Black Hole Attack Prevention Method Using Dynamic Threshold in Mobile Ad Hoc Networks

Noguchi, Taku; Yamamoto, Takakazu

doi:10.15439/2017f101

Cited by 6 publications

(4 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, hybrid methods that can restore normal nodes to the network by applying an opinion-based redecision mechanism have been developed as well. In a study employing this method, Noguchi et al [14] applied a dynamic sequence number threshold to RREP packets received by a node to determine whether the sender of the RREP packet is a black hole node. Other studies have aimed to establish secure routes without focusing on the behavior of black hole attacks or sequence numbers.…”

Section: Methods Of Defense Against Black Hole Attacksmentioning

confidence: 99%

Preventing Black Hole Attacks in AODV Using RREQ Packets

Nakano,

Matsuzawa

2023

Network

View full text Add to dashboard Cite

Ad hoc networks, formed by multiple wireless communication devices without any connection to wired or intermediary devices such as by access points, are widely used in various situations to construct flexible networks that are not restricted by communication facilities. Ad hoc networks can rarely use existing infrastructure, and no authentication infrastructure is included in these networks as a trusted third party. Hence, distinguishing between ordinary and malicious terminals can be challenging. As a result, black hole attacks are among the most serious security threats to Ad hoc On-demand Distance Vector (AODV) routing, which is one of the most popular routing protocols in mobile ad hoc networks. In this study, we propose a defense method against black hole attacks in which malicious nodes are actively detected to prevent attacks. We applied the proposed method to a network containing nodes engaging in black hole attacks, confirming that the network’s performance is dramatically improved compared to a network without the proposed method.

show abstract

Section: Methods Of Defense Against Black Hole Attacksmentioning

confidence: 99%

Preventing Black Hole Attacks in AODV Using RREQ Packets

Nakano,

Matsuzawa

2023

Network

View full text Add to dashboard Cite

show abstract

“…A black hole (BH) is a type of denial of service (DoS) attack that discards or eavesdrops on data packets that are sent from a source node to a destination node [11,20]. The BH node catches an RREQ and returns an RREP with a spoofed sequence number to the source node, thereby constructing a communication path that includes the BH node.…”

Section: Blackhole Attackmentioning

confidence: 99%

“…We implemented a smart BH attack and a defense method against this attack. In addition to the defense method proposed in this study, we also evaluated and compared a BH-attack prevention method using a dynamic threshold in MANETs [11]. This method classifies nodes as either normal or BH using a dynamically updated sequence number threshold.…”

Section: Simulation Environmentmentioning

confidence: 99%

Collaborative Defense Techniques Against MANETs Malicious Nodes

Terai

Yoshida

Ramonet

et al. 2021

IJNC

Self Cite

View full text Add to dashboard Cite

Blackhole (BH) attacks are among the most significant threats in mobile ad-hoc networks. A BH is a security attack in which a malicious node absorbs data packets and sends fake routing information to neighboring nodes. BH attacks have been widely studied. However, existing defense methods wrongfully assume that BH attacks cannot overcome the most common defense approaches. A new wave of BH attacks is known as smart BH attacks. In this study, we used a highly aggressive type of BH attack that can predict sequence numbers to overcome traditional detection methods that set a threshold to sequence numbers. To protect the network from this type of BH attack, we propose a collaborative defense method that uses local information collected from neighboring nodes. We evaluated the performance of our defense method against a smart BH attack and a collaborative attack that uses the collaboration of another malicious node. Our results show that the proposed method successfully detects and contains these threats to some degree. Consequently, the smart BH attack success rate decreases.

show abstract

“…The BN tracking node responds to the dummy RREP and broadcasts a block message in the network so that real nodes can use it to isolate black hole nodes. Noguchi and Yamamoto [7] proposed a dynamic threshold-based method with the support route request (RREQ) dummy approach to maximize the true detection rate and minimize the false detection rate of blackhole attack. The threshold value identifies a black hole node, and the RREQ dummy prejudges the black hole node in advance before permanently deleting it from the blacklist table.…”

Section: Introductionmentioning

confidence: 99%

A Blackhole Attack Mitigation Algorithm in MANET based on Standard Deviation Outlier Detection

Clemence

Xuan

Younis

2020

Wseas Transactions on Computers

View full text Add to dashboard Cite

A mobile ad hoc network (MANET) performs a routing and data forwarding obligations in a trustless environment where mobile nodes are not controlled and administered by third parties, it usually suffers from multiple attacks such as the blackhole attacks. This blackhole attacks cause two extreme effects on the network if the malicious nodes are not eliminated. Firstly, it deliberately alters the original data route sequence with an injection of false routing information comprises of the counterfeit destination sequence number and smallest hop count. Secondly, it becomes too greedy to send data to other nodes after receiving from a genuine node. Therefore, this may delay the data transmission process in the act of data dropping. To protect the routing discovery process of an ad hoc on-demand distance vector (AODV) protocol from the blackhole attack, we present a mitigation algorithm based on standard deviation outlier detection to determine a threshold value for validating the route reply (RREP) destination sequence number before route establishment. The simulation shows that the algorithm can detect the malicious nodes and performs better than AODV in a blackhole attack environment.

show abstract

Black Hole Attack Prevention Method Using Dynamic Threshold in Mobile Ad Hoc Networks

Cited by 6 publications

References 8 publications

Preventing Black Hole Attacks in AODV Using RREQ Packets

Preventing Black Hole Attacks in AODV Using RREQ Packets

Collaborative Defense Techniques Against MANETs Malicious Nodes

A Blackhole Attack Mitigation Algorithm in MANET based on Standard Deviation Outlier Detection

Contact Info

Product

Resources

About