Journal Article10.1016/j.compeleceng.2024.109236
Deep learning-based encryption for secure transmission digital images: A survey
Soniya Rohhila,Amit Kumar Singh +1 more
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TL;DR: This survey reviews recent digital image encryption using deep learning models, discussing motivations, state-of-the-art techniques, and challenges, including standard security metrics, to protect image privacy and prevent leakage in high-throughput big data storage and media applications.
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Abstract: With the innovation of high-throughput big data storage technology and the construction of digital information systems in media applications, images are the common and most popular media carriers and are generated and transmitted in huge quantities. Due to the significant advantages and high value of digital image content, there is an urgent demand to protect their privacy and prevent leakage. In the past few years, deep learning models have brought more options for image encryption algorithm design. This paper offers a comprehensive survey of recent digital image encryption using deep learning models. First, a strong motivation for image encryption using deep learning models along with recent applications is introduced. Next, various state-of-the-art deep learning-based encryption techniques are discussed. The technical summary of different popular techniques is then given in tabular form. Lastly, by deeply investigating existing deep learning-based encryption, we establish some important research challenges and possible solutions, including standard security metrics.
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Citations
Penggunaan Artificial Intelligence dalam perhitungan dinamis sudut kontak hysteresis pada droplet
Kumara Ari Yuana,arifiyanto hadinegoro,Teguh Wibowo,Drajat Indah Mawarni,Agung Pambudi,Kumara Ari Yuana,arifiyanto hadinegoro,Teguh Wibowo,Drajat Indah Mawarni,Agung Pambudi +9 more
Abstract: Sudut kontak hysteresis (SKH) adalah selisih antara sudut kontak maju (advancing) dan mundur (receding). Besaran ini merupakan indikator penting dalam karakterisasi kebasahan permukaan, yang berdampak pada berbagai aplikasi teknik dan industri seperti pendinginan semprot dan material anti-icing. Tujuan penelitian ini adalah untuk mengukur sudut kontak histeresis (SKH) pada permukaan logam panas menggunakan metode tumbukan droplet campuran air dan campuran etilen glikol (20%) yang direkam dengan kamera kecepatan tinggi (2000 fps). Penggunaan kamera berkecepatan tinggi menjanjikan kemampuan menangkap fenomena pergerakan tinggi tetapi memiliki keterbatasan-keterbatasan yang harus diselesaikan seperti noise dan thermal artifact. Untuk mengatasi noise citra akibat gerakan cepat dan thermal artifact, penelitian ini menerapkan pemrosesan citra berbasis kecerdasan buatan/artificial intelligence (AI) menggunakan arsitektur CNN (ResNet-18) dan GAN (ESRGAN). Hasil menunjukkan bahwa metode ini mampu meningkatkan kualitas citra dan akurasi pengukuran sudut kontak, dengan nilai rata-rata sudut kontak advancing sebesar 80,5°, receding sebesar 32,74° dan SKH 47,76°. Pendekatan ini menawarkan solusi efektif dan presisi tinggi dalam pengukuran SKH serta memberikan kontribusi terhadap pemodelan kebasahan permukaan pada sistem dinamis.
Synchronization of Chaotic Extremum-Coded Random Number Generators and Its Application to Segmented Image Encryption
Shunsuke Araki,Ji-Han Wu,Jun‐Juh Yan +2 more
TL;DR: This paper proposes a secure image encryption technique using chaotic synchronization of extremum-coded random number generators (ECRNGs) with AES encryption, achieving complete synchronization within a single sampling time and significantly enhancing image encryption performance.
Image encryption algorithm based on homogenized one-dimensional chaotic mapping and compressed sensing
Xiao Yuan Yang,Liyong Bao,Hongwei Ding,Y. Si +3 more
- 22 Jul 2024
Privacy-Preserving ConvMixer Without Any Accuracy Degradation Using Compressible Encrypted Images
Han Yu Lin,Shoko Imaizumi,Hitoshi Kiya +2 more
TL;DR: This paper proposes a novel privacy-preserving ConvMixer method using block-wise encryption, enhancing robustness against ciphertext-only attacks, and achieving comparable accuracy to non-encrypted models without performance degradation.
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