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PurposeThe purpose of the paper is to analyze the layer wise security issues in IoT and to obtain the effective security mechanism for jamming attack .Design/methodology/approachIn this study, the authors proposed a multi layer security approach for the detection of DDoS in IoT environment, which protects the smart devices from DDoS, this scheme also reduces the computational cost in the network under mobility condition.FindingsEven though many works have been done for the security of wireless sensor network (WSN), all works have focused on encryption which depends on the key management strategy. In this study, the authors proposed a multilayer approach to analyze the layer wise security issues and also proposed a threshold-based countermeasure (TBC) for replay attack in each layer.Originality/valueThe results indicate that the proposed algorithm lowers the computational costs and energy consumption than in modern schemes. Also, the proposed research work improves the scalability of sensor networks using the TBC.

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A Mobile Ad-Hoc Network (MANET) is a arrangement of wireless mobile nodes which forms a temporary network for the communication without the access point, high availability of wireless devices in everyday is a measure factor in the success of infrastructure-less networks. MANET is dealing with both kinds of attacks, active and passive attacks at all the layers of network model. The lack in security measures of their routing protocols is alluring a number of attackers to intrude the network. A particular type of attack; known as Wormhole, which is launched by creation of tunnels and it results in complete disruption of routing paths on MANET. This paper presents a technique NWLID: Normalized Wormhole Local Intrusion detection Algorithm which is the modified version of Local Intrusion Detection Routing Security over mobile adhoc Network which has an intermediate neighbor node discovery mechanism, packet drop calculator, individual node receiving packet estimator followed by isolation technique for the confirmed Wormhole nodes . Result shows the effect of wormhole attack on normal behavior and improvement of performance after the application of proposed scheme. The effectiveness of NWLID algorithm is evaluated using ns2 network simulator.

IoT Consist of interrelated devices such as digital devices, mechanical devices, computer system, sensors, etc. for transceiving the information over the network. The scalability is essential to enhance the energy utilization and the performance of the environment, while mobility enhances the coverage of the system. Key management is vital for encrypted information transmitted over the network. Although many key management techniques are available, still it is a challenging issue concerning energy and computational cost, so robust key management technique is required that guarantees the required security requirements. In this paper, we proposed a cognitive key management technique (CKMT). The CKMT mechanism is helpful for key management and maintenance in a cluster-based mobile environment that reduces the rekeying process which is required for the mobile node when it enters the new location area, thereby reducing the computational overhead and enhances the scalability to large size network which makes our scheme more robust because strong key management technique is important while providing security services. Initially, we form a cluster, then Cluster-Head (CH) will be elected, it's a coordinator node that acts as a key manager. We also made an assumption that the sensors and Cluster-Heads are mobile, they can be able to shift from one position to another. This CH oversees and keeps up the private keys of sensors. When CH changes its location, it will hand over its responsibilities to the other CH in the network for uninterrupted communication. Our scheme uses local keys and foreign keys for each node and pairwise key is used only for the common nodes among the cluster so our scheme reduces the computational cost in the network under mobility condition. The results show that our proposed algorithm lowers the overhead in terms of computational costs, energy consumption, and delay.