Deepali Virmani

Deepali Virmani, Shweta Taneja, Geetika Malhotra

K-means is an effective clustering technique used to separate similar data into groups based on initial centroids of clusters. In this paper, Normalization based K-means clustering algorithm(N-K means) is proposed. Proposed N-K means clustering algorithm applies normalization prior to clustering on the available data as well as the proposed approach calculates initial centroids based on weights. Experimental results prove the betterment of proposed N-K means clustering algorithm over existing K-means clustering algorithm in terms of complexity and overall performance.

Savneet Kaur, Deepali Virmani, Satbir Jain

Recent advances in the development of the low-cost, power-efficient embedded devices, coupled with the rising need for support of new information processing paradigms such as smart spaces and military surveillance systems, have led to active research in large-scale, highly distributed sensor networks of small, wireless, low-power, unattended sensors and actuators. While applications keep diversifying, one common property they share is the need for an efficient network architecture tailored towards information retrieval in sensor networks. Previous solutions designed for traditional networks serve as good references; however, due to the vast differences between previous paradigms and needs of sensor networks, a framework is required to gather and impart only the required information .To achieve this goal in this paper we have proposed a framework for intelligent information retrieval and dissemination to desired destination node. The proposed frame work combines three major concern areas in WSNs i.e. data aggregation, information retrieval and data dissemination in a single scenario. In the proposed framework data aggregation is responsible for combining information from all nodes and removing the redundant data. Information retrieval filters the processed data to obtain final information termed as intelligent data to be disseminated to the required destination node.

Deepali Virmani, Ankita Soni, Shringarica Chandel et al.

Wireless Sensor Networks (WSN) is an emerging technology now-a-days and has a wide range of applications such as battlefield surveillance, traffic surveillance, forest fire detection, flood detection etc. But wireless sensor networks are susceptible to a variety of potential attacks which obstructs the normal operation of the network. The security of a wireless sensor network is compromised because of the random deployment of sensor nodes in open environment, memory limitations, power limitations and unattended nature. This paper focuses on various attacks that manifest in the network and provides a tabular representation of the attacks, their effects and severity. The paper depicts a comparison of attacks basis packet loss and packet corruption. Also, the paper discusses the known defence mechanisms and countermeasures against the attacks.

Deepali Virmani, Vikrant Malhotra, Ridhi Tyagi

Opinion Mining and Sentiment Analysis is a process of identifying opinions in large unstructured/structured data and then analysing polarity of those opinions. Opinion mining and sentiment analysis have found vast application in analysing online ratings, analysing product based reviews, e-governance, and managing hostile content over the internet. This paper proposes an algorithm to implement aspect level sentiment analysis. The algorithm takes input from the remarks submitted by various teachers of a student. An aspect tree is formed which has various levels and weights are assigned to each branch to identify level of aspect. Aspect value is calculated by the algorithm by means of the proposed aspect tree. Dictionary based method is implemented to evaluate the polarity of the remark. The algorithm returns the aspect value clubbed with opinion value and sentiment value which helps in concluding the summarized value of remark.

Deepali Virmani, Vikrant Malhotra, Ridhi Tyagi

Opinion mining and Sentiment analysis have emerged as a field of study since the widespread of World Wide Web and internet. Opinion refers to extraction of those lines or phrase in the raw and huge data which express an opinion. Sentiment analysis on the other hand identifies the polarity of the opinion being extracted. In this paper we propose the sentiment analysis in collaboration with opinion extraction, summarization, and tracking the records of the students. The paper modifies the existing algorithm in order to obtain the collaborated opinion about the students. The resultant opinion is represented as very high, high, moderate, low and very low. The paper is based on a case study where teachers give their remarks about the students and by applying the proposed sentiment analysis algorithm the opinion is extracted and represented.

Deepali Virmani, Nidhi Beniwal, Gargi Mandal et al.

As computer systems become more pervasive and complex, security is increasingly important. Secure Transmission refers to the transfer of data such as confidential or proprietary information over a secure channel. Many secure transmission methods require a type of encryption. Secure transmissions are put in place to prevent attacks such as ARP spoofing and general data loss. Hence, in order to provide a better security mechanism, in this paper we propose Enhanced Tiny Encryption Algorithm with Embedding (ETEA), a data hiding technique called steganography along with the technique of encryption (Cryptography). The advantage of ETEA is that it incorporates cryptography and steganography. The advantage proposed algorithm is that it hides the messages.