Prevention Of Black Hole Attack Research Articles

Trust-Based Optimized Reporting for Detection and Prevention of Black Hole Attacks in Low-Power and Lossy Green IoT Networks.

The Internet of Things (IoT) is empowering various sectors and aspects of daily life. Green IoT systems typically involve Low-Power and Lossy Networks (LLNs) with resource-constrained nodes. Lightweight routing protocols, such as the Routing Protocol for Low-Power and Lossy Networks (RPL), are increasingly being applied for efficient communication in LLNs. However, RPL is susceptible to various attacks, such as the black hole attack, which compromises network security. The existing black hole attack detection methods in Green IoT rely on static thresholds and unreliable metrics to compute trust scores. This results in increasing false positive rates, especially in resource-constrained IoT environments. To overcome these limitations, we propose a delta-threshold-based trust model called the Optimized Reporting Module (ORM) to mitigate black hole attacks in Green IoT systems. The proposed scheme comprises both direct trust and indirect trust and utilizes a forgetting curve. Direct trust is derived from performance metrics, including honesty, dishonesty, energy, and unselfishness. Indirect trust requires the use of similarity. The forgetting curve provides a mechanism to consider the most significant and recent feedback from direct and indirect trust. To assess the efficacy of the proposed scheme, we compare it with the well-known trust-based attack detection scheme. Simulation results demonstrate that the proposed scheme has a higher detection rate and low false positive alarms compared to the existing scheme, confirming the applicability of the proposed scheme in green IoT systems.

A Back propagation Neural Network Model for HWSNs Using IMIMO with a Secured Routing Mechanism

Generally, a wireless sensor network (WSN) is made up of autonomous devices that are spatially distributed and use sensors to monitor environmental conditions. Due to some of the diverse applications, such as healthcare monitoring, management of disasters, smartphones, military, and other systems of surveillance, deployment of sensor nodes is more which are independent and distributed in harsh environments. Clustering stabilizes the network and gives the maximum efficiency of energy where sensor nodes are grouped into clusters that give preservation of energy. The proposed work is mainly on a heterogeneous wireless sensor network (HWSN) which has various levels of energy developed to overcome some of the issues. Many protocols have been developed and designed for enhancing the performance of HWSN. The proposed work presents a model with the concept of Improved-Multiple Input Multiple Output (IMIMO) which provides secured routing against attacks. The research work is focused mainly on the detection and prevention of black hole attacks using an algorithm called Modified Back Propagation Neural Network (Modified-BPNN). Considering the previous research, the objective is to provide secure routing and increase network performance. The modified-BPNN algorithm reconstructs the network by eliminating the malicious nodes which disturb the network operation. The proposed algorithm works better for data transmission with secured routes and also network performance is achieved by expanding the MAC parameters. Throughput, Packet Delivery Ratio (PDR), Packet Loss, and Routing Overhead are evaluated using NS 2.35 simulator tool and compared with the existing Protocols such as DSR, AODV, and MAODV.

Prevention of Blackhole Attack in MANET using Certificate less Signature Scheme

Mobile AdHoc Networks (MANETs) are the network of self-configuring nodes. Such nodes communicate through single as well as multi-hop modes without the aid of any centralized administrator or pre-existing network infrastructure. Due to this reason, MANETs have gained a highly significance in modern wireless networking technologies. Such networks are extremely vulnerable to one of the security attack i.e. blackhole attack. It is a malicious node when an attacker is able to send a fake route reply to the originator of a route request packet. Such attackers discard the legitimate packets and replay packets in the whole network thereby adversely affecting network performance. Most of the security protocols for MANET are using bilinear pairing methods to provide security against security attacks and it takes high computing cost for the computation of pairing operations. Nowadays, researchers are using certificate-less signature schemes in distributed environments to provide efficient security. This signature scheme is very popular because it does not use any certificate authority for the management of security certificates. In this paper, we proposed an efficient technique to prevent blackhole attack in MANET using RSA-based certificateless signature scheme without using any bilinear pairing operations. Our scheme provides security against forgery and blackhole attacks and is evaluated under a discrete logarithm problem. Proposed scheme outperforms existing schemes in terms of these metrics viz., throughput, packet delivery ratio, routing overhead and end-to-end delay when we are varying mobility and fixed percentage of malicious nodes. Our proposed scheme not only detects or prevents the blackhole attack but it is also capable to provide important security services viz., integrity, authentication and non-repudiation.

