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An innovative malware detection methodology employing the amalgamation of stacked <scp>BiLSTM</scp> and <scp>CNN</scp>+<scp>LSTM</scp>‐based classification networks with the assistance of Mayfly metaheuristic optimization algorithm in cyber‐attack
Research article (Concurrency and Computation Practice and Experience, 2023) · cited 10× · AI/ML
An innovative malware detection methodology employing the amalgamation of stacked BiLSTM and CNN+LSTM‐based classification networks with the assistance of Mayfly metaheuristic optimization algorithm in cyber‐attack
Summary
An innovative malware detection methodology employing the amalgamation of stacked BiLSTM and CNN+LSTM‐based classification networks with the assistance of Mayfly metaheuristic optimization algorithm in cyber‐attack is a scholarly article[1].
Key Facts
An innovative malware detection methodology employing the amalgamation of stacked BiLSTM and CNN+LSTM‐based classification networks with the assistance of Mayfly metaheuristic optimization algorithm in cyber‐attack's instance of is recorded as scholarly article[2].
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). An innovative malware detection methodology employing the amalgamation of stacked <scp>BiLSTM</scp> and <scp>CNN</scp>+<scp>LSTM</scp>‐based classification networks with the assistance of Mayfly metaheuristic optimization algorithm in cyber‐attack. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-innovative-malware-detection-methodology-employing-the-amalgamation-of-stacked-scp-bilstm-scp-and-scp-cnn-scp-scp-lst
MLA“An innovative malware detection methodology employing the amalgamation of stacked <scp>BiLSTM</scp> and <scp>CNN</scp>+<scp>LSTM</scp>‐based classification networks with the assistance of Mayfly metaheuristic optimization algorithm in cyber‐attack.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-innovative-malware-detection-methodology-employing-the-amalgamation-of-stacked-scp-bilstm-scp-and-scp-cnn-scp-scp-lst.
BibTeX@misc{4ortxyz_an-innovative-malware-detection-methodology-employing-the-amalgamation-of-stacked-scp-bilstm-scp-and-scp-cnn-scp-scp-lst_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An innovative malware detection methodology employing the amalgamation of stacked <scp>BiLSTM</scp> and <scp>CNN</scp>+<scp>LSTM</scp>‐based classification networks with the assistance of Mayfly metaheuristic optimization algorithm in cyber‐attack}}, year = {2026}, url = {https://4ort.xyz/entity/an-innovative-malware-detection-methodology-employing-the-amalgamation-of-stacked-scp-bilstm-scp-and-scp-cnn-scp-scp-lst}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): An innovative malware detection methodology employing the amalgamation of stacked <scp>BiLSTM</scp> and <scp>CNN</scp>+<scp>LSTM</scp>‐based classification networks with the assistance of Mayfly metaheuristic optimization algorithm in cyber‐attack — https://4ort.xyz/entity/an-innovative-malware-detection-methodology-employing-the-amalgamation-of-stacked-scp-bilstm-scp-and-scp-cnn-scp-scp-lst (retrieved 2026-05-24)
