Publications

2022

1. ICDSAI

   

   Strengthening Deep-Learning-Based Malware Detection Models Against Adversarial Attacks

   R. Pai, M. Purohit, and P. Vinayakray

   In Advances in Data Science and Artificial Intelligence , 2022

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   Detecting malware is no easy feat as there are many families with exponentially more variants. Much research has been carried out into deep-learning-based malware detection models due to their ability to handle large volumes of data and learn complex features. However, classical deep learning models are unable to adapt to malware variants and specially crafted adversarial samples. Moreover, these models have been trained on older and much smaller datasets. Therefore, there is a need for new models capable of withstanding adversarial attacks while providing accurate results. Hence, we propose a model trained on the latest dataset, capable of handling various malicious adversarial samples while providing a low false-positive rate and high precision, recall, and F1 score.

2021

1. ICAC3

   

   Vigila: Application for General Safety

   R. Pai, A. Naik, H. Sandesara, and S. Dholay

   In 2021 International Conference on Advances in Computing, Communication, and Control (ICAC3) , 2021

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   Most safety applications already existing in the market send SOS messages to the victim’s saved contacts and the police, which could prove to be slow in situations which demand urgency. We propose a system to counter this and to respond to such emergencies. We store real-time location of our users and when anyone presses the SOS button, all users in a 100 meter radius, around that user, are notified about the emergency along with the coordinates of the victim. Our application also maintains a comprehensive first-aid and emergency response guide which the users can peruse so they can be more helpful in such situations.