Reputation based malicious node detection in OppNets
01 Jan 2016-pp 1-6
TL;DR: In this paper, a node by node packet dropping detection mechanism is developed using the Merkle tree hashing technique to build trust and reputation for nodes, which is then used to detect malicious nodes.
Abstract: Routing and security management in Opportunistic Networks is challenging, where effective and secure forwarding of data delivery without any loss is not easy to guarantee. Packet dropping attacks are one of the most popular attacks that OppNets are exposed to. This paper presents an efficient malicious path, malicious node, and a packet dropping detection technique against selective packet dropping attacks. In our technique, we have developed a node by node packet dropping detection mechanism using the Merkle tree hashing technique. The result of detection is used to build trust and reputation for nodes, which are then used to detect malicious nodes. Simulation results show that the technique efficiently detects malicious paths, malicious nodes, and dropped packets. The results also show that with the increase of simulation time, node detection accuracy also increases as nodes have more time to establish reputation among nodes in the network. Results also show that the packet dropping rate drops over time, thus improving routing in OppNets.
Citations
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TL;DR: Delays Tolerant Networks are type of Intermittently Connected Networks featured by long delay, intermittent connectivity, asymmetric data rates and high error rates, and a review of misbehaving node attacks, and detection algorithms is presented.
28 citations
TL;DR: Opportunistic Networks as discussed by the authors is a new concept that is increasingly gaining ground since it appears as a concrete example of the Internet of Things, Internet of Vehicles, Industrial IoT, and the IoT with Mobile ad hoc Networks' characteristics.
Abstract: Opportunistic Networks is a new concept that is increasingly gaining ground since it appears as a concrete example of the Internet of Things, Internet of Vehicles, Industrial Internet of Things, and the Internet of Everything with Mobile ad hoc Networks’ characteristics. An Opportunistic Network starts with a Seed OppNet that sets up the network; expands from the Seed OppNet to an extended Seed OppNet through devices’ discovery. The characteristics of Opportunistic Networks make OppNets more challenging than any other networks. So, a deep understanding of OppNets’ characteristics and demands is an unavoidable precondition before proposing any OppNets related scheme. However, under OppNets’ constraints, the relevance of the Opportunistic Networks related articles in literature is yet to be established. Also, most surveys tackling Opportunistic Networks do not give a complete insight into what Opportunistic Networks stand for. This work reviews state of the art on Opportunistic Networks providing three main contributions. First, resorting to the primary definition of Opportunistic Networks, it elucidates what OppNets are, pointing out the particularities of an OppNet, its domains of applications, and challenges. Second, it provides a comprehensive review that encompasses most Opportunistic Networks’ research areas: routing, intrusion detection, authentication, privacy protection, data aggregation, and the technology for OppNets, organising them in a taxonomy. Third, it evaluates the role of the Seed OppNet in Opportunistic Networks related schemes. Any proposed OppNets related scheme, to be relevant to OppNets’ research, should include OppNets’ characteristics and demands.
10 citations
21 May 2021
TL;DR: This research work is identifying the location of malicious node using Stack based approach using Cooja simulator and simulation results shows the efficiency of the approach.
Abstract: -Security is the main concern in wireless sensor network. Attack can be occurred in different ways in WSN depending upon the types of malicious activity through this research work we are identifying the location of malicious node using Stack based approach. Cooja simulator is used to implement the RPL attack and considering the Average Power Consumption as a bench mark for identifying the malicious activity. We have verified the impact of the attack by varying the number of malicious node and the network size. The Stack based approach for finding the location is novel one and simulation results shows the efficiency of the approach.
4 citations
Cites background or methods from "Reputation based malicious node det..."
...Case 4: In this case we have set up the network size to 11, having ten sensor nodes (yellow in color) and one sink node (green in color) shows in Figure [4] and measured the power consumption of each node that shows in Figure [5] Fig....
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...Figure [3] shows the graph of the number of packets received per node based on the size of the malicious node....
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...Case 4: In this case we have set up the network size to 11, having ten sensor nodes (yellow in color) and one sink node (green in color) shows in Figure [4] and measured the power consumption of each node that shows in Figure [5]...
