Multi-layer and Clustering based Security Implementation for an IoT Environment

IoT devices are having many constraints related to computation power and memory etc. Many existing cryptographic algorithms of security could not work with IoT devices because of these constraints. Since the sensors are used in large amount to collect the relevant data in an IoT environment, and different sensor devices transmit these data as useful information, the first thing needs to be secure is the identity of devices. The second most important thing is the reliable information transmission between a sensor node and a sink node. While designing the cryptographic method in the IoT environment, programmers need to keep in mind the power limitation of the constraint devices. Mutual authentication between devices and encryption-decryption of messages need some sort of secure key. In the proposed cryptographic environment, there will be a hierarchical clustering, and devices will get registered by the authentication center at the time they enter the cluster. The devices will get mutually authenticated before initiating any conversation and will have to follow the public key protocol.

Nonuniform Clustering of Wireless Sensor Network Node Positioning Anomaly Detection and Calibration

In order to detect and correct node localization anomalies in wireless sensor networks, a hierarchical nonuniform clustering algorithm is proposed. This paper designs a centroid iterative maximum likelihood estimation location algorithm based on nonuniformity analysis, selects the nonuniformity analysis algorithm, gives the flowchart of node location algorithm, and simulates the distribution of nodes with MATLAB. Firstly, the algorithm divides the nodes in the network into different network levels according to the number of hops required to reach the sink node. According to the average residual energy of nodes in each layer, the sink node selects the nodes with higher residual energy in each layer of the network as candidate cluster heads and selects a certain number of nodes with lower residual energy as additional candidate cluster heads. Then, at each level, the candidate cluster heads are elected to produce the final cluster heads. Finally, by controlling the communication range between cluster head and cluster members, clusters of different sizes are formed, and clusters at the level closer to the sink node have a smaller scale. By simulating the improved centroid iterative algorithm, the values of the optimal iteration parameters α and η are obtained. Based on the analysis of the positioning errors of the improved centroid iterative algorithm and the maximum likelihood estimation algorithm, the value of the algorithm conversion factor is selected. Aiming at the problem of abnormal nodes that may occur in the process of ranging, a hybrid node location algorithm is further proposed. The algorithm uses the ℓ 2 , 1 norm to smooth the structured anomalies in the ranging information and realizes accurate positioning while detecting node anomalies. Experimental results show that the algorithm can accurately determine the uniformity of distribution, achieve good positioning effect in complex environment, and detect abnormal nodes well. In this paper, the hybrid node location algorithm is extended to the node location problem in large-scale scenes, and a good location effect is achieved.

Strategies for Enhancing the Performance of (RPL) Protocol

Wireless sensor networks have many limitations such as power, bandwidth, and memory, which make the routing process very complicated. In this research, a wireless sensor network containing three moving sink nodes is studied according to four network scenarios. These scenarios differ in the number of sensor nodes in the network. The RPL (Routing Protocol for low power and lossy network) protocol was chosen as the actual routing protocol for the network based on some routing standards by using the Wsnet emulator. This research aims to increase the life of the network by varying the number of nodes forming it. By using different primitive energy of these nodes, this gives the network to continue working for the longest possible period with low and fair energy consumption between the nodes. In this work, the protocol was modified to make the sink node move to a specific node according to the node’s weight, which depends on the number of neighbors of this node, the number of hops from this node to the sink node, the remaining energy in this node, and the number of packets generated in this node. The simulation process of the RPL protocol showed good results and lower energy consumption compared to previous researches.

Effective Aggregate Data Collection and Enhanced Network Lifetime Using Energy Efficient Aggregation Data Convening Routing in Wireless Sensor Network

A wireless sensor network is a network system that uses wireless sensor nodes to monitor physical or environmental conditions as voice, temperature, and spatial dispersive movements. Each node can locally sense its environment, process information and data and send the data to one or more collection points within the WSN. In the existing solution categorized into member nodes and group/cluster heads(CH). The CH election process increases the overhead of the network and reduce the network lifetime. The processing and energy limitations of the nodes are considered for the CH election process. In this cluster formation methods aiming at Cluster head selection process and providing trust in hierarchical WSN are proposed. In this Energy Efficient Aggregation Data Convening Routing (E2ADCR) to estimate the routing path, and aggregate data collection to improve the network lifetime. The major advantage of this technique is to avoid the malicious or selfish node from becoming a dominant cluster in a group of clusters. Initially sink node selection is forward the Configuration Message (CM) to every node on network to construct the performing node. In this, cluster selection based on connection density, degree of the node angle, and residual energy (Quality Factor) that is evaluated from the link robustness, energy and degree of the node. Multi hop link transmission support path optimization technique is estimated in the path when the obstacle is present in the WSN. To introduce an Aggregated Support based Data Collection for evaluate each packet flow monitor on the network if any unrelated packet that will eliminate to forward to sink node. The new routing protocols, which were developed during this research, have better energy efficiency. The proposed routing path of the computational simplicity is achieved by a simple method.

