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ExamSecure

ExamSecure

Automated Virtual Proctoring System

ExamSecure is a platform for conducting secure remote examinations and deter candidates from resorting to malpractice.

ExamSecure uses the following techniques to prevent cheating by the candidates -

  1. Complete Browser Lockdown: In the exam environment, ExamSecure completely locks down the candidate's browser, triggering a warning if the candidate tries to switch tabs, open a new window, exit full screen mode or click anywhere else except the Exam screen. Text Selection, Text Copying, and Right Click is also disabled in Exam environment.

  2. Multiple Persons Detection: Furthermore, ExamSecure uses the candidate's camera feed to perform advanced image analysis in real time to determine if there are multiple people in the candidate's frame, or if there is no one in the candidate's frame.

  3. Impersonation Detection: At the start of the exam, the candidate's face features are saved and if the detected face during the examination do not match the initial face, it triggers an Impersonation Warning.

  4. Head Pose Estimation: Using Head Pose estimation, ExamSecure is able to detect the direction in which the candidate is facing and triggers a warning if the candidate is staring away from the screen for long periods of time. This works by using Rekognition to define the human head's rotation in a 3D plane with respect to the camera in terms of the three Euler Angles: Yaw, Pitch and Roll and then using these three angles to determine the direction where the candidate is facing.

  5. Electronic Objects Detection: ExamSecure is also able to detect Electronic objects like Mobile Phones, Earphones in the candidate's camera frame and trigger a warning.

It uses the AWS Rekognition API for Object Detection, Person Detection, and Face Analysis.

In addition to the anti-cheating mechanisms, ExamSecure also has the features you might expect in an e-exam software.

  • ExamSecure automatically syncs the candidate's answers with the server as he/she is attempting the test. The timer is synced as well. So, if there is a loss of connectivity in between, the candidate can continue from where he left off.
  • Educators who are monitoring the exam can disqualify candidates if they find any camera frames to be objectionable.

... and many more features to be added soon.

Note: ExamSecure is currently a Work In Progress. It is deployed here but only authorized test candidates are given access. If you want to test it, please follow these steps to run ExamSecure locally.

Screenshots

Following is a sneak peek of how the interface looks.

Home, Log In Allow Camera Permissions
Pre-Exam Instructions Exam Interface
Impersonation Warning Image Analysis Demo
Mobile Detected Force Logout

For more, check out the Demo Videos page, and the Image Analysis Demo

Running ExamSecure Locally

Note: Running this project will require you to set up and configure the required AWS resources.

  1. Clone the project.
  2. Run npm install to install all required dependencies.
  3. Configure AWS and put required details in public/settings.js.
  4. Run npm start.

The project should run now. In case of any error, make sure your AWS configuration is correct.

AWS Configuration

This project uses many AWS services - S3, CloudFront, Rekognition, Lambda, Cognito, DynamoDB, API Gateway, and CodePipeline. To make the configuration process easy, a CloudFormation stack template is provided. All you need to deploy that template and CloudFormation will take care of the rest!

  • First, you need to make a S3 bucket which contains the build files of the React app. Follow this documentation by AWS for more details.

    • To get the build files, run npm run build. Build files will be /build

  • Now that you have the S3 bucket details, you need to create a CloudFormation stack which will manage all the resources we need. I have provided the stack template at cloudformation/template.yaml in this repository. Follow the steps given this documentation by AWS to deploy this template. During the creation of stack, it will ask you for S3 Bucket URL. You have to provide the URL got in the prior step.

  • Once the Stack Creation process is complete, create a file settings.js in your public folder and paste the details from the Clouformation console output in the following format -

window.rekognitionSettings = {
    "apiGateway": "YOUR_API_GATEWAY",
    "cognitoIdentityPool": "YOUR_COGNITO_IDENTITY_POOL",
    "cognitoUserPoolId": "YOUR_COGNITO_POOLID",
    "cognitoUserPoolClientId": "YOUR_COGNITO_POOL_CLIENDID",
    "region": "YOUR_AWS_REGION"
};

Challenges & Learnings

  • Increasing Complexity of State Management: Initially, I used simple React state. However, as I added more and more features, the state management became increasingly complex and I was facing issues like prop drilling on a regular basis. More time was being spent on refactoring components in a way to enable them to share state, than on implementing new features. So, I learned and integrated Redux into the project. The concept of global state store made it easy to add new features. (Although I still use simple React state for managing ephemeral state)
  • Locking Down the Browser: The requirement was that the user should not be allowed to do anything else while attempting the exam. To implement this, I learned about a lot of DOM APIs for Full Screen, Focus Lost, Context Menu, Text Selection, etc.
  • AWS Rekognition & Lambda: For the server side, I've used AWS Lamdba along with AWS API Gateway. For real time image analysis, AWS Rekognition is used. This project allowed me to learn a lot about these AWS services and the "serverless" paradigm.

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