{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:E5M23VLVIMNQ5TINJAR6YXFDAY","short_pith_number":"pith:E5M23VLV","canonical_record":{"source":{"id":"2401.12790","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-01-23T14:25:43Z","cross_cats_sorted":[],"title_canon_sha256":"eb9d68b18dc9d9d924689ec53647529c99f8f3b0b39dd51f8e1b39a915969ce9","abstract_canon_sha256":"bcaf7cd7422c970562a8aed179b61368d3278d436e91d63874472f829c1f8403"},"schema_version":"1.0"},"canonical_sha256":"2759add575431b0ecd0d4823ec5ca3063d90b50756db2abbc00facd9d3e27c66","source":{"kind":"arxiv","id":"2401.12790","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.12790","created_at":"2026-07-05T07:36:36Z"},{"alias_kind":"arxiv_version","alias_value":"2401.12790v1","created_at":"2026-07-05T07:36:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.12790","created_at":"2026-07-05T07:36:36Z"},{"alias_kind":"pith_short_12","alias_value":"E5M23VLVIMNQ","created_at":"2026-07-05T07:36:36Z"},{"alias_kind":"pith_short_16","alias_value":"E5M23VLVIMNQ5TIN","created_at":"2026-07-05T07:36:36Z"},{"alias_kind":"pith_short_8","alias_value":"E5M23VLV","created_at":"2026-07-05T07:36:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:E5M23VLVIMNQ5TINJAR6YXFDAY","target":"record","payload":{"canonical_record":{"source":{"id":"2401.12790","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-01-23T14:25:43Z","cross_cats_sorted":[],"title_canon_sha256":"eb9d68b18dc9d9d924689ec53647529c99f8f3b0b39dd51f8e1b39a915969ce9","abstract_canon_sha256":"bcaf7cd7422c970562a8aed179b61368d3278d436e91d63874472f829c1f8403"},"schema_version":"1.0"},"canonical_sha256":"2759add575431b0ecd0d4823ec5ca3063d90b50756db2abbc00facd9d3e27c66","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:36:36.282070Z","signature_b64":"5WmBTsEQL/TJSS/k1SpJHAXY0Dg/0wJd5/v1mHFtePF+ONXK6i7OaJs1TLS+gkABHNwH6ZIzh17HzxePlMeSAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2759add575431b0ecd0d4823ec5ca3063d90b50756db2abbc00facd9d3e27c66","last_reissued_at":"2026-07-05T07:36:36.281647Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:36:36.281647Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2401.12790","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:36:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kY/5JNEPpFYwEP6g243+xPiPE7QRKUpWC27dY8RQLZzXSothUve3pefcPgzOHLYEAh7U7gcETfAGeEt1VVtbDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T19:53:56.941250Z"},"content_sha256":"b9b9c72ec0fc9dd506df649dce4a89fea7bcd29bee5bc1ef4f952fe4ee50ddb2","schema_version":"1.0","event_id":"sha256:b9b9c72ec0fc9dd506df649dce4a89fea7bcd29bee5bc1ef4f952fe4ee50ddb2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:E5M23VLVIMNQ5TINJAR6YXFDAY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MORPH: Towards Automated Concept Drift Adaptation for Malware Detection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Ashim Mahara, Md Tanvirul Alam, Nidhi Rastogi, Romy Fieblinger","submitted_at":"2024-01-23T14:25:43Z","abstract_excerpt":"Concept drift is a significant challenge for malware detection, as the performance of trained machine learning models degrades over time, rendering them impractical. While prior research in malware concept drift adaptation has primarily focused on active learning, which involves selecting representative samples to update the model, self-training has emerged as a promising approach to mitigate concept drift. Self-training involves retraining the model using pseudo labels to adapt to shifting data distributions. In this research, we propose MORPH -- an effective pseudo-label-based concept drift "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.12790","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2401.12790/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:36:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kqDWh5GiRBXc3OmWZ79yafK07T1MzkMHap6oOhuQQ9QFVcRHo/jf5CAfHXRgO6rcWZCXmsSrKcNVgy9/PtwhAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T19:53:56.941756Z"},"content_sha256":"488a84f54a5b54c9401272885c933be29d2138847dee37910d8fdfcf4b230319","schema_version":"1.0","event_id":"sha256:488a84f54a5b54c9401272885c933be29d2138847dee37910d8fdfcf4b230319"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/E5M23VLVIMNQ5TINJAR6YXFDAY/bundle.json","state_url":"https://pith.science