Flow Increment through Network Expansion

The network expansion problem is a very important practical optimization problem when there is a need to increment the flow through an existing network of transportation, electricity, water, gas, etc. In this problem, the flow augmentation can be achieved either by increasing the capacities on the existing arcs, or by adding new arcs to the network. Both operations are coming with an expansion cost. In this paper, the problem of finding the minimum network expansion cost so that the modified network can transport a given amount of flow from the source node to the sink node is studied. A strongly polynomial algorithm is deduced to solve the problem.

Distributed partition detection and recovery using UAV in wireless sensor and actor networks

Wireless Sensor and Actor Networks (WSANs) have been extensively employed in various domains ranging from elementary data collection to real-time control and monitoring for critical applications. Network connectivity is a vital robustness measure for overall network performance. Different network functions such as routing, scheduling, and QoS provisioning depends on network connectivity. The failure of articulation points in the network disassociates the network into disjoint segments. We proposed Distributed Partition Detection and Recovery using Unmanned Aerial Vehicle (UAV) (DPDRU) algorithm, as an optimal solution to recover the partitioned network. It consists of three steps: Initialization, Operational and Detection, and Recovery. In the Initialization phase sink node collects all the information about the network. In the Operational and Detection phase, network nodes communicate regularly by exchanging HEARTBEATS, detects failure if some nodes do not get a message from the neighbor node and send failure reports, and sink node identifies network partition. In the recovery phase, the sink node sends UAV at the positional coordinates of the failed node and examines network recovery after UAV reaches the desired location. Our approach primarily focuses on reducing message overhead by sending few update messages to sink node and energy consumption by engaging network nodes only for communication. The requirements of the recovery process (physical movement and communication) are fulfilled by UAV. The algorithm is tested according to the following parameters: Detection Time, Recovery Time, message overhead, and distance traveled by UAV. Simulation results validate the efficacy of the proposed algorithm based on these parameters to provide reliable results. The minimum and the maximum number of messages transmitted are 11 for 10 nodes and 24 for 100 nodes respectively. Hence these results demonstrate that the message overhead in our proposed solution is less as compared to other techniques when the number of nodes increases.

Challenges in Sinkhole Attack Detection in Wireless Sensor Network

Wireless sensor networks (WSN’s) comprise limited energy small sensor nodes having the ability to monitor the physical conditions and communicate information among the various nodes without requiring any physical medium. Over the last few years, with the rapid advancements in information technology, there has been an increasing interest of various organizations in making the use of wireless sensor networks (WSN’s). The sensor nodes in WSN having limited energy detects an event, collect data and forward this collected data to the base node, called sink node, for further processing and assessment. Few attributes of WSN’s like the energy consumption and lifetime can be impacted by the design and placement of the Sink node. Despite various useful characteristics WSN’s is being considered vulnerable and unprotected. There is a large class of various security attacks that may affect the performance of the system among which sinkhole an adversary attack puts dreadful threats to the security of such networks. Out of various attacks, a sinkhole attack is one of the detrimental types of attacks that brings a compromised node or fabricated node in the network which keeps trying to lures network traffic by advertising its wrong and fake routing update. Sinkhole attacks may have some other serious harmful impacts to exploit the network by launching few other attacks. Some of these attacks are forwarding attacks, selective acknowledge spoofing attacks, and they may drop or modify routing information too. It can also be used to send fake or false information to the base station. This study is analyzing the challenges with sinkhole attacks and exploring the existing available solutions by surveying comparatively which used to detect and mitigate sinkhole attacks in the wireless sensor network.

Challenges in Sinkhole Attack Detection in Wireless Sensor Network

Wireless sensor networks (WSN’s) comprise limited energy small sensor nodes having the ability to monitor the physical conditions and communicate information among the various nodes without requiring any physical medium. Over the last few years, with the rapid advancements in information technology, there has been an increasing interest of various organizations in making the use of wireless sensor networks (WSN’s). The sensor nodes in WSN having limited energy detects an event, collect data and forward this collected data to the base node, called sink node, for further processing and assessment. Few attributes of WSN’s like the energy consumption and lifetime can be impacted by the design and placement of the Sink node. Despite various useful characteristics WSN’s is being considered vulnerable and unprotected. There is a large class of various security attacks that may affect the performance of the system among which sinkhole an adversary attack puts dreadful threats to the security of such networks. Out of various attacks, a sinkhole attack is one of the detrimental types of attacks that brings a compromised node or fabricated node in the network which keeps trying to lures network traffic by advertising its wrong and fake routing update. Sinkhole attacks may have some other serious harmful impacts to exploit the network by launching few other attacks. Some of these attacks are forwarding attacks, selective acknowledge spoofing attacks, and they may drop or modify routing information too. It can also be used to send fake or false information to the base station. This study is analyzing the challenges with sinkhole attacks and exploring the existing available solutions by surveying comparatively which used to detect and mitigate sinkhole attacks in the wireless sensor network.