Pinki Sharma

Bio: Pinki Sharma is an academic researcher. The author has contributed to research in topics: Wireless sensor network & Physical layer. The author has an hindex of 1, co-authored 3 publications receiving 24 citations.

Security issues in wireless sensor networks: A review

Abstract: A wireless sensor network typically consists of large number of low-cost densely deployed sensor nodes that have strictly constrained sensing, computation, and communication capabilities. Because of resource restricted sensor nodes, it is necessary to reduce the amount of information transmission so that average lifetime of sensor and thus the bandwidth consumption are improved. As wireless sensor networks are typically deployed in remote and hostile environments to transmit sensitive data, sensor nodes are in danger of node compromise attacks and security issues like data confidentiality and integrity are terribly necessary. Therefore, in this paper we have explored general security threats in wireless sensor network and made an extensive study to categorize available data gathering protocols and analyze possible security threats on them.

Simulators for Wireless Sensor Networks: A Review

Abstract: Wireless Sensor Networks (WSN) is made by an oversized variety of networked sensing nodes. It’s rather advanced, or perhaps unworkable, to model analytically a WSN and it always results in simple analysis with restricted confidence. Besides, deploying test-beds supposes a large effort. Therefore, simulation is important to check WSN. However, it needs acceptable model supported solid assumptions and an appropriate framework to ease implementation. Additionally, simulation results admit the actual state of affairs below study (environment), hardware and physical layer assumptions, that aren't typically correct enough to capture the behavior of a WSN, thus, make vulnerable the quality of results. However, a careful model yields to measurability and performance problems, attributable to the massive variety of nodes, that betting on application, got to be simulated. Therefore, the exchange between measurability and accuracy becomes a serious issue once simulating WSN. During this survey an acceptable model for WSN simulation is introduced, at the side of tips for choosing an acceptable framework. Additionally, a comparative description of obtainable tools is provided

Study of Mining Frequent Patterns at Various Levels of Abstraction

Abstract: The discovery of interesting association relationships among huge amounts of business transaction records can help in many business decision making process, association rules is one of the main popular pattern discovery techniques in data mining (KDD).The problem of dis-covering association rules has received considerable research attention and several algorithms for mining frequent pattern at primitive and multi-ple level have been developed. In this paper, we have studied various association rule mining algorithms like primitive association rule mining, generalized association rule mining and multilevel association rule mining. Mining primitive association rules helps in finding general knowl-edge considers all items at single level. Generalized association rule mining provides extra knowledge as sibling associations and even cross-parent associations. Multilevel association rule mining algorithm takes care of analyzing different level wise knowledge. Keywords: Primitive association rules, Multiple level association rules, Generalized association rules, Data mining, Support, Confidence.

A Survey on Security Requirements for WSNs: Focusing on the Characteristics Related to Security

Abstract: As WSNs combine with a diversity of next-generation technologies, wireless sensor networks (WSNs) have gained considerable attention as a promising ubiquitous technology. Even though several studies on WSNs are being undertaken, few systematically analyze the security issues relating to them. Moreover, recent systems tend to be implemented without sufficient consideration about owns security requirements, which can lead to lethal threats. Systems that do not consider security requirements may provide attackers the opportunity to reduce the overall efficiency and performance of the system. This means that inadequately applied security requirements can result in defective security of systems. Therefore, in this study, we emphasized the importance of security requirements to raise awareness regarding them. In addition, we analyzed literature that could be improved by including WSNs security requirements such as characteristics, constraints, and threats. Furthermore, we adopted a systematic methodology by referring to reliable literature and performed a different analysis from previous studies. We derived and mapped the different security factors based on the literature and illustrated the relationships of each security factor. Finally, our research compared with studies of a similar type to evaluate whether it provided a significant contribution. In other words, in this study, we analyzed various factors related to WSNs security based on reviewing the literature and show our contribution, such as a systematic analysis framework and factor mapping compared with traditional studies. Though there are some considerations, we expect that this research derived the essential security requirements in any WSNs environments.

