{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:ZPDJLWAOB2HIXZPZBPDW3EZWUQ","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"22063c3f538b02ab9110098a1e8f028735e9de9e3a3c24aecb1d49559c028801","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2026-05-21T20:16:14Z","title_canon_sha256":"408e609db5d15bdf7126cab06184dfc1c7e3ad1a4138cd1829a8580a374cf2fc"},"schema_version":"1.0","source":{"id":"2605.23004","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.23004","created_at":"2026-05-25T02:01:34Z"},{"alias_kind":"arxiv_version","alias_value":"2605.23004v1","created_at":"2026-05-25T02:01:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.23004","created_at":"2026-05-25T02:01:34Z"},{"alias_kind":"pith_short_12","alias_value":"ZPDJLWAOB2HI","created_at":"2026-05-25T02:01:34Z"},{"alias_kind":"pith_short_16","alias_value":"ZPDJLWAOB2HIXZPZ","created_at":"2026-05-25T02:01:34Z"},{"alias_kind":"pith_short_8","alias_value":"ZPDJLWAO","created_at":"2026-05-25T02:01:34Z"}],"graph_snapshots":[{"event_id":"sha256:9ca1c6041c2da121ec021e40e4807ba8c206d529f7b9de25335d7153cebaa354","target":"graph","created_at":"2026-05-25T02:01:34Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2605.23004/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Botnets are among the most persistent cyber threats, enabling large-scale attacks such as spam, credential theft, and distributed denial-of-service (DDoS). While deep learning approaches have recently been applied to botnet detection, they are computationally intensive and often lack interpretability. We present a comparative study of lightweight machine learning models including Logistic Regression, Decision Tree, and Random Forest on the CTU-13 dataset, a benchmark for botnet traffic analysis. We extract interpretable flow-based features and evaluate each model on detection accuracy, precisi","authors_text":"Naveen Kumar Chaudhary, Subhash Gurappa, Sundararaj Sitharama Iyengar, Yashas Hariprasad","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2026-05-21T20:16:14Z","title":"Botnet Detection on CTU-13 Using Lightweight Machine Learning Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.23004","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:4973140350f48e5ed3d6b00639e5f6dd559d2ac27c651047b719cf9241b6487c","target":"record","created_at":"2026-05-25T02:01:34Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"22063c3f538b02ab9110098a1e8f028735e9de9e3a3c24aecb1d49559c028801","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2026-05-21T20:16:14Z","title_canon_sha256":"408e609db5d15bdf7126cab06184dfc1c7e3ad1a4138cd1829a8580a374cf2fc"},"schema_version":"1.0","source":{"id":"2605.23004","kind":"arxiv","version":1}},"canonical_sha256":"cbc695d80e0e8e8be5f90bc76d9336a435373fdf3f6a7eb8698d30ebbd800f43","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cbc695d80e0e8e8be5f90bc76d9336a435373fdf3f6a7eb8698d30ebbd800f43","first_computed_at":"2026-05-25T02:01:34.060377Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-25T02:01:34.060377Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IS/l9FJHmRfSkPRefqiXeNKhqaJN130qkUSs8BnQxqRmkLNR/utjifGVcV8cgZNLPtyWTEefU2qMN4pA6grGDQ==","signature_status":"signed_v1","signed_at":"2026-05-25T02:01:34.061118Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.23004","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4973140350f48e5ed3d6b00639e5f6dd559d2ac27c651047b719cf9241b6487c","sha256:9ca1c6041c2da121ec021e40e4807ba8c206d529f7b9de25335d7153cebaa354"],"state_sha256":"defa8f59ac8d6a9b60dd4d56de21fb4c581a8f636ecbfeef8642a2a0cec2f4c8"}