An Efficient Dynamic Solution for the Detection and Prevention of Black Hole Attack in VANETs.

Rapid and tremendous advances in wireless technology, miniaturization, and Internet of things (IoT) technology have brought significant development to vehicular ad hoc networks (VANETs). VANETs and IoT together play a vital role in the current intelligent transport system (ITS). However, a VANET is highly vulnerable to various security attacks due to its highly dynamic, decentralized, open-access medium, and protocol-design-related concerns. Regarding security concerns, a black hole attack (BHA) is one such threat in which the control or data packets are dropped by the malicious vehicle, converting a safe path/link into a compromised one. Dropping data packets has a severe impact on a VANET’s performance and security and may cause road fatalities, accidents, and traffic jams. In this study, a novel solution called detection and prevention of a BHA (DPBHA) is proposed to secure and improve the overall security and performance of the VANETs by detecting BHA at an early stage of the route discovery process. The proposed solution is based on calculating a dynamic threshold value and generating a forged route request (RREQ) packet. The solution is implemented and evaluated in the NS-2 simulator and its performance and efficacy are compared with the benchmark schemes. The results showed that the proposed DPBHA outperformed the benchmark schemes in terms of increasing the packet delivery ratio (PDR) by 3.0%, increasing throughput by 6.15%, reducing the routing overhead by 3.69%, decreasing the end-to-end delay by 6.13%, and achieving a maximum detection rate of 94.66%.

Real Time Spatial Transmission Analysis Based Improved Black Hole Attack Detection In WSN For Improved QoS


 
 
 
 ABSTRACT
 Despite the extensive utilisation of Wireless Sensor Networks (WSNs), they remain vulnerable to various types of security breaches, including black hole attacks. The detection and prevention of black hole attacks are crucial for safeguarding the security and reliability of Wireless Sensor Networks (WSNs). The present study introduces a technique for real-time detection of black hole attacks in Wireless Sensor Networks (WSNs) by means of spatial transmission analysis, with the aim of enhancing Quality of Service (QoS). In order to enhance the identification of black hole attacks, we propose a methodology that leverages real-time spatial transmission analysis to quantify the Euclidean distance separating the source and destination nodes of every packet. An algorithm with a high detection rate and a low false positive rate was developed by us. In order to evaluate the efficacy of the proposed mechanism and establish a comparative analysis with existing methodologies, we conducted extensive experimentation. The results indicate that the proposed mechanism exhibits superior performance compared to existing techniques in terms of both detection rate and false positive rate. Our proposed mechanism aims to safeguard the quality of service of Wireless Sensor Networks (WSNs) against black hole attacks in real-time.
 
 
 

Detection and Prevention of Blackhole Attack in the AOMDV Routing Protocol

Mobile ad-hoc network is a collection of dynamically organized nodes where each node acts as a host and router. Mobile ad-hoc networks are characterized by the lack of preexisting infrastructures or centralized administration. So, they are vulnerable to several types of attacks, especially the Blackhole attack. This attack is one of the most serious attacks in this kind of mobile networks. In this type of attack, the malicious node sends a false answer indicating that it has the shortest path to the destination node by increasing the sequence number and decreasing the number of hops. This will have a significant negative impact on source nodes which send their data packets through the malicious node to the destination. This malicious node drop received data packets and absorbs all network traffic. In order overcome this problem, securing routing protocols become a very important requirement in mobile ad-hoc networks. Multipath routing protocols are among the protocols affected by the Blackhole attack. In this paper, we propose an effective and efficient technique that avoids misbehavior of Blackhole nodes and facilitates the discovery for the most reliable paths for the secure transmission of data packets between communicating nodes in the well-known Ad hoc On-demand multi-path routing protocol (AOMDV). We implement and simulate our proposed technique using the ns 2.35 simulator. We also compared on how the three routing protocols AOMDV, AOMDV under Blackhole attack (BHAOMDV), and the proposed solution to counter the Blackhole attack (IDSAOMDV) performs. The results show the degradation on how AOMDV under attack performs, it also presents similarities between normal AOMDV and the proposed solution by isolating misbehaving node which has resulted in increase the performance metrics to the standard values of the AOMDV protocol.

