You said:

I am looking for posable ways to implement an idea for home internet security. The idea came up in a discussion about how the trend to use phone apps to do setup tasks presents a potential increase in opportunities for software exploits targeting home networks.

In a simple example, a home router does a fair job of being a firewall mostly just by implementing NAT protocols that keep out inbound traffic. But when a person adds an IOT device that allows remote operation, effectively firewall has a hole in it. In the worst case the IOT device at some point requests a host somewhere on the internet for any software updates. And the software update contains exploits a destructive kind. Say ransomware for our discussion, or an enemy state actor that just wants to disable home networks.

The problem seems to be that a typical home user does not have much of a way to know what internet traffic the devices on a network is happening. I have a new ASUS router, and I was interested to see that it has a basic traffic tracking function. But it seems more focused on finding excessive data use. Maybe someone using all the bandwidth running a web game. Or a bad phone app that is forwarding everything the camera can see.

I also have some familiarity with Wireshark and have had a collage class where we decoded some traffic. But the manual use of Wireshark is not well adapted to finding a stray packet here or there from something like a wall thermostat to an address in China.

It would seem that an expert system that is trained with knowledge of worldwide IP addressing could look at the stream and pick out things that a manual operator could not.

And now there is talk of running compressed AI models on PC level hardware. Such a model would probably need special training. There is also a certain element of learning or dynamic adaptation that is needed.

Maybe a distributed network between different nodes (home networks) to update other members when bad things are found on one node.

ChatGPT said:

You're describing a home-grade IDS/expert system that can (1) see everything on-net, (2) flag risky destinations (geo/IP/reputation), (3) learn each devices normal behavior, and (4) optionally share new bad indicators with other homes. Heres a practical, buildable path in layersfrom you can do this tonight to small-lab research with local AI.

0) Quick wins (weekend setup)

1.   Put IoT on its own VLAN/SSID

• On the ASUS: create an IoT guest SSID; disable Intranet access/Access to local network.
• Bonus: a Quarantine SSID for brand-new devices until vetted.

2.   Log all DNS, then enforce it

• Run Pi-hole or AdGuard Home on a tiny box (Pi/mini-PC). Point ASUS DHCP to that DNS.
• Turn on query logging + blocklists; add DoH/DoT to upstreams; enable never forward non-FQDN/private to catch odd beacons.
• Add a small GeoIP/ASN note in the logs (plug-in or sidecar script) so queries resolve to Country / ASN / Provider.

3.   Baseline reports, not packets

• Instead of diving into Wireshark, export NetFlow/IPFIX or conntrack summaries from the router (or mirror IoT VLAN to a tap) and visualize with ntopng.
• Youll get Top talkers, new destinations, long-lived flows without packet-level noise.

1) Expert-system style detection (rule + intel + geo)

Drop this on the same Pi/mini-PC that runs Pi-hole.

A) Suricata (IDS/IPS, rule-based)

• Run in IDS mode on the IoT VLAN mirror or on a gateway box.
• Load community rules (ET Open) and selectively enable policy categories (malware C2, crypto-miners, exploit kits).
• Set drop=off, alert=on first; route alerts to a local dashboard.

B) Zeek (behavioral scripting)

• Parallel to Suricata, Zeek generates rich logs (dns.log, conn.log, ssl.log).
• Add simple Zeek scripts:
• New external IP for a device (never seen before) → alert if country ∉ {US, CA, } or ASN on a deny list.
• Unexpected service (thermostat making SMTP or SSH) → alert.
• Beaconing (per-device periodic contacts every N seconds) → flag for review.

C) IP/Domain reputation + Geo policy

• Pull a small, curated threat feed (e.g., AbuseIPDB top offenders, PhishTank domains).
• Maintain local allowlist for your devices known vendors/CDNs to cut false positives.
• Add a soft geo-block policy: IoT VLAN may only egress to a short list of countries or vendor ASNs; everything else → log & prompt.

Deliverable: youll see Thermostat → *.cn CDN on TCP/443 (new ASN, new country) in human-readable alertsno packet spelunking needed.

2) Lightweight local ML (no cloud, runs on a PC)

Goal: learn normal per device and flag outliers. This is flow-level ML , not DPI.

Features to learn per device (daily rollups + short windows):

• Count of distinct remote IPs/domains, entropy of SNI, ports used, bytes up/down, mean/variance of flow duration, inter-arrival time, time-of-day histogram.

Model choices (on CPU; small, explainable):

• Isolation Forest or One-Class SVM per device for anomaly score.
• Optional: a tiny autoencoder (Keras/TensorFlow CPU) if you want.
• Train from your Zeek/ntopng summaries (CSV/Parquet). Refit daily; keep last 30 days.

