---
owner:
    hid: 224
    name: Rawat, Neha
    url: https://github.com/bigdata-i523/hid224
paper1:
    abstract: >
         The rise of Big Data in the field of Hospitality
         though recent, is by no means temporary. The hotel
         industry is one which deals with millions of customers
         on a day-to-day basis and generates a plethora  of customer
         data through such interactions. It is also the sector which
         depends the most on customer  loyalty, and thus profits greatly
         through the analytical insights that Big Data has to offer.
         Keeping  this is mind, hotels today, whether they are big chains
         or small independent establishments, are using data generated
         internally and on the web to develop strategies for better
         customer satisfaction, marketing  effectiveness, yield management
         and operational efficiency.
    author:
        - Rawat, Neha
    chapter: Business
    hid:
        - 224
    status: Nov 3 17 100%
    title: Big Data Applications in the Hospitality Sector
    url: https://github.com/bigdata-i523/hid224/blob/master/paper1/report.tex
paper2:
    review: Nov 6 2017
    abstract: >
              Efficient management and utilization of energy and other
              utilities is the need of the hour. The plethora of real-time
              data generated during day-to-day operational activities can
              be used to detect consumption patterns and predict outages,
              shortages and surges in power usage, while simultaneously
              improving the use of renewable resources as sustainable
              alternatives. Intelligent big data analytics can help the
              energy and utilities sector by reducing costs through devising
              efficient operational strategies, becoming more
              self-sufficient and productive in their performance and
              improving customer satisfaction and interaction by making
              valuable suggestions to the consumers on how to use their
              resources better.
    author:
        - Rawat, Neha
    chapter: Energy
    hid:
        - 224
    status: Nov 6 17 100%
    title: Big Data Applications in the Energy and Utilities Sector
    url: https://github.com/bigdata-i523/hid224/blob/master/paper2/report.tex
project:
    abstract: >
              With the increase in internet traffic, threats on the network
              have also increased. Denial-of-service attacks are cyber
              attacks wherein a perpetrator, due to any kind of malicious
              intent, tries to make a resource on the network unavailable
              to its intended users and carries it out by swamping the
              system or resource with excess requests in order to overload
              it and prevent users from accessing it. A much more dangerous
              variety of such an attack is if it is distributed i.e. coming
              from various sources. Big Data analytics, however, can be
              used to detect such attacks by having the ability to store
              the voluminous logs of such attacks and using the data and
              machine learning techniques to design an anomaly detection
              system (using a classification model) to detect and prevent
              these attacks. This project wil aim to explore such
              classification models, design and train the most optimum
              model and display its effects using a DDoS logs dataset.
    author:
        - Rawat, Neha
    hid:
        - 224
    status: Dec 04 17 100%
    title: >
           Big Data Analytics in Detection of
           DDoS (Distributed Denial-of-Service) attacks
    type: project
    url: https://github.com/bigdata-i523/hid224/blob/master/project/report.tex
    chapter: Security