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...The network set up and power consumed per node shows in Figure[6] and Figure[7]...
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...Against selective packet dropping attacks, an effective technique is introduced for the detection of the malicious path, malicious node, and packet dropping [5]....
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01 Aug 2017
TL;DR: A Trust-based Routing Protocol (TRP) is designed, combined with various utility algorithms, to more comprehensively evaluate the competency of a candidate node and effectively reduce negative effects by malicious nodes.
Abstract: It is hard to set up an end-to-end connection between source and destination in Opportunistic Networks, due to dynamic network topology and the lack of infrastructure. Instead, the store-carry-forward mechanism is used to achieve communication. Namely, communication in Opportunistic Networks relies on the cooperation among nodes. Correspondingly, Opportunistic Networks have some issues like long delays, packet loss and so on, which lead to many challenges in Opportunistic Networks. However, malicious nodes do not follow the routing rules, or refuse to cooperate with benign nodes. Some misbehaviors like black-hole attack, gray-hole attack may arbitrarily bloat their delivery competency to intercept and drop data. Selfishness in Opportunistic Networks will also drop some data from other nodes. These misbehaviors will seriously affect network performance like the delivery success ratio. In this paper, we design a Trust-based Routing Protocol (TRP), combined with various utility algorithms, to more comprehensively evaluate the competency of a candidate node and effectively reduce negative effects by malicious nodes. In simulation, we compare TRP with other protocols, and shows that our protocol is effective for misbehaviors.
1 citations
Cites background from "Reputation based malicious node det..."
...One is to mitigate the negative effect of malicious nodes like [2][3][5][6][7][8], and the other is to detect malicious nodes in networks like [9][10][11][12]....
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TL;DR: In this paper , the authors present a novel algorithm to detect/mitigate fake-packet and selective packet drops attacks in DTNs using Merkle-Hash-Tree.
Abstract: Delay/Disruption Tolerant Networks (DTNs) are a special category of IntermittentlyConnectedNetworks (ICNs). It has features such as long-delay, frequent-disruption, asymmetrical-data-rates, and high-bundle-error-rates. DTNs have been mainly developed for planet-to-planet networks, commonly known as Inter-Planetary-Networks (IPNs). However, DTNs have shown undimmed potency in challenged communication networks, such as DakNet, ZebraNet, KioskNet and WiderNet. Due to unique characteristics (Intermittent-connectivity and long-delay) DTNs face tough/several challenges in various research areas i.e bundle-forwarding, key-distribution, privacy, bundle-fragmentation, and malicious/selfish nodes particularly. Malicious/selfish nodes launch various catastrophic attacks, this includes, fake packet attacks, selective packet drops attacks, and denial-of-service/flood attacks. These attacks inevitably consume limited resources (persistent-buffer and bandwidth) in DTNs. Fake-packet and selective-packet-drops attacks are top among the challenging attacks in ICNs. The focus of this article is on critical analyses of fake-packet and selective-packet-drops attacks. The panoramic view on misbehavior nodes mitigation algorithms are analyzed, and evaluated mathematically through several parameters for detection probability/accuracy. This article presents a novel algorithm to detects/mitigates fake-packet and selective-packet-drops attacks. The proposed algorithm uses Merkle-Hash-Tree to detects the aforementioned attacks. The proposed algorithm added root hash along with all packets, when the malicious nodes drop packets or inject fake packets, the algorithm detects malicious nodes. Moreover, trace-driven simulation results show the proposed algorithm of this article accurately (enhanced detection-accuracy, enhanced packet delivery/packet loss ratios, and reduces false-positive/false-negative rates) detects malicious nodes which launch fake-packet and selective-packet-drops attacks, unlike previously proposed algorithms which detect only one attack (fake-packet or packet-drops at a time) or detect only malicious path (do not exactly detect malicious nodes which launch attacks). Furthermore, this article mathematically analyzed various scenarios to track exactly/position of various vehicular nodes.
