{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:AUIFO5XGFZLG6TU4RF4XFL2FEJ","short_pith_number":"pith:AUIFO5XG","canonical_record":{"source":{"id":"2404.13125","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-04-19T18:28:38Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e8e43a62bef653f0a6bbb3a1f19fed76f89b1205d76e2450e0c7fad99c379356","abstract_canon_sha256":"0f1d30ce7656aeef289d7d9cc953a1c2ce8d881a3ad541935c1db860748cc291"},"schema_version":"1.0"},"canonical_sha256":"05105776e62e566f4e9c897972af4522751dddee56ec73b111f2545a1ba1cb81","source":{"kind":"arxiv","id":"2404.13125","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.13125","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"arxiv_version","alias_value":"2404.13125v1","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.13125","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"pith_short_12","alias_value":"AUIFO5XGFZLG","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"pith_short_16","alias_value":"AUIFO5XGFZLG6TU4","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"pith_short_8","alias_value":"AUIFO5XG","created_at":"2026-07-05T08:10:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:AUIFO5XGFZLG6TU4RF4XFL2FEJ","target":"record","payload":{"canonical_record":{"source":{"id":"2404.13125","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-04-19T18:28:38Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e8e43a62bef653f0a6bbb3a1f19fed76f89b1205d76e2450e0c7fad99c379356","abstract_canon_sha256":"0f1d30ce7656aeef289d7d9cc953a1c2ce8d881a3ad541935c1db860748cc291"},"schema_version":"1.0"},"canonical_sha256":"05105776e62e566f4e9c897972af4522751dddee56ec73b111f2545a1ba1cb81","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:10:27.534146Z","signature_b64":"RvLBTg0G4VLoMA83VeIL4ic0AKeHOdRd7P0kt5YXN0orqxcm/tujnGMC9u//VxelycVW7IXghzOgfW8gbVuuBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"05105776e62e566f4e9c897972af4522751dddee56ec73b111f2545a1ba1cb81","last_reissued_at":"2026-07-05T08:10:27.533690Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:10:27.533690Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.13125","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":"2026-07-05T08:10:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6NJqvHNx4GSxFb2WjwB9EaCBfHD3Sq/vHAZXa/M/PXiPwyd9vexhUaweupWv+SkUDf/MKgka1ngbbADy05eyAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T23:24:33.409990Z"},"content_sha256":"9968a02c75be97c599771be54fcb5926b8980aec0f87de534d8a72a765493cc1","schema_version":"1.0","event_id":"sha256:9968a02c75be97c599771be54fcb5926b8980aec0f87de534d8a72a765493cc1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:AUIFO5XGFZLG6TU4RF4XFL2FEJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Robust Real-Time Hardware-based Mobile Malware Detection using Multiple Instance Learning Formulation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CR","authors_text":"Biswadeep Chakraborty, Harshit Kumar, Saibal Mukhopadhyay, Sudarshan Sharma","submitted_at":"2024-04-19T18:28:38Z","abstract_excerpt":"This study introduces RT-HMD, a Hardware-based Malware Detector (HMD) for mobile devices, that refines malware representation in segmented time-series through a Multiple Instance Learning (MIL) approach. We address the mislabeling issue in real-time HMDs, where benign segments in malware time-series incorrectly inherit malware labels, leading to increased false positives. Utilizing the proposed Malicious Discriminative Score within the MIL framework, RT-HMD effectively identifies localized malware behaviors, thereby improving the predictive accuracy. Empirical analysis, using a hardware teleme"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.13125","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/2404.13125/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":"2026-07-05T08:10:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NQVEFekNwoWRIxXHtVa0S8bVNA4CKe5F6grtVeixyTAuMCIoKPTvWGKM3SI06ATKQKZNfY9LtDqgfnGWGnowBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T23:24:33.410640Z"},"content_sha256":"1b1d92de8e2b24e88de6143e33eeae42bd448c505d15817c55660ed07b6da0cd","schema_version":"1.0","event_id":"sha256:1b1d92de8e2b24e88de6143e33eeae42bd448c505d15817c55660ed07b6da0cd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AUIFO5XGFZLG6TU4RF4XFL2FEJ/bundle.json","state_url":"https://