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Analyzing Privacy Vulnerabilities of Third-Party Skills in Alexa

Privacy Project for CSC 533

Smart speakers have been popularly used around the world, mainly due to the convenience brought from the virtual personal assistant (VPA) which offers interactive actions through the convenient voice commands from users. Besides the built-in capabilities, VPA services can be further extended by third-party developers through skills. These skills attract users together with malicious developers. We plan to implement a skill explorer to systematically explore the interaction behaviors of skills developed for Alexa and identify the ones which violate the users’ privacy. The skill explorer will analyze the Alexa skills listed on the Amazon marketplace.

Setup

If you wish to test the system with the sample privacy policies provided by the rpository, skip to the Execution step. If you wish add new privacy policies, follow the below instructions.

Obtaining the privacy policy

  1. Navigate to any skill on the Amazon market place
  2. Under the "Skill details" section, click on "Privacy Policy"
  3. A new tab opens in the browser displaying the privacy policy with an alpha-numeric Skill ID displayed in the URL. Save this page as an HTML document and name it as <skillID>.txt

Converting the privacy policy to plaintext

The project uses an external system known as PolicyLint to convert a privacy policy of a skill from HTML to plain text:

  1. Navigate to the PolicyLint project
  2. Follow the README to setup and execute the PolicyLint converter
  3. From the root folder of the project, copy the "plaintext_policies" folder located at /ext/plaintext_policies

Project setup

  1. Clone this repository
  2. Paste the "plaintext_policies" folder at the root level of the project

Execution

cd src
python3 main.py
Execute the ipython notebook in collab to get the Dependency and Parse Trees

Authors

  • Shivaprakash Balasubramanian
  • Varsha Anantha Ramu Sharma

License

This project is licensed under MIT License

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Project for CSC 533 Privacy

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  • Jupyter Notebook 73.5%
  • Python 26.5%