Tuhina Jayanta Banerjee

Studying at MPSTME
Mumbai
Skills:
frontend, dataset, neural networks, natural language processing, machine learning
Education:
MPSTME
Profile
Projects
Publications
Education
Achievements
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Language Activity
Technical Skills
frontend, dataset, neural networks, natural language processing, machine learning, artificial intelligence
Projects
Android application for recruitment “Linker”
-
An Android app that can be used to recruit candidates for various jobs. The app was
developed with an added feature that helped organizations in social networking. This
app was developed using the development environment
Hotel Booking “7Seas”
-
A website that can help customers to book hotel rooms and avail other related services. The website includes a login page, payment page, and a menu with a list of other reservation related services.
Data mining and Web Scrapping “Spider”
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The solution will detect fake news, offensive/ inappropriate texts (comments, posts,
feeds, etc.), images (original or morphed pictures) and videos (original or fake videos)
across the social media websites using keywords, crawling, APIs, reverse image and
AI/ML/data mining techniques. The solution will also help in identifying the original
source of posting and proximate profiles.
Skills: artificial intelligence | dataset | ml
Publications
Detection of DOS & DDOS attacks using Neural network(October-2019)
International Journal of Research in Engineering, Science and Management
10 Oct, 2019
Abstract: In this paper, there are many techniques reviewed
which detects the Denial of Services (DoS) attack and Distributed
Denial of Services (DDoS) attack over a network, server or device
and the new technique of detection of DoS and DDoS using neural
the network is proposed. In DoS and DDoS attacks, the attacker may
not have any specific mindset to manipulate or steal the data, but
these attacks can lead to volume traffic which will lead to the
denial of service for legitimate users. A neural network is known
for its effectiveness and efficiency and is quite comprehensive
which proves to be one of the reliable techniques in the aspect of
detection. The model proposed can predict the trend of normal
network traffic, identify the abnormal traffic caused by DDoS and
DoS hit over a network.
Education
MPSTME
Bachelor of Engineering (B.E.), Computer Engineering
2016 - 2022
Achievements
Social conclave ’19 – Cyberbullying by NMIMS with UNICEF at NMIMS
NMIMS
Runner-up
IDEA ’20 by Smart India Hackathon (SIH)
Smart India Hackathon, NMIMS.
Participant
Cyber Hackathon ’19
NASSCOM Pune-DC Infosys
Top 10
PowerPoint presentation competition ’18- Make in India
T.I.M.E. at NMIMS
Participant
Innovative Project Competition’18- Road Roller
NMIMS
Participant
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