How to collaborate
We are excited to announce the list of collaboration opportunities in our Mon(IoT)r IoT lab. These can be interesting opportunities to get exposed to cutting-edge IoT technologies and understand how they work.
For the Summer and Fall 2022 terms we are following Northeastern University regulations for on-site and remote work, this means that, unless something changes, students can conduct their research on-site in our lab under direct supervision of our team.
If you are interested in any of these projects, you are a current active student at Northeastern University, and you satisfy the prerequisites for the project you are interested in, please send an email to firstname.lastname@example.org with subject “Summer 2022 Mon(IoT)r Lab collaboration” or “Fall 2022 Mon(IoT)r Lab collaboration” and a recent resume attached (with GPA), specifying the following:
- What project you are interested in, why you are interested in that particular project, why you are a fit for that project, how you plan to use your existing experience to contribute to that project, how collaborating to the project aligns with your career goals. If you are interested in more than a project, please rank them starting from the one you are interested the most.
- The preferred start date and end date for the collaboration, and the total number of average hours you plan to spend per week on this project;
- Your expected course load for the semester (number of classes and credits)
- Any other time commitments you have during the semester, for example TA, RA in another group, or a co-op;
- Your availability for a volunteer position, or for a paid/for credits position.
- The possibility or preference to work on site, remotely, or both.
Please note that, in general, we have a preference for projects that are on-site, that last the whole semester, and for a minimum of 10 hours per week. Also, for first-time collaborations in our lab we usually prefer to start with a volunteer position first, and then consider other types of positions if the initial volunteer project is successful.
We will be reviewing applications for Summer 2022 and Fall 2022 as soon as we receive them until the positions are filled. Sometimes it may take us up to two weeks to get back to you, so please be patient if you do not hear back by then.
If you are interested to apply for Spring 2023 or later, we cannot guarantee that this list of projects will still be valid, and therefore we suggest to wait for the projects to be updated before applying (usually one month before the semester starts).
Current open projects
Project 1. Internet of Things analysis from network traffic
Internet of Things (IoT) devices are increasingly found in homes, providing useful functionality for devices such as TVs, smart speakers, and video doorbells. Along with their benefits come potential risks, since these devices can communicate information (audio recordings, video recordings, television viewing habits) about their users to other parties over the Internet. However, understanding these risks is difficult due to heterogeneity in devices’ online behaviors. For example, smart speakers responding to voice commands send very different network traffic than a smart power plug that is activated via a companion app.
The goal of this project is to measure what IoT devices are doing, simply based on the network traffic they generate. For example, we would like to know if a smart speaker is recording audio from users when it should not, and we can automatically infer this if we have a good model and analysis of what normal, expected recording behavior looks like.
This project will have several outcomes, including published source code and data, published research papers in academic venues, and press articles about our findings through our journalist partners at the New York Times and other prominent venues.
Some available research directions for this project that a student can choose are:
- PROJECT 1A (ongoing): Detect the presence and analyze the network traffic that groups of IoT devices exchange with each other.
- PROJECT 1B (new): Analyze if an IoT device behaves differently when deployed on an IPv6 network with respect to an IPv4 network.
- Familiarity with the most important Internet and networking protocols and measurement tools (Ethernet, TCP/IP, DNS, Wireshark/tshark).
- Extensive programming experience (python recommended).
- Strong interest in network security (e.g., traffic filtering, man-in-the-middle, intrusion detection).
Project 2. Voice Assistant User Profiling
Voice assistants such as Amazon’s Alexa, are becoming increasingly pervasive in our homes. While convenient, these systems also raise important privacy concerns. One of them is understanding to what extent they use or share information from past user interactions.
To perform this investigation, the student will focus on the three most popular voice assistants (Amazon Alexa, Google Assistant, Apple Siri), accessing them using any of the interfaces available to us, including smart speakers, mobile apps, integration SDKs.
This project is organized into three research activities: (1) the creation of user profiles, such as a list of questions aimed at simulating particular user profiles, followed by experiments to actually expose the voice assistants to such questions; (2) the creation of a way to probe the voice assistants for evidence of customization, such as curating a list of control questions, followed by experiments to check if the voice assistants exhibit any sign of profiling; (3) search of evidence of profiling also beyond the voice assistants, for example searching for targeted advertising in Amazon and Google searches.
This research will be performed in the Mon(IoT)r Lab (https://moniotrlab.ccis.neu.edu/), where the student will have access to all the smart speakers that are needed for this project.
Although not a strict requirement, we recommend basic knowledge of python, bash, and/or Selenium, which will help to automate some of the manual tasks that may be necessary for discovering instances of user profiling.
Project 3. Visualization of Internet of Things traffic
The goal of this project is to visualize traffic statistics of IP-based IoT devices both in real time and offline. For example, visualizing statistics about incoming and outgoing traffic for each IoT device on a local network on a responsive web application and/or phone app. Statistics include traffic averages, traffic spikes, amount of traffic by device and by destination. The purpose is to give a tool to visualize what is happening / has happened on an IoT network.
To achieve this goal, the student will be given access to a tool we have previously developed, and will be responsible for learning how it works and adding improvement to its frontend or backend components.
This project will require work on both the backend and the frontend part of our existing tool, but it can be more backend or frontend focused, based on the student’s interests.
- For the backend, familiarity with Node.JS, in-memory (e.g., Redis) and noSQL (e.g., MongoDB) databases.
- For both: extensive programming experience.