 2012, Coimbatore [Tamil nadu, India] ACM 978-1-4503-1310-0/12/10 [11] Poonam," Misbehaving nodes Detection through Opinion Based Trust Evaluation Model in MANETs", International Conference and Workshop on Emerging Trends in Technology (ICWET 2011) – TCET, Mumbai, India ICWET’11, February 25–26, 2011, Mumbai, Maharashtra, India. ACM 978-1- 4503-0449-8/11/02 [12] Kamaljit Kaur," Comparative Analysis of Black Hole Attack over Cloud Network using AODV and DSDV", CCSEIT-12, October 26-28, 2012, Coimbatore [Tamil nadu, India] ACM 978-1-4503-1310- 0/12/10 [13] B.Revathi," A Survey of Cooperative Black and Gray hole Attack in MANET", International Journal of Computer Science and Management Research Vol 1 Issue 2 September 2012 ISSN 2278-733X [14] Vishnu K," Detection and Removal of Cooperative Black/Gray hole attack in Mobile ADHOC Networks", 2010 International Journal of Computer Applications (0975 - 8887) Volume 1 – No. 22 [15] Moumita Deb," A Cooperative Blackhole Node Detection Mechanism for ADHOC Networks", Proceedings of the World Congress on Engineering and Computer Science 2008 WCECS 2008, October 22 - 24, 2008, San Francisco, USA ISBN: 978-988-98671-0-2
- 22. THANK YOU