M. Pushpalatha

Regression-based trust model for mobile ad hoc networks

The focus of this study is to propose a generalised trust-model over routing protocols in mobile ad hoc networks (MANETs). It is observed that the presence of malicious nodes is a critical factor affecting the network performance in an ad hoc network. The novelty in the approach is that the notion of trust can be easily incorporated into any routing protocol in MANETs. The vector auto regression based trust model is introduced to identify malicious nodes that launch multiple attacks in the network. The proposed trust model is incorporated over ad hoc on-demand distance vector (AODV) routing protocol and optimised link state routing (OLSR) protocol in MANETs. The performance evaluations show that by carefully setting the trust parameters, substantial benefit in terms of throughput can be obtained with minimal overheads. The computed trust and confidence values are introduced into the path computation process of the ad hoc routing protocols. It was observed that the nodes in the network were able to learn the malicious activities of their neighbours and hence, alternate trustworthy paths are taken to avoid data loss in the network, with trade-offs in end-to-end packet delay and routing traffic.

Prevention of flooding attacks in mobile ad hoc networks

The lack of any centralized infrastructure in mobile ad hoc networks (MANET) is one of the greatest security concerns in the deployment of wireless networks. Thus communication in MANET functions properly only if the participating nodes cooperate in routing without any malicious intention. However, some of the nodes may be malicious in their behavior, by indulging in flooding attacks on their neighbors. Some others may act malicious by launching active security attacks like denial of service. This paper addresses few related works done on trust evaluation and establishment in ad hoc networks. Related works on flooding attack prevention are reviewed. A new trust approach based on the extent of friendship between the nodes is proposed which makes the nodes to co-operate and prevent flooding attacks in an ad hoc environment. The performance of the trust algorithm is tested in an ad hoc network implementing the Dynamic Source Routing (DSR) protocol.

Analysis of energy efficient ECC and TinySec based security schemes in Wireless Sensor Networks

Modern day scientific society has seen the emergence of various trends in research and implementation. Wireless Sensor Network (WSN) is one among those research trends that has emerged, but its progress has been dammed by the security concerns due to certain limitations in resource and energy scarcity. In this paper we have analysed the performance of certain common well known security schemes like TinySec, RC5, ECIES and ECDSA by implementing it in real time scenarios. We have made a detailed comparison among them to find out their affectivity and their performance under multiple metrics. The paper also promotes the use of a security scheme based on Elliptical Curve Cryptography (ECC), utilizing ECDSA and Diffie-Hellman (DH key transfer). Analysis results shows that the scheme works better than the common existent schemes and is also energy efficient as well as can conserve resources if used appropriately.

Fault tolerant and dynamic file sharing ability in mobile ad hoc networks

This paper proposes a new method for replication of files within a mobile adhoc network based on the prediction of the drift of the mobile nodes. The main feature of mobile ad hoc network is the dynamic topology. That is the nodes in the network are in mobile. To facilitate file sharing in mobile networks the only technique is file replication. Shared files are available at all times even if the owner of the file drifts away. The goal is to ensure that files autonomously maintain replica levels over time in a potentially dynamic and hostile environment. Also the proposed algorithm ensures that only those files are to be replicated which are about to exit from the network ensuring better efficiency and fewer overheads. Existing algorithms are simulated in Netlogo simulation environment and observations are compared with the proposed technique to check the efficiency of all algorithms.

Implementation of a trust model over AODV in a wireless ad hoc testbed

We have customized Ad hoc On demand Distance Vector (AODV) protocol and augmented security aspect in real time scenario using numeric step values called Trust assigned to finite number of neighbor nodes to evaluate network behavior, subsequently secure the network by barricading the network from malicious nodes in Blackhole and flooding attack modes. Experiments were carried out using a custom-made testbed built on wxPython that supports various characteristics of nodes like variable data rates, node positions and malicious behavior for testing and display results in a graphical format. The results have favored aforementioned proposal showing a 70% increase in throughput obtained from trust implemented experimentation as compared to standard one without the trust parameter. The overhead in trusted scenario encountered was minimal despite the end to end delay of packets being higher than the traditional AODV by 30 msec. Hence, we have concluded that our method of using trust has resulted in a secured reactive protocol with applications suited for wireless attack prone environment when applied to a network consisting of four nodes. Our work is also the first ever implementation of a trust model over an adhoc routing protocol in a real adhoc testbed.