Black hole attack prevention scheme using a blockchain-block approach in SDN-enabled WSN

The success of software-defined networking (SDN) technology in the wired environment has accelerated the research on the deployment of SDN in wireless sensor networks (WSN). Since the wireless environment has a shared nature, it is more vulnerable to routing attacks. Most of the existing security protocols cannot be implemented for WSN, as the wireless environment has physical restrictions and the nodes in the network have limited energy, processing capacity, and memory. This paper investigates the possible threats in SDN-enabled WSN and analyses the black hole attack in detail. In the paper, we have also proposed a novel lightweight security model that exploits the blockchain-block approach to be able to protect the flow table in each node, which is the main target of possible routing attacks. We have generated an unchangeable fingerprint called the signature token for the flow entries with a secret key belonging to each node. Thanks to this token, not only have the flow entries been secured against tampering but also data packets have been transmitted securely along the path and secured against replay attacks and man-in-the-middle attacks. The results show that the proposed security model can be a promising solution for securing SDN-enabled WSN structures.

Black hole attack prevention scheme using a blockchain-block approach in SDN-enabled WSN

Black hole attack prevention scheme using a blockchain-block approach in SDN-enabled WSN

Secure co-operative neighbour-based approach for detection and prevention of black hole attack in wireless mobile ad-hoc networks

Mobile ad-hoc networks are infrastructure-less, temporary networks which are exposed to routing attacks. Black hole attack is a routing attack formed by dropping all the received packets by a malicious node. To ensure the security and strength of MANETs a secure and effective mechanism is obligatory. This paper presents Secure Cooperative Neighbour-Based Approach in AODV to perceive and circumvent the black hole attack from the start of the network. This approach enables every node to exchange information with its neighbour using a secure, efficient and quick detection process against routing attacks by taking an alternative route on finding an attacker. This approach is able to avoid the black hole nodes and improve the performance of the system as observed in the simulations under ns2.

Secure co-operative neighbour-based approach for detection and prevention of black hole attack in wireless mobile ad-hoc networks

Mobile ad-hoc networks are infrastructure-less, temporary networks which are exposed to routing attacks. Black hole attack is a routing attack formed by dropping all the received packets by a malicious node. To ensure the security and strength of MANETs a secure and effective mechanism is obligatory. This paper presents Secure Cooperative Neighbour-Based Approach in AODV to perceive and circumvent the black hole attack from the start of the network. This approach enables every node to exchange information with its neighbour using a secure, efficient and quick detection process against routing attacks by taking an alternative route on finding an attacker. This approach is able to avoid the black hole nodes and improve the performance of the system as observed in the simulations under ns2.

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

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.

DRI-Based Implementation for Detecting and Eliminating Cooperative Black Hole Nodes in MANET

Mobile Ad hoc Networks is configured by itself using the Mobile nodes in the Network, the maintenance also done by the wireless nodes itself. Dynamic topology, hop-to-hop communication and open-to-all are the features of MANETS, but these features made security of network highly challengeable. From security concern, routing protocols are highly vulnerable to many security threats like black hole attack. In black hole attack malicious node generates false routing information to the path requests about the route it asked for, which results all data packets forward toward it-self by the source and the black hole node manipulate its data. The cooperative black hole nodes in the other hand cooperate within the malicious nodes to fool the single black hole attack prevention algorithms. Here an approach is proposed to detecting the cooperative black holes nodes and eliminate them by broad casting there information into the network.

