B.Tech + M.Tech , 2016
Indian Institute of Technology - Bombay
I am a Ph.D student at University of Wisconsin-Madison majoring in Computer Science. My hometown is Jaipur, Rajasthan, India; also known as the pink city due it’s trademark building color. I started my graduate school in 2016 with research in Neutrino Physics where I worked on the Askaryan Radio Array, an experiment located at the geographic South Pole. During the next two years, I even got the opportunity to visit the South Pole(!). Currently, I am working towards my Ph.D in Computer Science under the supervision of Prof. Kassem Fawaz. Some of the key projects that I have been working on are listed below. For more information, you can visit my personal webpage here.
In this project, we are lookings at online users’ interaction with privacy controls. Online service providers offer online menus and forms so users can control their privacy settings. However, in their current form, privacy control settings suffer from usability and reachability issues, making it hard for users to exercise informed control. To mitigate this and make the privacy controls more usable, we designed and developed PriSEC - a privacy setting enforcer that transforms privacy control pages from domains using machine learning techniques into a machine-readable format. Applications can be built on this machine-readable format to enhance the user experience. We demonstrated this by developing a browser extension that leverages a search interface where the users can easily select and enforce the desired setting.
Online services utilize privacy settings to provide users with control over their data. However, these privacy settings are often hard to locate, causing the user to rely on provider-chosen default values. In this work, we train privacy settings centric encoders and leverage them to create an interface that allows users to search for privacy settings using free-form queries. To achieve this, we create a custom Semantic Similarity dataset, which consists of real user queries covering various privacy settings. We then use this dataset to fine-tune the state of the art encoders. Using these fine-tuned encoders, we perform semantic matching between the user queries and the privacy settings to retrieve the most relevant setting. Finally, we also use these encoders to generate embeddings of privacy settings from the top 100 websites and perform unsupervised clustering to learn about the online privacy settings types.
In this project, we studied the impact of the General Data Protection Regulation (GDPR) on the landscape of privacy policies online. We conducted the first longitudinal, in-depth, and at-scale assessment of privacy policies before and after the GDPR. We gauged the complete consumption cycle of these policies, from the first user impressions until the compliance assessment. To achieve this, we created a diverse corpus of two sets of 6,278 unique English-language privacy policies from inside and outside the EU, covering their pre-GDPR and post-GDPR versions. We further developed a workflow for the automated assessment of requirements in privacy policies using natural language processing techniques.
PriSEC: A Privacy Settings Enforcement Controller
Rishabh Khandelwal, Thomas Linden, Hamza Harkous, Kassem Fawaz
USENIX Security, 2021
Surfacing Privacy Settings using Semantic Matching
Rishabh Khandelwal, Asmit Nayak, Yao Yao, Kassem Fawaz
Thomas Linden, Rishabh Khandelwal, Hamza Harkous, Kassem Fawaz
Sterile neutrinos in astrophysical neutrino flavor
Carlos A. Argüelles, Kareem Farrag,Teppei Katorid, Rishabh Khandelwal, Shivesh Mandalia and Jordi Salvado
Journal of Cosmology and Astroparticle Physics, 2020
Optimization of an ARA like Radio Neutrino Detector in Ice
Rishabh Khandelwal, Ming-Yuan Lu, Albrecht Karle
35th International Cosmic Ray Conference 2017
Askaryan Radio Array neutrino detector: status and design considerations for the future
Rishabh Khandelwal, Lu, Ming-Yuan, Karle, Albrecht, ARA Collaboration
APS April Meeting 2018