References
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TL;DR: Several protocols for public key distribution and for digital signatures are briefly compared with each other and with the conventional alternative.
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TL;DR: This work proposes two complementary approaches for social trust establishment: explicit social trust and implicit social trust that are more robust against manipulation attacks compared to state-of-the-art approaches such as PGP- like certification chains and distributed community detection algorithms.
Abstract: Opportunistic networks enable mobile users to participate in various social interactions with applications such as content distribution and micro-blogs. Because of their distributed nature, securing user interactions relies rather on trust than hard cryptography. Trust is often based on past user interactions such as in reputation systems relying on ratings. Yet, a more fundamental trust, social trust - assessing a user is genuine with honest intentions - must be established beforehand as many identities can be created easily (i.e., sybils). By leveraging the social network structure and its dynamics (conscious secure pairing and wireless contacts), we propose two complementary approaches for social trust establishment: explicit social trust and implicit social trust. Complexity, trust propagation and security issues are evaluated using real world complex graphs, synthetic mobility models and mobility traces. We show how our approach limits the maximum number of sybils independently of the network size and is more robust against manipulation attacks compared to state-of-the-art approaches such as PGP- like certification chains and distributed community detection algorithms.
118 citations
"Reputation based malicious node det..." refers methods in this paper
...The main contributions of this paper are: 1) An algorithm to detect selective packet dropping attacks using the Merkle tree hashing technique, where half of the Merkle tree hashes are used to authenticate the number of packets received....
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01 Jun 2013
TL;DR: A trust-based framework to more accurately evaluate an encounter's delivery competency is designed, which can be flexibly integrated with a large family of existing data forwarding protocols designed for OppNets.
Abstract: In general, the encounter probability is leveraged to evaluate whether a node is a qualified next-hop forwarder in Opportunistic Networks (OppNets); however, it does not truly present the node's competency of delivering data in a hostile wireless environment, because a malicious node can arbitrarily bloat that probability to intercept data from others. In this paper, we design a trust-based framework to more accurately evaluate an encounter's delivery competency, which can be flexibly integrated with a large family of existing data forwarding protocols designed for OppNets. As a case study, we integrate our proposed framework with PROPHET, and demonstrate its effectiveness against ''black hole'' attacks through experimental study.
105 citations
01 Oct 2013
TL;DR: A Trust-based Security Protocol (TSP) is proposed to secure Oppnets against blackhole attacks and simulation results are provided to support the effectiveness of the proposed TSP approach.
Abstract: Opportunistic networks (Oppnets) are a kind of wireless networks that provide the opportunity to have social interaction and obtain data that can be used for message passing decision. The increase observed in the number of people with PDAs and other handset devices equipped with wireless technologies makes the forwarding paradigm and Oppnets scenarios more interesting and challenging. The main challenge in Oppnets is to take efficient routing decisions on securing the delivery of messages to the destination. Cooperation and trust between nodes in the network saves them from malicious attacks. The trust of a node is a basic value that symbolizes the magnitude of its social responsibility in the network, which include helping groups of nodes in message delivery, saving these nodes from malicious attacks, just to name a few. This paper focuses on blackhole attack against the PRoPHET routing protocol for Oppnets. A Trust-based Security Protocol (TSP) is proposed to secure Oppnets against blackhole attacks. Simulation results are provided to support the effectiveness of our proposed TSP approach, in the sense that considerable control is observed in the number of dropped packets, number of messages captured bythe malicious nodes (so-called malicious count) and overhead ratio.
33 citations
"Reputation based malicious node det..." refers methods in this paper
...The main contributions of this paper are: 1) An algorithm to detect selective packet dropping attacks using the Merkle tree hashing technique, where half of the Merkle tree hashes are used to authenticate the number of packets received....
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TL;DR: Trust-Based Spreading (TBS) is proposed - a scheme where trusted nodes collaborate and filter spam by opportunistically exchanging assessments to promote or block the spreading of content.
23 citations
"Reputation based malicious node det..." refers methods in this paper
...In this paper, we aim to establish trust relationships in OppNets by using a detection method to detect packet dropping attacks....
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