Metaheuristics with Vector Quantization Enabled Codebook Compression Model for Secure Industrial Embedded Environment
نویسندگان
چکیده
At the present time, Industrial Internet of Things (IIoT) has swiftly evolved and emerged, picture data that is collected by terminal devices or IoT nodes are tied to user's private data. The use image sensors as an automation tool for IIoT increasingly becoming more common. Due fact this organisation transfers enormous number photographs at any one most significant issues it reducing total quantity sent and, a result, available bandwidth, without compromising quality. Image compression in sensor, on other hand, expedites transfer while simultaneously bandwidth use. traditional method protecting sensitive rendered less effective environment dominated owing involvement third parties. encryption model provides safe adaptable protect confidentiality transformation storage inside system. This helps ensure datasets kept safe. Linde–Buzo–Gray (LBG) methodology example vector quantization algorithm extensively used relatively new form reduction known (VQ). As purpose research create artificial humming bird optimization approach combines LBG-enabled codebook creation (AHBO-LBGCCE) setting. In beginning, AHBO-LBGCCE LBG conjunction with AHBO order construct VQ. Burrows-Wheeler Transform (BWT) accomplish compression. addition, Blowfish carry out procedure so security may be attained. A comprehensive experimental investigation carried verify effectiveness proposed comparison algorithms. values suggested outcomes examined variety different perspectives further enhance them.
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ژورنال
عنوان ژورنال: Intelligent Automation and Soft Computing
سال: 2023
ISSN: ['2326-005X', '1079-8587']
DOI: https://doi.org/10.32604/iasc.2023.036647