Browsing by Author "Kankar, M."

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    Intrusion Detection Techniques for Detection of Cyber Attacks
    (Springer Science and Business Media Deutschland GmbH, 2021) Ahmed, S.S.; Kankar, M.; Rudra, B.
    Intrusion detection system (IDS) is a software-related application where we can detect the system or network activities and notice if any suspicious task happens. Excellent broadening and the use of the Internet lift examine the communication and save the digital information securely. Nowadays, attackers use variety of attacks for fetching private data. Most of the IDS techniques, algorithms, and methods assist to find those various attacks. The central aim of the project is to come up with an overall study about the intrusion detection mechanism, various types of attacks, various tools and techniques, and challenges. We used various machine learning algorithms and found performance metrics like accuracy, recall, and F-measure and compared with the existing work. After this research, we got good results that can help to detect the cyber attacks being performed in the network. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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    Price Prediction of Agricultural Products Using Deep Learning
    (Springer Science and Business Media Deutschland GmbH, 2022) Kankar, M.; Anand Kumar, A.M.
    Every field in the world is undergoing a significant change because of the influence of technology. The agricultural sector of the Indian economy needs more technological support for its development and growth in India. Price prediction of agricultural products helps ensure that the farmers either get good returns or recover their investments. Hence, the characteristics of deep neural networks such as CNN and deep learning models can be used in predicting prices. A convolution neural network-based model can indirectly predict fruits and vegetable prices by classifying images to their variety. Deep learning models such as long short-term memory (LSTM) and bidirectional LSTM (BiLSTM) can also help predict the market price of agricultural products. Fruits and vegetable prices mainly depend on a few things, variety, quality, and market rate. We use the CNN model to deal with variety and quality, different varieties of a single fruit or vegetable having different prices, followed by prediction using LSTM and bidirectional LSTM to deal with market price prediction in a volatile market. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.