Methods to track behind cheating on exams using on-line sites? In the current state of the technologies, what ways can be used to track clear yet directly untraceable cases of academic misconduct specific to students who post questions from and view answers to a take-home exam using on-line (homework) sites?

My case is specific to Chegg, although answers related to other on-line sites would be certainly welcomed.

As a background, I have a list (from Chegg) of the email address, log-in times, university affiliation, and question posted / viewed. I can clearly correlate the posting information to being from my exam during my exam. I can directly correlate some cases because the email address is ... surprisingly ... the student's university email address or their personal email address. What I do not have in some cases is a) a valid or directly representative email address and b) a full name.

I have a roster list of students and have diligently checked their email addresses against the offending emails to no avail. I will pass the roster and list to our administration to review against their (larger) database of email accounts. However, I can only imagine that an email address could be from a neighbor or friend or roommate or ... someone entirely untraceable in the full university email database.

After a formal inquiry to obtain the above list, I have an email response (from Chegg) that tells me that I will get no further help to obtain any other information. I will be glad to hear about other levers that can be pulled to get better information.

I can accept that at some point I may have to conceed that I am simply out of luck to track the real perpetrator. But, before I do so, I have to wonder whether this community has insights to additional resources to help solve my problem.

To help also focus the discussion further, I am not interested to learn about the ways to avoid this problem in the future. I have my own insights and plans to move forward on this front. I am also not interested to spend time trashing Chegg or equivalent sites, deserving or not.

Finally, in addition to the specific question on additional effective methods, I am also interested in one other broader aspect of the problem. I am curious to hear from like-minded individuals who have initiated or are aware of actions being initiated for a larger academic community stand against the problem. I make this latter statement especially as we faculty are all most likely to have to face yet another round of on-line teaching for the coming Fall 2020 semester.

In summary, I hope to hear about approaches that others have used that could also help me solve my problem to track perpetrators of cheating who, up to this point, are essentially directly untraceable.
I can think of a few approaches that might help. I'm not sure pursuing the sites used will be very fruitful. There are always disposable emails they can sign up with, Tor exit nodes they can route traffic through etc. It's a fool's errand.

Oral interviews post-exam

Ask a random sample of students for an interview after they've submitted their answers. With the script in front of both of you, ask them about their thought process when answering the question and evaluate the extent to which they can confidently discuss the subject.

Cons: time-consuming, potential for false positives from students who forget most of the content after taking the exam/have other assessments to study for/don't cope well with the interview pressure.

Issue unique questions per student

If you have control over the online assessment platform, you may be able to issue unique questions per student to catch out blatant copy-pasting of the question text in order to publicly outsource an answer. I am not proposing that a paper is manually put together per student; this seems like something you'd want to automate.

Cons: the ability to do this well will vary from subject to subject. It might be easy to generate lots of linear programming problems of comparable difficulty if your exam e.g. assesses the student's ability to apply the Simplex algorithm. But, explanation questions may be more difficult and lead to a perception that some students unfairly get 'easier' or 'harder' papers.