On 2025-06-24 09:27, evabouchard38--- via NANOG wrote:
Hi all,
I'm part of a postgraduate team at Dublin City University working with
Chirp, a startup developing real-time, embedded child-protection
software for telecom operators. The solution analyzes data traffic on
children’s devices to block harmful content and alert parents to risks
such as grooming, cyberbullying, or self-harm — all while respecting
privacy and working natively within telco infrastructure.
As part of our MSc practicum, we’re seeking feedback from telecom and
network professionals on the commercial, technical, and regulatory
feasibility of such an approach.
Would you be open to completing a short, 10-minute questionnaire?
🔗 https://dcusurveys.qualtrics.com/jfe/form/SV_8oBhWiZMRrUh1zM
From the content of the survey and your website, your team seems well
aware of where your app sits in the network stack: on the user's device,
not in telco space.
Honestly, the survey reads a bit like a sales pitch to residential ISP
product managers. I'm mildly curious what they would think of offering
this app.
Does your solution require equipment deployed on the ISP network?
We’d be very grateful for your insights. Happy to follow up with more
technical or contextual details if helpful.
Personally, I haven't found any value in my home ISP's value-added
services (like Norton Anti-Virus). But that would certainly vary by
locale.
Also, historically, I know pattern matching software works well when the
content to be filtered is relatively static, like malware. Pattern
matching works less well with images, audio, and human-generated text.
As an engineer, I would want a more thorough description of your
filtering strategies to understand why your app might work where others
have failed. Real-world false-positive and false-negative rates would be
key if I were a parent. Any LLM integration would also need to be
detailed, to understand where a child's data might be shipped for
analysis.
Thanks in advance for your time!
Best regards,
Eva Bouchard
Thanks,
-Brian
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