Thursday, March 23, 2023
HomePythonAnalysis Writeup: Deanonymization and Proximity Detection Utilizing Wi-Fi

Analysis Writeup: Deanonymization and Proximity Detection Utilizing Wi-Fi

Hello everybody! When you have been following my weblog for some time you’ll know that I did analysis at Colgate College over the summers. My analysis was on Wi-Fi and the way I can do some attention-grabbing stuff utilizing it. The college simply revealed its annual catalogue of all of the analysis tasks which occurred over the summer season. My analysis was performed beneath the mentorship of Aaron Gember-Jacobson. I couldn’t have requested for a greater advisor. Right here is the writeup of my venture:

In response to RAINN (Rape, Abuse & Incest Nationwide Community), 23.1% of feminine and 5.4% of male undergraduate college students expertise rape or sexual assault, with solely a minute share reporting their assault to regulation enforcement1. In sure instances, survivors can overlook who the perpetrator was as a result of trauma and/or intoxication. I wish to use know-how to counter this drawback. My hope is to scale back the variety of potential culprits when such an incident happens to make it simpler for the survivor to determine the perpetrator.

This may be made attainable through the use of a tool that most individuals carry always – a smartphone. The thought is to save lots of the gadget identifier and the space between your telephone and that of every one who comes close to you in a searchable database. This enables you, the consumer, to seek for which gadget was close to you at a selected time. The analysis is additional divided into two components. The primary concerned discovering a strategy to successfully calculate the relative distance between two smartphones and the second concerned data storage and querying. I targeted primarily on the primary half, which turned out to be harder and concerned than I anticipated.

The cornerstone of this concept is Wi-Fi and the knowledge your smartphone emits when the Wi-Fi is turned on, although not essentially linked to an entry level. The formal necessities of this technique are as follows: it must be passive so that you don’t should actively monitor it; it shouldn’t require different folks’s smartphones to run any particular utility; the error in distance estimation must be lower than 1 meter so the algorithm can precisely determine a human interplay; the system must work in NLOS (Non-line-of-sight) eventualities since folks usually have their smartphones of their pockets; lastly, it shouldn’t require greater than three units, together with your smartphone, a close-by smartphone, and a Wi-Fi Entry Level to which each telephones are linked, as a result of the system must be transportable.

Earlier analysis in relative distance estimation presents various ranges of precision. One methodology includes utilizing RSSI (Obtained Sign Power Indication) readings from a number of entry factors (4+ for accuracy) and triangulating smartphone place based mostly on that. We can’t use this methodology as a result of 4+ units are required. One other methodology includes utilizing Time-of-Flight (ToF) measurements. There are a number of variations of this methodology, however the fundamental thought is to ship information out of your gadget to the gadget being localized, and recording the time taken for the info to journey from one gadget to a different and for an acknowledgment to be obtained. Primarily based on this timing measurement and the required time delay (generally known as SIFS, or Brief Interframe House) between a tool receiving information and sending an acknowledgement, we are able to estimate the space between two units. This offers the most effective accuracy however shouldn’t be straight relevant to this example, as a result of it requires a direct connection between the 2 smartphones.


I sought to develop a modified model of the ToF methodology, as a result of it presents the most effective precision and requires the least variety of units to work successfully. The strategy I developed was to ship unsolicited management packets (a particular kind of knowledge body) to the goal cellular gadget and power it to ship an acknowledgement (see determine). The key analysis query is: how can we power the goal gadget to ship an acknowledgement even when we aren’t straight linked to it?

I arrange a testbed with three desktops outfitted with Wi-Fi playing cards and operating Ubuntu Linux. I used Scapy (a Python program for producing community packets) to generate and ship management packets from one desktop to a different and tcpdump on the third desktop to observe and analyze the wi-fi communication happening. I used to be capable of ship the management packets and solicit an acknowledgment from the goal cellular (Ubuntu desktop) with out being straight linked to it.

Nonetheless, there was a bug within the networking drivers of Ubuntu that generated acknowledgments even in instances the place no acknowledgment was imagined to be despatched by the goal gadget. Presently, I’m investigating the bug and making an attempt to determine probably the most appropriate method ahead. Via this analysis, I discovered that the method of distance estimation is extra ****sophisticated than it appears. There are a number of variables and timing points that must be taken under consideration. Sooner or later, I plan on discovering a workaround for this bug, with the eventual aim of creating this technique usable in on a regular basis life.

When you have any questions on my analysis or something basically please write them within the feedback under. Wanting ahead to listening to your views! Have an ideal day/evening! 🙂



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