Efficient and Secure Data Transmission and Sinkhole Detection in a Multi-Clustering Wireless Sensor Network Based on Homomorphic Encryption and Watermarking

Abstract: In a wireless sensor network, the sensors periodically transmit sensed data from a specific environment to a centralized station by wireless communication. Deployment in an open environment leads to the potential of security attacks. A sinkhole attack is a destructive attack aimed at the network layer, where the sinkhole node attracts other nodes by advertising itself as the best path to the base station. Subsequently receiving other sensor node packets and compromising network security. Hence, this work proposes a lightweight, secure method based on the Threshold Sensitive Energy Efficient Sensor Network protocol and watermarking techniques to ensure data integrity during transmission. The homomorphic encryption used in this scheme is to provide fast and efficient and consumes less energy while identifying sensor nodes for the purpose of sinkhole detection and prevention. The proposed work has been evaluated using OMNET++ simulation environment to measure the proposed work performance in the following metrics: delay, packet delivery ratio, throughput, and average energy consumption. Compared with previous works, the proposed work shows better results in these metrics. In addition, the proposed scheme consumes less energy compared with similar works due to the use of lightweight watermarking and authentication techniques. The results show that the proposed scheme enhances security by detecting the sinkhole attacker node before the attack is even activated. In addition, the proposed method ensures the integrity and authenticity of the sensed data while transmitting them from the sensor node until receiving it in the base station, and it can detect any tampering of the data.

EES-WCA: energy efficient and secure weighted clustering for WSN using machine learning approach

Abstract: The Wireless Sensor Network (WSN) is an application-centric network, where the data is collected using sensor nodes and communicated to the server or base station to process raw data and to obtain the decisions. For this, it is essential to maintain efficiency and security to serve critical applications. To deal with this requirement, most of the existing techniques modify the routing techniques to secure the network from one or two attacks, but there are significantly fewer solutions that can face multiple kinds of attacks. Therefore, this paper proposed a data-driven and machine learning-based Energy Efficient and Secure Weighted Clustering Algorithm (EES-WCA). The EES-WCA is a combination of EE-WCA and machine learning-based centralized Intrusion detection system (IDS). This technique first creates network clusters, then, without disturbing the WSN routine activity, collect traffic samples on the base station. The base station consists of two machine learning models: Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) to classify the traffic data and identify the malicious nodes in the network. This technique is validated through the generated traffic from the NS2.35 simulator and is also examined in real-time scenarios. The experimental results demonstrate that both the variants of EES-WCA are useful and classify seven different kinds of patterns. According to the simulation results on validation test data, we found up to 90% detection accuracy. Additionally, in real-time scenarios, it replicates the performance by approximately 75%. The performance of EES-WCA in terms of network quality of services such as packet delivery rate, throughput, end to end delay, and energy consumption confirm the superiority of the EES-WCA algorithm.

Symmetric-Key-Based Security for Multicast Communication in Wireless Sensor Networks

Abstract: This paper presents a new key management protocol for group-based communications in non-hierarchical wireless sensor networks (WSNs), applied on a recently proposed IP-based multicast protocol. Confidentiality, integrity, and authentication are established, using solely symmetric-key-based operations. The protocol features a cloud-based network multicast manager (NMM), which can create, control, and authenticate groups in the WSN, but is not able to derive the actual constructed group key. Three main phases are distinguished in the protocol. First, in the registration phase, the motes register to the group by sending a request to the NMM. Second, the members of the group calculate the shared group key in the key construction phase. For this phase, two different methods are tested. In the unicast approach, the key material is sent to each member individually using unicast messages, and in the multicast approach, a combination of Lagrange interpolation and a multicast packet are used. Finally, in the multicast communication phase, these keys are used to send confidential and authenticated messages. To investigate the impact of the proposed mechanisms on the WSN, the protocol was implemented in ContikiOS and simulated using COOJA, considering different group sizes and multi-hop communication. These simulations show that the multicast approach compared to the unicast approach results in significant smaller delays, is a bit more energy efficient, and requires more or less the same amount of memory for the code.

A Security Concept Based on Scaler Distribution of a Novel Intrusion Detection Device for Wireless Sensor Networks in a Smart Environment.

Abstract: Following the significant improvement of technology in terms of data collection and treatment during the last decades, the notion of a smart environment has widely taken an important pedestal in the science industry. Built in order to better manage assets, smart environments provide a livable environment for users or citizens through the deployment of sensors responsible for data collection. Much research has been done to provide security to the involved data, which are extremely sensitive. However, due to the small size and the memory constraint of the sensors, many of these works are difficult to implement. In this paper, a different concept for wireless sensor security in smart environments is presented. The proposed security system, which is based on the scaler distribution of a novel electronic device, the intrusion detection system (IDS), reduces the computational functions of the sensors and therefore maximizes their efficiency. The IDS also introduces the concept of the feedback signal and "trust table" used to trigger the detection and isolation mechanism in case of attacks. Generally, it ensures the whole network security through cooperation with other IDSs and, therefore, eliminates the problem of security holes that may occur while adopting such a security technique.