Alert logic (keep it simple):

• If anomaly score > threshold and (new country/ASN OR new port/protocol) → raise High.
• Else if just anomaly score spike → Medium, review.

Explainability:

• Include top contributing features (e.g., Unusual: 14 new domains, port 8883 MQTT to ASxxxx, at 3:12am).

3) Policy enforcement loop (contain first, ask later)

• Start observe-only: alerts only.
• After a month of baseline: turn on auto-quarantine for IoT VLAN using router scripts or an OpenWrt/pfSense box in front of ASUS:
• When a High alert fires, move MAC to Quarantine VLAN (only DNS + captive portal).
• Show a local portal page: Device X tried to contact Y (Country/ASN). Allow once / Allow always / Keep blocked.
• Your choice becomes a rule (allowlist/denylist) and trains the model (label = benign/malicious).

4) Cooperative defense (privacy-preserving sharing)

You mentioned distributed network between homes. Heres a safe way:

Share only indicators, never raw traffic:

• Hash of domain (Bloom filter optional), ASN, port, time bucket, and anonymized device class (thermostat).
• Sign with a local key; publish via a tiny Mastodon-like or MQTT broker you control, or to a small trusted group.
• Your node subscribes and elevates scores when a peer reports the same indicator within, say, 24h.

Abuse/poisoning defenses:

• Rate-limit accepts from any single peer.
• Require ≥2 independent peers before auto-quarantine on shared intel.
• Decay reputation quickly (714 days) unless reconfirmed.

5) Where ASUS fits

• Many ASUS models support Traffic Analyzer, AiProtection, Adaptive QoS use these for quick visibility, but dont rely on them for reputation/geo/ML.
• If the model allows port mirroring or syslog/traffic export , mirror the IoT SSID/VLAN to your sensor box.
• If not, place a tiny inline bridge (OpenWrt mini-PC) between the WAN and ASUS or between ASUS and your IoT AP; that bridge runs Suricata/Zeek/ntopng and enforces egress.

6) Hardware sketches (quiet + cheap)

• Sensor/Analyzer box : fanless mini-PC (Celeron/Jasper Lake or N100, 816 GB RAM, dual NICs).
• All-in-one option : Replace/augment the router with OpenWrt on that mini-PC + your ASUS as AP only. Gives you first-class VLANs, mirror ports, Suricata at line rate for home speeds.
• Storage : keep 714 days of logs; rotate with logrotate/S3-compatible NAS if desired.

7) Concrete first build checklist

• Create IoT + Quarantine SSIDs on ASUS; block LAN access.
• Stand up Pi-hole/AdGuard; point DHCP to it; turn on logging.
• Deploy ntopng; ingest flows from router or bridge; email a daily New Destinations by Device report.
• Mirror IoT VLAN to Suricata + Zeek; enable ET Open + minimal Zeek scripts (new-country, new-service, beaconing).
• Write a 50-line Python job: roll up Zeek logs per device → train Isolation Forest → output anomalies.
• Add a one-click quarantine script (MAC → VLAN). Test on a spare IoT bulb.
• (Optional) Add a tiny web portal to review/approve blocks and generate allow/deny rules.

8) Why this works for the thermostat-to-China scenario

• DNS/flow logs: instantly show new country/ASN and never-seen domain.
• Rules: Suricata/Zeek catch odd protocols or suspicious TLS patterns.
• ML: if its a one-off beacon at 3 AM with unusual flow duration/size, the model elevates it.
• Enforcement: device is auto-moved to Quarantine; you get a clear, human-readable alert; you decide to allow/deny.

If you want, I can generate any of these ready-to-run bits next:

• Minimal Zeek scripts (new country/service/beaconing).
• A Python notebook that ingests Zeek logs and trains an Isolation Forest, plus a small HTML report.
• An OpenWrt firewall/VLAN script + quarantine/restore buttons.

Tell me which deliverable youd like and your exact ASUS model, and Ill tailor the commands/config to your setup.

You said:

This is very helpful for a start, I like the approach that builds on simple starting points. I am familiar with a lot of what you have said but will need to study in detail to better see the interaction. I already have my DNS pointed to a PiHole, but you are indicating that there is a lot more I can do with it. It will take me some time to work through. Could you format my question and your response for me as both a .pdf and an HTML page I can put on my website as you have done previously.

ChatGPT said:

All set! Here are your files, ready to post or share:

• Download the HTML
• Download the PDF

If youd like a different title, added table of contents, or your name/date in the header/footer, say the word and Ill regenerate both.