/pith/E5M23VLVIMNQ5TINJAR6YXFDAY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/E5M23VLVIMNQ5TINJAR6YXFDAY/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-09T19:53:56Z","links":{"resolver":"https://pith.science/pith/E5M23VLVIMNQ5TINJAR6YXFDAY","bundle":"https://pith.science/pith/E5M23VLVIMNQ5TINJAR6YXFDAY/bundle.json","state":"https://pith.science/pith/E5M23VLVIMNQ5TINJAR6YXFDAY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/E5M23VLVIMNQ5TINJAR6YXFDAY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:E5M23VLVIMNQ5TINJAR6YXFDAY","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":"bcaf7cd7422c970562a8aed179b61368d3278d436e91d63874472f829c1f8403","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-01-23T14:25:43Z","title_canon_sha256":"eb9d68b18dc9d9d924689ec53647529c99f8f3b0b39dd51f8e1b39a915969ce9"},"schema_version":"1.0","source":{"id":"2401.12790","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.12790","created_at":"2026-07-05T07:36:36Z"},{"alias_kind":"arxiv_version","alias_value":"2401.12790v1","created_at":"2026-07-05T07:36:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.12790","created_at":"2026-07-05T07:36:36Z"},{"alias_kind":"pith_short_12","alias_value":"E5M23VLVIMNQ","created_at":"2026-07-05T07:36:36Z"},{"alias_kind":"pith_short_16","alias_value":"E5M23VLVIMNQ5TIN","created_at":"2026-07-05T07:36:36Z"},{"alias_kind":"pith_short_8","alias_value":"E5M23VLV","created_at":"2026-07-05T07:36:36Z"}],"graph_snapshots":[{"event_id":"sha256:488a84f54a5b54c9401272885c933be29d2138847dee37910d8fdfcf4b230319","target":"graph","created_at":"2026-07-05T07:36:36Z","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/2401.12790/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Concept drift is a significant challenge for malware detection, as the performance of trained machine learning models degrades over time, rendering them impractical. While prior research in malware concept drift adaptation has primarily focused on active learning, which involves selecting representative samples to update the model, self-training has emerged as a promising approach to mitigate concept drift. Self-training involves retraining the model using pseudo labels to adapt to shifting data distributions. In this research, we propose MORPH -- an effective pseudo-label-based concept drift ","authors_text":"Ashim Mahara, Md Tanvirul Alam, Nidhi Rastogi, Romy Fieblinger","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-01-23T14:25:43Z","title":"MORPH: Towards Automated Concept Drift Adaptation for Malware Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.12790","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:b9b9c72ec0fc9dd506df649dce4a89fea7bcd29bee5bc1ef4f952fe4ee50ddb2","target":"record","created_at":"2026-07-05T07:36:36Z","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":"bcaf7cd7422c970562a8aed179b61368d3278d436e91d63874472f829c1f8403","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-01-23T14:25:43Z","title_canon_sha256":"eb9d68b18dc9d9d924689ec53647529c99f8f3b0b39dd51f8e1b39a915969ce9"},"schema_version":"1.0","source":{"id":"2401.12790","kind":"arxiv","version":1}},"canonical_sha256":"2759add575431b0ecd0d4823ec5ca3063d90b50756db2abbc00facd9d3e27c66","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2759add575431b0ecd0d4823ec5ca3063d90b50756db2abbc00facd9d3e27c66","first_computed_at":"2026-07-05T07:36:36.281647Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:36:36.281647Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5WmBTsEQL/TJSS/k1SpJHAXY0Dg/0wJd5/v1mHFtePF+ONXK6i7OaJs1TLS+gkABHNwH6ZIzh17HzxePlMeSAg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:36:36.282070Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.12790","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b9b9c72ec0fc9dd506df649dce4a89fea7bcd29bee5bc1ef4f952fe4ee50ddb2","sha256:488a84f54a5b54c9401272885c933be29d2138847dee37910d8fdfcf4b230319"],"state_sha256":"855e3ff17c29d12203062af527f0521d526172fecc3577029e9e6b028ed9196d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lQoV+mgkuO08gu0MksTsVzw1ZwSCcm61r8xtrnNj6D0BFFdz1okmLuXxBH03+ApaibRKyLiqPxAfbXK6icHrBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T19:53:56.946052Z","bundle_sha256":"5faf9fbe07ee9b1c14044470fff2521dc8444c6abc7b0afff0da1ec85c973f76"}}