pith:QFB4EV6B
Self-Supervised Learning for Android Malware Detection on a Time-Stamped Dataset
Self-supervised pre-training on a time-verified Android app dataset delivers 98% accuracy and 89% F1 for malware detection under realistic time constraints.
arxiv:2604.23025 v2 · 2026-04-24 · cs.CR · cs.LG
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Claims
Under time-aware evaluation, the method attains 98% accuracy and 89% F1.
The timestamp-verification procedure produces a dataset whose temporal distribution matches real-world app release patterns and that BYOL pre-training yields obfuscation-resilient representations sufficient for the downstream classification task.
A verified time-stamped Android app dataset combined with BYOL self-supervised pre-training yields 98% accuracy and 89% F1 under time-aware malware detection evaluation.
Receipt and verification
| First computed | 2026-06-08T01:04:05.561629Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
8143c257c126eeda7cad0625ddde991220745679482e8fcc13fd34a17a4efc15
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/QFB4EV6BE3XNU7FNAYS53XUZCI \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 8143c257c126eeda7cad0625ddde991220745679482e8fcc13fd34a17a4efc15
Canonical record JSON
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