pith.science/pith/AUIFO5XGFZLG6TU4RF4XFL2FEJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AUIFO5XGFZLG6TU4RF4XFL2FEJ/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":"2026-07-31T23:24:33Z","links":{"resolver":"https://pith.science/pith/AUIFO5XGFZLG6TU4RF4XFL2FEJ","bundle":"https://pith.science/pith/AUIFO5XGFZLG6TU4RF4XFL2FEJ/bundle.json","state":"https://pith.science/pith/AUIFO5XGFZLG6TU4RF4XFL2FEJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AUIFO5XGFZLG6TU4RF4XFL2FEJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:AUIFO5XGFZLG6TU4RF4XFL2FEJ","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":"0f1d30ce7656aeef289d7d9cc953a1c2ce8d881a3ad541935c1db860748cc291","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-04-19T18:28:38Z","title_canon_sha256":"e8e43a62bef653f0a6bbb3a1f19fed76f89b1205d76e2450e0c7fad99c379356"},"schema_version":"1.0","source":{"id":"2404.13125","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.13125","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"arxiv_version","alias_value":"2404.13125v1","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.13125","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"pith_short_12","alias_value":"AUIFO5XGFZLG","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"pith_short_16","alias_value":"AUIFO5XGFZLG6TU4","created_at":"2026-07-05T08:10:27Z"},{"alias_kind":"pith_short_8","alias_value":"AUIFO5XG","created_at":"2026-07-05T08:10:27Z"}],"graph_snapshots":[{"event_id":"sha256:1b1d92de8e2b24e88de6143e33eeae42bd448c505d15817c55660ed07b6da0cd","target":"graph","created_at":"2026-07-05T08:10:27Z","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/2404.13125/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This study introduces RT-HMD, a Hardware-based Malware Detector (HMD) for mobile devices, that refines malware representation in segmented time-series through a Multiple Instance Learning (MIL) approach. We address the mislabeling issue in real-time HMDs, where benign segments in malware time-series incorrectly inherit malware labels, leading to increased false positives. Utilizing the proposed Malicious Discriminative Score within the MIL framework, RT-HMD effectively identifies localized malware behaviors, thereby improving the predictive accuracy. Empirical analysis, using a hardware teleme","authors_text":"Biswadeep Chakraborty, Harshit Kumar, Saibal Mukhopadhyay, Sudarshan Sharma","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-04-19T18:28:38Z","title":"Towards Robust Real-Time Hardware-based Mobile Malware Detection using Multiple Instance Learning Formulation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.13125","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":"sha256:9968a02c75be97c599771be54fcb5926b8980aec0f87de534d8a72a765493cc1","target":"record","created_at":"2026-07-05T08:10:27Z","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":"0f1d30ce7656aeef289d7d9cc953a1c2ce8d881a3ad541935c1db860748cc291","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-04-19T18:28:38Z","title_canon_sha256":"e8e43a62bef653f0a6bbb3a1f19fed76f89b1205d76e2450e0c7fad99c379356"},"schema_version":"1.0","source":{"id":"2404.13125","kind":"arxiv","version":1}},"canonical_sha256":"05105776e62e566f4e9c897972af4522751dddee56ec73b111f2545a1ba1cb81","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"05105776e62e566f4e9c897972af4522751dddee56ec73b111f2545a1ba1cb81","first_computed_at":"2026-07-05T08:10:27.533690Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:10:27.533690Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RvLBTg0G4VLoMA83VeIL4ic0AKeHOdRd7P0kt5YXN0orqxcm/tujnGMC9u//VxelycVW7IXghzOgfW8gbVuuBA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:10:27.534146Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.13125","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9968a02c75be97c599771be54fcb5926b8980aec0f87de534d8a72a765493cc1","sha256:1b1d92de8e2b24e88de6143e33eeae42bd448c505d15817c55660ed07b6da0cd"],"state_sha256":"bb10482621d39f4d12082dbc9576a7d15f6ffec2408ffd8051e1874d468fb6af"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"txNDyopzoMHuoJRRhq5Suent25Lc6mbTGQvnpCPGsKCbwwpqcN95a3JC3nBMc+yGDqW4XKE1DSec9p9XF2n/Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-31T23:24:33.414867Z","bundle_sha256":"088976f088c88a8caba479d163a9b81981917bce6527278b19dbca86550b07d6"}}