Browsing by Author "Mishra, Richa"

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    E-commerce Dapp
    (AIKTC, 2023-05) Mishra, Richa; Kadiri, Saud (19CO21); Khan, Anas (19CO24); Khan, Farhaan (19CO26); Shikalgar, Farhan (19CO56)
    Improving efficiency and performance is an important topic in the world today. As it is well-known, cooperative computing is an effective and traditional approach, and it is widely used in various fields. Inspired by this idea, take E- commerce for example, Security is one of its important indicators. In E-commerce, the security technology has become a major issue restricting the rapid development and popularization of E- commerce.With the advent of new technologies, Blockchain plays a major role in ecommerce sector.With the characteristics of decentralization, persistency, anonymity and auditability, blockchain technology is a new tool to solve the product traceability, information security and privacy, payment efficiency and cost reduction in cross- border e-business.Existing E-commerce models are trapped in a dilemma between the proof of ownership and privacy protection. To address this issue,We have made a platform Shoppingverse which is a blockchain based ecommerce.we design a privacy-preserving business protocol by employing private smart contracts in the negotiation phase. The protocol allows counterparties make deals without the disclosure of private information such as identities, addresses, and phone numbers. Moreover, we employ the zero- knowledge proof to guarantee the ownership.
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    Stock analysis and prediction website
    (AIKTC, 2023-05) Mishra, Richa; Shaikh, Muhammad Huzaifa (18CO40); Bagdadi, Ameeruddin (19CO12); Khan, Raquib (19CO31); Qureshi, Mohammed Usman (19CO47)
    In this project we attempt to implement machine learning approach to predict stock prices. Machine learning is effectively implemented in forecasting stock prices. The objective is to predict the stock prices in order to make more informed and accurate investment decisions. We propose a stock price prediction system that integrates mathematical functions, machine learning, and other external factors for the purpose of achieving better stock prediction accuracy and issuing profitable trades. There are two types of stocks. You may know of intraday trading by the commonly used term ”day trading.” Interday traders hold securities positions from at least one day to the next and often for several days to weeks or months. LSTMs are very powerful in sequence prediction problems because they’re able to store past information. This is important in our case because the previous price of a stock is crucial in predicting its future price. While predicting the actual price of a stock is an uphill climb, we can build a model that will predict whether the price will go up or down. Apart from that, we have included a stock analysis feature, which helps users to understand the performance of a particular stock, also it guides users to invest in a stock whose price would eventually rise up in the coming future, leading to profit gains.