“…If the attacker uses a small CW value, it can preempt the channel and prevent others from accessing the channel with a high probability [2]. Cross-layer attacks in other types of wireless networks have been reported in the literature [15][16][17][18][19][20]. Some of these cross-layer attacks achieve similar goals as the attack described in this paper, but because of the nature of these networks, they do not have to consider the effect of the spectrum.…”
Section: Related Work 21 Security Attacks In Crsmentioning
confidence: 83%
“…From the graph, a higher connectivity is observed with the set of PRPs that are prime. For example consider PRP numbers set1, (2,3,5,7,11,13,17). All of them are prime numbers.…”
Section: Figure 6 Key Connectivity With Different Set Of Rpn Numbersmentioning
confidence: 99%
“…Node-Id with their keys and common keysThe alternative path goes through nodes20,14,15,16,17,18, 44 and 45. Here source node 20 communicates with node 14 through common key (0), node 14 communicates with node 15 through key (0), node 15 communicates with node 16 through key (1), node 16 communicates with node 17 through key…”
Existing research on attacks and security issues in Cognitive Radio networks focus on individual network layers. In this paper, we identify a cross-layer attack, which we call the MAC-TCP Crosslayer attack. This attack is launched from the MAC layer as the point of attack but the final target is to degrade TCP layer end to end throughput of flows by exploiting the TCP congestion control mechanism in cognitive radio. The chances of the attacker being detected are low owing to the fact that the target layer is different from the layer where the attack is launched. An adversary launches an attack on the MAC layer causing large variations in Round Trip Time (RTT) resulting in a large drop in throughput of TCP flows (drop of around 40% from our simulation results) but has little effect on the MAC-layer throughput and hence is very difficult to detect. A defense for this attack is proposed using a deterministic key pre-distribution algorithm where the keys are pre-distributed to nodes. Simulation results show that the throughput is restored to its original levels using key pre-distribution.
“…If the attacker uses a small CW value, it can preempt the channel and prevent others from accessing the channel with a high probability [2]. Cross-layer attacks in other types of wireless networks have been reported in the literature [15][16][17][18][19][20]. Some of these cross-layer attacks achieve similar goals as the attack described in this paper, but because of the nature of these networks, they do not have to consider the effect of the spectrum.…”
Section: Related Work 21 Security Attacks In Crsmentioning
confidence: 83%
“…From the graph, a higher connectivity is observed with the set of PRPs that are prime. For example consider PRP numbers set1, (2,3,5,7,11,13,17). All of them are prime numbers.…”
Section: Figure 6 Key Connectivity With Different Set Of Rpn Numbersmentioning
confidence: 99%
“…Node-Id with their keys and common keysThe alternative path goes through nodes20,14,15,16,17,18, 44 and 45. Here source node 20 communicates with node 14 through common key (0), node 14 communicates with node 15 through key (0), node 15 communicates with node 16 through key (1), node 16 communicates with node 17 through key…”
Existing research on attacks and security issues in Cognitive Radio networks focus on individual network layers. In this paper, we identify a cross-layer attack, which we call the MAC-TCP Crosslayer attack. This attack is launched from the MAC layer as the point of attack but the final target is to degrade TCP layer end to end throughput of flows by exploiting the TCP congestion control mechanism in cognitive radio. The chances of the attacker being detected are low owing to the fact that the target layer is different from the layer where the attack is launched. An adversary launches an attack on the MAC layer causing large variations in Round Trip Time (RTT) resulting in a large drop in throughput of TCP flows (drop of around 40% from our simulation results) but has little effect on the MAC-layer throughput and hence is very difficult to detect. A defense for this attack is proposed using a deterministic key pre-distribution algorithm where the keys are pre-distributed to nodes. Simulation results show that the throughput is restored to its original levels using key pre-distribution.
“…The earlier works on design of cross-layer security solutions were presented in [41]- [44]. In [41], author contend that a foe can together utilize impact on connection layer, parcel dropping and disarray on the network layer to performance out a Denial of Service (DoS) attack.…”
Nowadays Internet of Things (IoT) is emerging and effective technology along with Wireless Sensor Networks (WSNs) in a few constant applications in which the human intervention significantly reduced along with better human life. In IoT enabled WSNs, the sensor nodes used to assemble the fragile data and communicate towards the sink hub and actuators for automotive remote monitoring process. However as the WSNs operating at free frequency band, it is powerless against different attacks at various layers of WSNs protocol stack in which attackers may try to hack and compromise the user’s personal information. There are different types of attacks in WSNs and several research works conducted to protect from these attacks in WSNs. Majority of security methods proposed are based layered technique. However, the layer approach is not enough to protect the WSNs effectively as the many attackers used the cross-layer information to perform the attacks. This paper presents the study over the layered security solutions and their research problems at first to justify the importance of cross-layer solutions. The review of different ways of designing the cross-layer security techniques for WSNs with their behaviour presented as well. The challenges of IoT enabled WSNs single layered security solutions presented and then the various cross-layer solutions reviewed in this paper. The comparative study of different cross-layer techniques to demonstrate the layers and their parameters involved to detect of security threats. The outcome of this review work is the research challenges noticed from the present cross-layer solutions.
“…Vincent Toubiana et al [6] introduced a type of cross-layer attack that is usually applied against MANET cooperation enforcement tools. This kind of attack depends on CSMA/CA model with an intention of leaking information about the possible easy targets.…”
Section: Cross-layer Attack Against the Manet Co-operation Enforcemenmentioning
A Mobile ad hoc network (MANET) is a self-configuring network that has no infrastructure. Each device in a MANET is free to move independently in any direction and will therefore change its links to other devices frequently. It is an emerging technology that has the potential to be applied in applications like battlefields and also in many commercial applications. With great features MANET also has some limitations like unreliability of wireless links, constantly changing topologies and more. Due to this vulnerable nature of MANET, they are exposed to various security threats that cause problems in using them. The attackers takes advantage of these vulnerabilities to launch various kinds of security attacks on MANETs. Among the security attacks, the attack of most concern is Cross-layer attack that initializes at MAC layer and launches attack on routing layer which causes serious degradation in network performance. This attack emerges from lack of interaction between MAC and routing layer. In this paper, we focus on surveying various Cross-layer attacks that were discovered till now and their defense systems. Finally we highlight what could be done in future to improve the defense systems.
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