Detection and Prevention of Black Hole Attack in RPL Protocol Based on the Threshold Value of Nodes in the Internet of Things Networks

Due to the technology of IOT the human daily life services were became easier. With this technology the scalability will become very more to handle this kind of networks 6LOWPAN protocol was used, In this 6LOWPAn networks the RPL protocol was used to route the packets. The RPL protocol is constrain protocol particularly suits for the constrain node. Due to this constrain behavior this protocol may leads to many attacks. The attacks may be a black hole, wormhole, sinkhole etc. This paper was focused on Black hole attack. The black hole attack was simulated in the Contiki cooja simulator and proposed an detection approach based on the threshold value of each node in the network, to this black hole attack and the results was generated by using the contiki cooja simulator the results shows the effectiveness of the proposed technique in terms of the packet delivery rate, detection rate of attack.

Prevention of Black Hole Attacks in Virtualized Cloud Network Using Trust-Aware Energy Efficient AODV Routing With Firefly Based AI Technique

Cloud networks are very widespread and unreliable because of the amount of VMs and presented nodes in their Virtual Cloud Network. Nodes might connect and revoke networks at any time. Resilience is a advantage of cloud computing, but it has many safety issues in routing and transmitting information between messages. VCN research is very similar to the portable ad-hoc network (MANET), which depends on the collaboration of all involved nodes to provide fundamental activities. Many safety assaults and risks exploit the safety of information transmission due to the decentralized environment in VCN and MANET. Malicious nodes can interfere and use information during wireless communications. Numbers of methods are there that has a diverse effect on such attacks for malicious nodes. Varied attacks are susceptible to security, but Black hole assault is one of the most common effective assaults, as fraudulent nodes dump all incoming emails reducing network performance and reliability. A black hole node is designed to lampoon every node in the network that conveys with some other node by saying it always has the easiest route to the target node. In this manuscript, a secure routing discovery method has been presented using Ad hoc on demand distance vector (AODV) routing protocol. For the detection of attack in the cloud, the concept of Artificial Intelligence (AI) has been used. Therefore, in this research, Artificial Neural Network (ANN) and Support Vector Machine (SVM)is adapted to determine Packet Delivery Ratio (PDR), Delay and Throughput measures. The comparative examination has been conducted to depict the proposed FNN-AODV effectiveness. There is an enhancement of 61.01% in FNN-AODV and 5.08% enhancement in Throughput in proposed FNN-AODV than R-AODV, 6.26% enhancement in PDR for FNN-AODV than R-AODV and 10.8% is the decrement in delay in FNN-AODV than of R-AODV.

Prevention of Black Hole Attacks on Mobile Ad Hoc Networks Through Intrusion Detection Systems

In a mobile ad hoc network, a source node must rely on intermediate nodes to forward its packets along multi-hop routes to the destination node. The performance of a mobile ad hoc network is closely related to the capability of the implemented routing protocol to adapt itself to unpredictable changes of topology network and link status. One of these routing protocols is optimized link state routing protocol which assumes that all nodes are trusted. However, in a hostile environment, the OLSR is known to be vulnerable to various kinds of malicious attacks. Without having any control on packet forwarding, an intermediate node can behave selfishly or maliciously to drop packets going through it. Therefore, in this article, the authors propose a new technique for the selection of multipoint relays whose aims to provide each node the ability to select alternative paths in order to reach any destination two hops away.

An Efficient Scheme for Detection and Prevention of Black Hole Attacks in AODV-Based MANETs

Mobile ad hoc network (MANET) is a set of independent mobile nodes, which connect to each other over a wireless channel without any centralized infrastructure, nor integrated security. MANET is a weak target to many Denial of Service (DOS) attacks, which seriously harms its functionality and connectivity. A black hole attack is a type of DOS attack, where the malevolent node tries to get all the data packets from a source node by sending fabricated fake route reply (RREP) packet, falsely pretending that it possesses the shortest path towards the destination node, and then drops all the packets it receives. In this paper, the AODV (Ad-hoc on-demand distance vector) routing protocol is improved by incorporating an efficient and simple mechanism to mitigate black hole attacks. Mechanism to detect black hole attacks from MANET (MDBM) uses fake route request (RREQ) packets with an unreal destination address in order to detect black hole nodes prior to the actual routing process. Simulation experiment conducted has verified the performance of the proposed detection and prevention scheme. The results demonstrated that the proposed mechanism performed well in terms of Packet Delivery Ratio, End-to-End Delay and Throughput under black hole attack.