A Generalized Trust Framework for Mobile Ad Hoc Networks

Mobile ad hoc networks (MANET) are formed when two or more nodes come within the communication range of each other. Since the wireless range is very short, all the nodes in the network have to extend their complete co-operation for efficient functioning of the network. This paper proposes a generalized trust framework for any ad hoc routing protocol to curb selfish and malicious nodes in a MANET. The trust relationships existing between the nodes determine the routing path to be taken for data transfer. The trust framework is combined with any MANET routing algorithm. The performance analysis of this framework is currently done with two reactive protocols. Jointly, they form a trusted network to curb various attacks originating in the ad hoc network. This type of a trusted framework established in a MANET, would be most suited for tactical environments.

Energy Aware Data Sharing in Mobile Ad Hoc Networks

In mobile ad hoc networks (MANET) ,computation devices are battery powered. Limited energy in battery constrains the computation and communication of each device. Hence services like sharing a data or information among users becomes a challenging issue in critical environments like military applications, rescue operations etc. To overcome this, we have proposed a replication model which replicates shared data in suitable nodes. It addresses how data sharing can be done effectively by periodically checking the remaining energy of each node that holds the replica. If the remaining energy falls below a threshold level, replica can be relocated to appropriate nodes that has the maximum energy. Therefore our proposal ensures file availability, improves the network life time, decreases query response time, increases energy utilization, decreases number of packet drops due to battery depletion of a node.

Applicability of sub graph centrality to improve data accessibility among peers in MANETs

Data sharing plays an essential role in many of the mobile ad-hoc network (MANET) applications that exhibits collaborative behavior. In such applications, replication is used as a foremost and fundamental technique to improve data availability. However, due to the dynamic nature of the network, data replication becomes more intricate in MANET. To alleviate this problem, we have proposed a mechanism which not only enhances data accessibility, replicates data in a minimum number of nodes, relocates shared data on the prediction of mobility of replica holder and in addition, data can be accessed by any node in a minimum number of hops. In our approach, we have prefaced mathematical concept known as minimum dominating set and sub graph centrality principle to decide the number of replicas both in static and dynamic environment. Simulation results when compared with the existing mechanisms shows that the response time or data access delay is reduced, client can access the data from the server in a minimum number of hops, and consequently the number of forwarded messages to access the data are greatly reduced thus making our network energy efficient.

Analysis of Weather Data Using Forecasting Algorithms

Predictive analytics is the current focus not only on business applications but also it emerges in all types of applications which involves in the prediction of future outcomes. This results in the development of various prediction algorithms under the domain of machine learning, data mining, and forecasting. This paper focuses on analysis of the data pattern and its behavior using univariate forecasting model. Temperature is taken as the univariate observation from weather dataset, and the forecast value is predicted using forecasting algorithms. The predicted forecast value is compared with real-time data from which it is observed that level component plays a major role than trend and seasonal component in real-time data, and the predicted forecast value does not depend on size of the dataset.

A survey of predictive analytics using big data with data mining

Today, the world is filled with data like Oxygen. The amount of data being harvested and eaten up is flourishing vigorously in the digital world. The growing exploitation of novel inventions and social media leads to the generation of huge quantities of data called Big data which can bring remarkable information if analysed properly. Organizations may undergo for analysis of big data to having better decisions, thus big data analytics is being paid attention in recent times. For finding the concealed values from big data, society requires new schemes or strategies. Predictive analytics comprises of several statistical and analytical techniques for developing novel strategies for the future possibilities of prediction. Therefore, Predictive analytics becomes vital when an essential quantity of highly sensitive data has to be handled. Based on the perceived events, future probabilities and measures are predicted. With the aid of available data mining techniques, predictive analytics predicts the events in future and can make recommendations called prescriptive analytics. This review paper gives clear idea to apply data mining techniques and predictive analytics on different medical dataset to predict various diseases with accuracy levels, pros and cons, that concludes about the issues of those algorithms and futuristic approaches on big data.