Visible to the public Biblio

Filters: Author is Kumar, Sanjeev  [Clear All Filters]
2023-09-20
Rawat, Amarjeet, Maheshwari, Himani, Khanduja, Manisha, Kumar, Rajiv, Memoria, Minakshi, Kumar, Sanjeev.  2022.  Sentiment Analysis of Covid19 Vaccines Tweets Using NLP and Machine Learning Classifiers. 2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COM-IT-CON). 1:225—230.
Sentiment Analysis (SA) is an approach for detecting subjective information such as thoughts, outlooks, reactions, and emotional state. The majority of previous SA work treats it as a text-classification problem that requires labelled input to train the model. However, obtaining a tagged dataset is difficult. We will have to do it by hand the majority of the time. Another concern is that the absence of sufficient cross-domain portability creates challenging situation to reuse same-labelled data across applications. As a result, we will have to manually classify data for each domain. This research work applies sentiment analysis to evaluate the entire vaccine twitter dataset. The work involves the lexicon analysis using NLP libraries like neattext, textblob and multi class classification using BERT. This word evaluates and compares the results of the machine learning algorithms.
2021-11-29
Lata, Kiran, Ahmad, Salim, Kumar, Sanjeev, Singh, Deepali.  2020.  Cloud Agent-Based Encryption Mechanism (CAEM): A Security Framework Model for Improving Adoption, Implementation and Usage of Cloud Computing Technology. 2020 International Conference on Advances in Computing, Communication Materials (ICACCM). :99–104.
Fast Growth of (ICT) Information and Communication Technology results to Innovation of Cloud Computing and is considered as a key driver for technological innovations, as an IT innovations, cloud computing had added a new dimension to that importance by increasing usage to technology that motivates economic development at the national and global levels. Continues need of higher storage space (applications, files, videos, music and others) are some of the reasons for adoption and implementation, Users and Enterprises are gradually changing the way and manner in which Data and Information are been stored. Storing/Retrieving Data and Information traditionally using Standalone Computers are no longer sustainable due to high cost of Peripheral Devices, This further recommends organizational innovative adoption with regards to approaches on how to effectively reduced cost in businesses. Cloud Computing provides a lot of prospects to users/organizations; it also exposes security concerns which leads to low adoption, implementation and usage. Therefore, the study will examine standard ways of improving cloud computing adoption, implementation and usage by proposing and developing a security model using a design methodology that will ensure a secured Cloud Computing and also identify areas where future regularization could be operational.
2020-02-17
Kumar, Sanjeev, Kumar, Harsh, Gunnam, Ganesh Reddy.  2019.  Security Integrity of Data Collection from Smart Electric Meter under a Cyber Attack. 2019 2nd International Conference on Data Intelligence and Security (ICDIS). :9–13.
Cyber security has been a top concern for electric power companies deploying smart meters and smart grid technology. Despite the well-known advantages of smart grid technology and the smart meters, it is not yet very clear how and to what extent, the Cyber attacks can hamper the operation of the smart meters, and remote data collections regarding the power usage from the customer sites. To understand these questions, we conducted experiments in a controlled lab environment of our cyber security lab to test a commercial grade smart meter. In this paper, we present results of our investigation for a commercial grade smart meter and measure the operation integrity of the smart meter under cyber-attack conditions.