{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T05:19:20Z","timestamp":1787894360016,"version":"build-2784847793"},"reference-count":40,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T00:00:00Z","timestamp":1787788800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T00:00:00Z","timestamp":1787788800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Forensic Sciences"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Video forgery has become increasingly prevalent with advanced editing tools, posing serious threats to digital media authenticity. However, existing approaches used for detecting manipulations often faced challenges in handling intra\u2010frame forgeries, decreased generalization, sensitivity to noise, and inadequate selection of key frames, thus leading to a decrease in the overall detection performance. To tackle these issues and to design an effective intra\u2010frame forgery detection system, this research proposes an Optimized Multi\u2010level Mixed Attention\u2010enabled Hybrid Learning\u2010based Bidirectional Gradient (OM\n                    <jats:sup>2<\/jats:sup>\n                    AHL\u2010BiG) Model. The framework leverages the hybrid learning technique to enhance representation of features, Bidirectional Long Short\u2010Term Memory (BiLSTM) for understanding long\u2010range temporal dependencies, and Gradient Boosting Machine (GBM) for precise classification. Additionally, the mixed attention mechanisms allow for refining relevant features, and the Cooperative Search Hunter optimization (CoSH) is designed for hyperparameter tuning in order to improve the detection accuracy. Overall, the OM\n                    <jats:sup>2<\/jats:sup>\n                    AHL\u2010BiG model results in enhanced detection, adaptability to various forgery types, and improved interpretability, making it an effective solution for detecting deepfake and intra\u2010frame video forgeries. The experimental results obtained on the FaceForensics++ dataset showcased an improved performance under 90% of training percentage by yielding an accuracy of 98.62%, precision of 99.2%, sensitivity of 98.04%, specificity of 98.91%, and 98.62% F1 score, surpassing conventional approaches effectively.\n                  <\/jats:p>","DOI":"10.1111\/1556-4029.70453","type":"journal-article","created":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T04:43:48Z","timestamp":1787892228000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Optimized mixed attention\u2010based bidirectional gradient model for intra\u2010frame video forgery detection"],"prefix":"10.1111","author":[{"given":"Neha","family":"Dhiman","sequence":"first","affiliation":[{"name":"Department of Computer Science &amp; Engineering, Chitkara University School of Engineering &amp; Technology Chitkara University  Baddi Himachal Pradesh India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hakam","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Computer Science &amp; Engineering, Chitkara University School of Engineering &amp; Technology Chitkara University  Baddi Himachal Pradesh India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"family":"Abhishek","sequence":"additional","affiliation":[{"name":"Department of Computer Science &amp; Engineering, Chitkara University School of Engineering &amp; Technology Chitkara University  Baddi Himachal Pradesh India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,8,27]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2024.3356549"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1049\/bme2.12031"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2024.339094"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/4976848"},{"key":"e_1_2_10_6_1","doi-asserted-by":"crossref","first-page":"471","DOI":"10.56155\/978-81-955020-2-8-43","volume-title":"Data science and intelligent computing techniques","author":"Shelke MP","year":"2023"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3342107"},{"key":"e_1_2_10_8_1","first-page":"8563","volume-title":"Proceedings of the 2024 IEEE\/CVF winter conference on applications on computer vision","author":"Nguyen TD","year":"2024"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.3390\/electronics14132680"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1155\/2023\/1648912"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/5595850"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.3390\/s24165341"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.3390\/electronics12224597"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1117\/1.JEI.29.3.033013"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3357395"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2023.103818"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/s43926\u2010025\u201000154\u20100"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042\u2010023\u201014602\u2010y"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2025.3585739"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICME57554.2024.10687645"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2024.3415415"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2024.3510355"},{"key":"e_1_2_10_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2026.3653134"},{"key":"e_1_2_10_24_1","unstructured":"FaceForensics++ Dataset. Available from:https:\/\/www.niessnerlab.org\/projects\/roessler2019faceforensicspp.html. Accessed Jul 2025."},{"key":"e_1_2_10_25_1","doi-asserted-by":"publisher","DOI":"10.3390\/e18030073"},{"key":"e_1_2_10_26_1","first-page":"1","volume-title":"Proceedings of the 2018 fourth international conference on computing communication control and automation (ICCUBEA)","author":"Chaudhari MN","year":"2018"},{"key":"e_1_2_10_27_1","first-page":"618","volume-title":"Proceedings of the IEEE international conference on computer vision (ICCV)","author":"Selvaraju RR","year":"2017"},{"key":"e_1_2_10_28_1","first-page":"761","volume-title":"Proceedings of the 2020 International Conference on Computational Performance Evaluation","author":"Haloi R","year":"2020"},{"key":"e_1_2_10_29_1","doi-asserted-by":"publisher","DOI":"10.1002\/cta.3025"},{"key":"e_1_2_10_30_1","doi-asserted-by":"publisher","DOI":"10.11591\/eei.v9i4.1837"},{"key":"e_1_2_10_31_1","doi-asserted-by":"publisher","DOI":"10.3390\/e22111190"},{"key":"e_1_2_10_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2988550"},{"key":"e_1_2_10_33_1","first-page":"2270","volume-title":"Proceedings of the Asian conference on computer vision","author":"Wang Q","year":"2022"},{"key":"e_1_2_10_34_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0277693"},{"key":"e_1_2_10_35_1","first-page":"3","volume-title":"Proceedings of the European conference on computer vision","author":"Woo S","year":"2018"},{"key":"e_1_2_10_36_1","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1145\/3357384.3357980","volume-title":"Proceedings of the 28th ACM international conference on information and knowledge management","author":"Ai Q","year":"2019"},{"key":"e_1_2_10_37_1","first-page":"395","volume-title":"Proceedings of the 2020 international conference on big data and informatization education","author":"Su Y","year":"2020"},{"key":"e_1_2_10_38_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10462\u2010019\u201009732\u20105"},{"key":"e_1_2_10_39_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11831\u2010022\u201009780\u20101"},{"key":"e_1_2_10_40_1","first-page":"3","volume-title":"Proceedings of the Asian conference on computer vision and pattern recognition","author":"Fang W","year":"2020"},{"key":"e_1_2_10_41_1","doi-asserted-by":"publisher","DOI":"10.3390\/en17081944"}],"container-title":["Journal of Forensic Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/1556-4029.70453","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1111\/1556-4029.70453","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/1556-4029.70453","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T04:43:55Z","timestamp":1787892235000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/1556-4029.70453"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,27]]},"references-count":40,"alternative-id":["10.1111\/1556-4029.70453"],"URL":"https:\/\/doi.org\/10.1111\/1556-4029.70453","archive":["Portico"],"relation":{},"ISSN":["0022-1198","1556-4029"],"issn-type":[{"value":"0022-1198","type":"print"},{"value":"1556-4029","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,27]]},"assertion":[{"value":"2025-12-12","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-07-18","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-08-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"1556-4029.70453"}}