Configuring DDoS and BotNet Detector Based on QoE
The detector allows automatic monitoring of incoming traffic, identifying DDoS attacks, and quickly taking measures to protect the network. When a threat is detected, the system can fully isolate the malicious stream or clean the traffic while maintaining service availability for users.
The solution requires SSG version BASE, COMPLETE, or BNG with additional options and is deployed on an existing server with QoE.
1. Updating QoE
On the QoE server.
Update QoE to the latest version, stopping the receivers beforehand. Before starting receivers, patch ClickHouse:
dnf --refresh install clickhouse-patched
Start the receivers.
2. Updating GUI
On the GUI server.
Update GUI to the latest version. Connect GUI to VAS Cloud if not already connected. Enable the aniddos license option.
In the file /var/www/html/dpiui2/frontend/env.js set the option AppEnv.DDoSAttack_isVisible = 1;
3. Installing the Detector
On the QoE server.
Install the mitigator package fastm_qoe on all nodes:
dnf install fastm_qoe
Switch Python version:
dnf install -y python39 python39-devel -y sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.6 60 sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.9 70 sudo update-alternatives --config python3
Select version 3.9:
python3 --version
4. Configuring the Detector
On the QoE server.
On all nodes, or on selected ones:
- Edit the file
/var/fastm_qoe/etc/.env.
It should contain the following:ANALYZER=avg-based-z-score ANALYZER_RULES_KEY=avg-based-z-score-any IDLE_MODE=1 FORCE_MODE=0 DB_DROP_TABLES=1 FM_ATTACKS_METRICS_BY_SUBS_FILTER="and has_attack = 0" FM_ATTACKS_METRICS_BY_SUBS_LIMIT=1 FM_ATTACKS_METRICS_BY_SUBS_COLLAPSE=1 FM_ATTACKS_METRICS_BY_SUBS_DAY='day_'
- Update schema:
fastm-db-scheme
- Enable metrics collection
Add to file/var/qoestor/backend/.envthe following:FM_FULLFLOW_HOOK_ENABLE=1 GEO_IP_DIC_AUTOLOAD_ENABLED=1
Execute the daily cron:
sh /var/qoestor/backend/app_bash/cron_daily.sh
Collect metrics for several hours, ideally 24 hours. Then edit
/var/fastm_qoe/etc/.envagain and change 2 parameters:IDLE_MODE=0 DB_DROP_TABLES=0
This activates the detector.
5. Trigger Thresholds
In the file /var/fastm_qoe/lib/rules/config.json, edit the section avg-based-z-score-any as follows:
"avg-based-z-score-any": {
"octets": { "th": 100, "weight": 0.1 },
"octets_dropped": { "th": 1000, "weight": 0.3 },
"packets": { "th": 100, "weight": 0.3 },
"packets_dropped": { "th": 1000, "weight": 0.3 },
"flows": { "th": 100, "weight": 0.4 },
"sessions": { "th": 100, "weight": 0.4 },
"duration": { "th": 100, "weight": 0.01 },
"host_ips": { "th": 100, "weight": 0.3 },
"protos": { "th": 100, "weight": 0.3 },
"bits_sec": { "th": 100, "weight": 0.05 },
"bits_dropped_sec": { "th": 1000, "weight": 0.05 },
"packets_sec": { "th": 100, "weight": 0.05 },
"packets_dropped_sec": { "th": 1000, "weight": 0.05 }
},
6. Metrics Storage (DDoS Attack Logs)
In the GUI web interface, configure storage of raw and aggregated metrics, as well as raw and aggregated attack logs.
In Admin → GUI Configuration → QoE Stor: set DB retention time values as follows:
QOESTOR_FM_ATTACKS_MAIN_LOG_PARTITIONS_LIFE_TIME_HOUR=720QOESTOR_FM_ATTACKS_AGG_LOG_PARTITIONS_LIFE_TIME_DAYS=30QOESTOR_FM_METRICS_MAIN_LOG_PARTITIONS_LIFE_TIME_HOUR=72QOESTOR_FM_METRICS_AGG_LOG_PARTITIONS_LIFE_TIME_DAYS=7
7. Attack Analysis
Detected attacks can be examined in the DDoS attack sections in QoE Analytics.
- Check the "TOP Attacks by Protocols" section
Also sort by session count. Note these protocols. - Check the Attack Log
Filter by previously selected subscribers and protocol.
Here you can get attack details and make additional conclusions to take actions.
For example, the screenshot below clearly shows port scanning on the same address via UDP protocol. In this case, it is sufficient to place the attacker IP into a separate AS and set it to drop.
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