Vasanth Kumar D

VIT Fashion Institute of Technology

Chennai Campus

Varatharajan R

Gunasekaran M

Priyan M

Gao X.Z.

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Computers & Electrical Engineering

As health data are very sensitive, there is a need to prevent and control the health data with end-to-end security solutions. In general, a number of authentication and authorization schemes are available to prevent and protect the sensitive data, which are collected with the help of wearable Internet of Things (IoT) devices. The transport layer security (TLS) protocol is designed to transfer the data from source to destination in more reliable manner. This protocol enables a user to overcome the no lost or reordered messages. The more challenge with TLS is to tolerate unreliability. In order to overcome this issue, Datagram transport layer security (DTLS) protocol has been designed and used in low-power wireless constrained networks. The DTLS protocol consists of a base protocol, record layer, handshake protocol, ChangeCipherSpec and alert protocol. The complex issue with the DTLS protocol is the possibility of an attacker could send a number of ClientHello messages to a server. This scenario would cause a denial-of-service (DOS) attack against the server. This DoS attack enables new connection between the attacker and server, increasing attacker bandwidth, and allocation of resources for every ClientHello message. In order to overcome this issue, we have proposed a smart gateway-based authentication and authorization method to prevent and protect more sensitive physiological data from an attacker and malicious users. The enhanced smart gateway-based DTLS is demonstrated with the help of Contiki Network Simulator. The packet loss ratio is calculated for the CoAP, host identity protocol, CoAP-DTLS and CoAP-enhanced DTLS to evaluate the performance of the proposed work. Data transmission and handshake time are also calculated to evaluate the efficiency of the enhanced DTLS. © 2017, Springer Science+Business Media, LLC.

The Journal of Supercomputing

Enhanced DTLS with CoAP-based authentication scheme for the internet of things in healthcare application

Twitter, a social blogging site which became the tremendous topic in today’s environment, which made several organizations and public to develop their identity and overwhelming through this social website. But unfortunately, twitter facing great challenges due to spammers who break the reputation of the website from deliberate users to stop using it. Researchers have proposed many techniques to overcome the issues faced by the spammers. As far researchers find a new path so as the spammers develop new techniques to travel in that path. So far, many algorithms were proposed to detect the spammers and some extraction techniques have developed to increase the potential of detection rate. In this paper, the main focus is about feature extraction of our data with a hybrid approach of combining logistic regression with dimensional reduction technique using principal component analysis. Our dataset contains 17 million users’ tweets with 159 features included in it. Then we are going to extract particular features from it which would be helpful for the further process of increasing the classification accuracy. For the classification process, our work extended for the process of classification of data using some machine learning techniques. From the proposed work the detection rate could be increased by using particular features for the classification process. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.

Cluster Computing

Feature extraction using LR-PCA hybridization on twitter data and classification accuracy using machine learning algorithms

In wireless sensor networks (WSN), the nodes are used to collect and gather the data from different environments. Hence, the network consumes more energy which is the main and challenging issue in WSNs. Since the sensor is operating under battery, recharging is impossible and hence the lifetime of each sensor is an important issue. Therefore, it is necessary to introduce new and efficient techniques to extend the network lifetime. In this paper, a new delay constrained energy efficient routing technique is proposed for performing effective routing in WSNs. This approach introduces a delay constraint based reliable routing approach which reduces the energy consumption by constructing efficient clusters without increasing the end-to-end delay. Moreover, the proposed technique called the rule based clustering for routing model provides better performance in terms of network lifetime than the other existing techniques since they consume more energy during the formation of clusters and finding the shortest path. Moreover, additional overhead on the cluster head selection is tackled also using rules in this proposed model in an efficient manner by building balanced clusters. The main advantage of the proposed approach is that it extends the lifetime of the network and increases the throughput, energy efficiency, link quality and scalability. The experimental verification of this technique has been carried out using MATLAB simulations and proved that this model increases the packet delivery rate, network performance and reduces the delay and energy consumption. © 2017, Springer Science+Business Media, LLC.

A rule based delay constrained energy efficient routing technique for wireless sensor networks

Most of the advancements are now carried out by interconnecting physical devices with computers; this is what known as Internet of Things (IoT). The major problems facing by blind people fall in the category of navigating through indoor and outdoor environments consisting of various obstacles and recognition of person in front of them. Identification of objects or person only with perceptive and audio information is difficult. An intelligent, portable, less expensive, self-contained navigation and face recognition system is highly demanded for blind people. This helps blind people to navigate with the help of a Smartphone, global positioning system (GPS) and a system equipped with ultrasonic sensors. Face recognition can be done using neural learning techniques with feature extraction and training modules. The images of friends, relatives are stored in the database of user Smartphone. Whenever a person comes in front of the blind user, the application with the help of neural network gives the voice aid to the user. Thus this system can replace the regular imprecise use of guide dogs as well as white sticks to help the navigation and face recognition process for people with impaired vision.In this paper, we have proposed a novel image recognition and navigation system which provides precise and quick messages in the form of audio to visually challenged people so that they can navigate easily. The performance of the proposed method is comparatively analyzed with the help of ROC analysis. © 2017, Springer Science+Business Media, LLC, part of Springer Nature.

Intelligent face recognition and navigation system using neural learning for smart security in Internet of Things

In the present era of Information Technology, almost all big and small scale companies are moving towards cloud to store and manage the data. Cloud computing is a routine of deploying a structure of distant servers speed up on the Internet to store, oversee, and manage information, rather than a neighbourhood server or a PC. The purpose for cloud procurement is reduced cost, adaptability, regular access and refreshed programming. Nowadays, healthcare frameworks are adjusting computerized stages and ending up being more patient-centered and data driven. In this paper, we present a planning empowered intermediary re-encryption method to defeat the security issues. This Technique will allow only limited access rights to an authorized agent to access the records for a specific time period. This technique will use a searchable encryption and proxy Re-encryption technique. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.

Mobile Networks and Applications

E-Health Cloud Security Using Timing Enabled Proxy Re-Encryption

An adaptive decision based kriging interpolation algorithm for the removal of high density salt and pepper noise in images

Journal of Biomolecular Techniques : JBT

Article Watch: September 2017

Signal, Image and Video Processing

Decision-based neighborhood-referred unsymmetrical trimmed variants filter for the removal of high-density salt-and-pepper noise in images and videos

IEEE Signal Processing Letters

A New Adaptive Weighted Mean Filter for Removing Salt-and-Pepper Noise

Signal Processing

A novel algorithm for removal of salt and pepper noise using continued fractions interpolation

Journal	Data powered by TypesetComputers & Electrical Engineering
Publisher	Data powered by TypesetElsevier BV
ISSN	0045-7906
Open Access	0