Preventing Black Hole Attack in Wireless Sensor Network Using HMM

Secure routing is a difficult task because of the limited nature of wireless sensor network resources. This paper provides a Hidden Markov Model solution to identify malicious nodes in wireless sensor networks through prevention of black hole attack. Our proposed approach based on a new routing algorithm which analyses shortest path in order to avoid malicious node path. Our results demonstrate the success and the efficiency of our proposed routing algorithm.

Black Hole Attack Prevention in Wireless Peer-to-Peer Networks: A New Strategy

Mobile peer-to-peer networking (MP2P) is a relatively new paradigm compared to other wireless network technologies. In the last 10–15 years, it has gained tremendous popularity because of its usefulness in applications such as file sharing over the Internet in a decentralized manner. Security of mobile P2P networks represents an open research topic and a main challenge regarding the vulnerability of these networks and their convenience to different security attacks such as black hole, Sybil, etc. In this work, we analyze the black hole attack in wireless P2P networks using the AODV as the routing protocol. In a black hole attack, a malicious node assumes the identity of a legitimate node, by creating forged answers with a higher sequence number, and thus forces the victim node to prioritize it as a relay node. We propose a solution based on a modification of the AODV routing protocol, taking into account the behavior of each node participating in the network. The performances of our proposal are evaluated by simulation.

Energy aware detection and prevention of black hole attack in MANET

Energy and security are the two vital components of Mobile Ad-hoc Networks (MANETs). During routing finding an optimal path from sender to receiver sense of path length (number of hops), longevity (battery life) and security becomes an essential requirement. Variety of schemes are proposed by the researchers for finding the shortest path along with energy saving and protecting from attacks Black-hole and gray-hole attacks are some of the most harmful attacks against MANET communication and needs attention. These attacks may cause by insider or outsider malicious node(s) who may drop packets or misroute the information during communication from sender node to receiver node. In our study we proposed an intelligent routing protocol based on Ant Colony Optimization (ACO) technique that finds shortest path from source to destination, applies the concept of power aware techniques to save energy increasing the longevity of the link avoiding link failure and also uses the concept of digital signatures, watchdog and path rater for detection and avoidance ofblack-hole and gray-hole attacks. Simulation study of the proposed scheme is made over some network parameters and found to be efficient in comparison to the basic AODV routing protocol.

Secured AODV Routing Protocol for the Detection and Prevention of Black Hole Attack in VANET

Vehicular ad hoc networks (VANETs) are becoming promising and popular technologies in the recent intelligent transportation world. They are used to provide an Intelligent Transportation System (ITS), efficient Traffic Information System (TIS), and Life Safety. The mobility of the vehicles and the volatile nature of the connections in the network have made VANET vulnerable to many security threats. Black hole attack is one of the security threat in which node presents itself in such a way to the other vehicles that it has the freshest and the shortest path to the destination. Hence in this research paper an efficient approach for the detection and prevention of the Black hole attack in the Vehicular Ad Hoc Networks (VANET) is presented. The proposed solution is implemented on AODV (Ad hoc On demand Distance Vector) routing protocol one of the most popular routing protocol for VANET. The proposed strategy can detect both the single and the Cooperative Black hole attacks in the early phase of route discovery. The simulation is carried on NS-2 and the results of the proposed scheme are compared to the fundamental DYMO routing protocol, this results are examined on various network performance metrics such as packet delivery ratio, throughput and end-to-end delay. The found results show the efficiency of the proposed method as the delivery ratio and end to end delay of the network does not deteriorate under a black hole attack.