With the widespread popularity of Internet-enabled devices, there is an exponential increase in the information sharing among different geographically located smart devices. These smart devices may be heterogeneous in nature and may use different communication protocols for information sharing among themselves. Moreover, the data shared may also change with respect to various Vs (volume, velocity, variety, and value) to categorize it as big data. However, as these devices communicate with each other using an open channel, the Internet, there is a higher chance of information leakage during communication. Most of the existing solutions reported in the literature ignore these facts. Keeping focus on these points, in this article, we propose secure storage, verification, and auditing (SecSVA) of big data in cloud environment. SecSVA includes the following modules: an attribute-based secure data deduplication framework for data storage on the cloud, Kerberos-based identity verification and authentication, and Merkle hash-tree-based trusted third-party auditing on cloud. From the analysis, it is clear that SecSVA can provide secure third party auditing with integrity preservation across multiple domains in the cloud environment.

SecSVA: Secure Storage, Verification, and Auditing of Big Data in the Cloud Environment

Internet of Things (IoT) is a new technology which offers enormous applications that make people’s lives more convenient and enhances cities’ development. In particular, smart healthcare applications in IoT have been receiving increasing attention for industrial and academic research. However, due to the sensitiveness of medical information, security and privacy issues in IoT healthcare systems are very important. Designing an efficient secure scheme with less computation time and energy consumption is a critical challenge in IoT healthcare systems. In this paper, a lightweight online/offline certificateless signature (L-OOCLS) is proposed, then a heterogeneous remote anonymous authentication protocol (HRAAP) is designed to enable remote wireless body area networks (WBANs) users to anonymously enjoy healthcare service based on the IoT applications. The proposed L-OOCLS scheme is proven secure in random oracle model and the proposed HRAAP can resist various types of attacks. Compared with the existing relevant schemes, the proposed HRAAP achieves less computation overhead as well as less power consumption on WBANs client. In addition, to nicely meet the application in the IoT, an application scenario is given.

Remote Authentication Schemes for Wireless Body Area Networks Based on the Internet of Things

An important issue of research in wireless sensor networks (WSNs) is to dynamically organize the sensors into a wireless network and route the sensory data from sensors to a sink. Clustering in WSNs is an effective technique for prolonging the network lifetime. In most of the traditional routing in clustered WSNs assumes that there is no obstacle in a field of interest. Although it is not a realistic assumption, it eliminates the effects of obstacles in routing the sensory data. In this paper, we first propose a clustering technique in WSNs named energy-efficient homogeneous clustering that periodically selects the cluster heads according to a hybrid of their residual energy and a secondary parameter, such as the utility of the sensor to its neighbors. In this way, the selected cluster heads have equal number of neighbors and residual energy. We then present a route optimization technique in clustered WSNs among obstacles using Dijkstra's shortest path algorithm. We demonstrate that our work reduces the average hop count, packet delay, and energy-consumption of WSNs.

Geographic Routing in Clustered Wireless Sensor Networks Among Obstacles

In sensor-enabled Internet of Things (IoT), nodes are deployed in an open and remote environment, therefore, are vulnerable to a variety of attacks. Recently, trust-based schemes have played a pivotal role in addressing nodes’ misbehavior attacks in IoT. However, the existing trust-based schemes apply network wide dissemination of the control packets that consume excessive energy in the quest of trust evaluation, which ultimately weakens the network lifetime. In this context, this paper presents an energy efficient trust evaluation (EETE) scheme that makes use of hierarchical trust evaluation model to alleviate the malicious effects of illegitimate sensor nodes and restricts network wide dissemination of trust requests to reduce the energy consumption in clustered-sensor enabled IoT. The proposed EETE scheme incorporates three dilemma game models to reduce additional needless transmissions while balancing the trust throughout the network. Specially: 1) a cluster formation game that promotes the nodes to be cluster head (CH) or cluster member to avoid the extraneous cluster; 2) an optimal cluster formation dilemma game to affirm the minimum number of trust recommendations for maintaining the balance of the trust in a cluster; and 3) an activity-based trust dilemma game to compute the Nash equilibrium that represents the best strategy for a CH to launch its anomaly detection technique which helps in mitigation of malicious activity. Simulation results show that the proposed EETE scheme outperforms the current trust evaluation schemes in terms of detection rate, energy efficiency and trust evaluation time for clustered-sensor enabled IoT.

Trust Evaluation for Light Weight Security in Sensor Enabled Internet of Things: Game Theory Oriented Approach

Efficient certificateless access control for industrial Internet of Things

Secure and efficient data transmission is a critical issue for cluster-based wireless Sensor Networks (WSNs). In Cluster-based WSNs authentication of users is a very Important issue .So, by authenticating the sent user and the destination user , we can achieve the security and efficiency of data over CWSNs. To provide security of data and authentication of user we proposed a technique where we are implementing two concepts for performing those operations. The first one is identity based signature (IBS) for verification of user generated by the verifier and second one is a key is xor operated with the data and get the cipher and then binary level technique for encryption and decryption of the original message. The binary level technique converts the plain text into binary form and then splits the data into blocks and assign values to it based on identification mark (IM) technique which depends upon the length of the binary digits, then these are divided into two level, 1 st level is 2 bit and 2 nd level is 4 bit . Then at the receiver user the Cipher text will be decrypted by using the reverse technique and the destination user will get the original message. By providing those techniques we can improve efficiency, security overhead and energy consumption.

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Secure and Efficient Data Transmission for Cluster-Based Wireless Sensor Networks

In this paper we are proposing an efficient decision support system for Diabetes Disease, apart from the traditional simple support vector machine. We are proposing an efficient two level approach for classifying data. In initial phase we extract optimal feature set from the training data by analyzing the optimality in the dataset, then new dataset is formed as optimal training dataset, now we apply our classification mechanism on the optimal feature set.

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An Efficient Expert System For Diabetes By Naïve

Now a day’s usage of mobile phones is higher when compared with the usage of laptops and desktops. Researchers are interested in invocation of functionalities to the user with minimal over head by using dynamic invocation and with language interoperability approach. Even though various traditional approaches introduced in the traditional mechanisms those are not optimum and used for only few simple query or minimal parameters. For dynamic invocation we introduced a novel Proxy based approach and for the language interoperability we introduced WSDL files.

Satyanarayana Gandi

Papers

Secure and Efficient Data Transmission for Cluster-Based Wireless Sensor Networks

An Efficient Expert System For Diabetes By Naïve

A Novel Architecture for Dynamic Invocation of Web Services