Lehmer Algoritması Tabanlı Rastgele Anahtar İle Şifrelenmiş Görüntüleri Kullanarak Nesne Tespitli Doğrulama Yoluyla Güvenli Mesaj İletimi

Year 2023, Volume: 9 Issue: 1, 108 - 127, 30.04.2023

Simay Hoşmeyve Arda Cem Bilecan Bahadir Karasulu İsmet Ünlü

Abstract

Günümüzde son kullanıcılar arası verinin başarılı iletimi, verinin korunması ve gizlilik önemli konulardır. Çalışmamızda, uçtan uca (end-to-end) güvenilir bir iletişim kanalı üzerinden rastgele anahtar üretimi için Lehmer algoritması tabanlı piksel renk matris bilgilerinde bit bazında şifrelenmiş görüntülerin iletilmesini sağlayan ve doğruluk geçerlemesini garanti eden bir sistem oluşturulmuştur. Derin öğrenme modeli kullanılarak görüntü sahnesi içerisindeki tespit edilen nesnelerin özellikleri ile üst veri oluşturulmaktadır. Çalışmada, mesajın göndericisi tarafından Lehmer algoritması kullanılarak şifreleme yapıldıktan sonra Base64 kodlama formatında yapılandırılmış veri oluşturulmaktadır. Güvenli iletim kanalı üzerinden bu mesaj alıcı tarafa uçtan uca iletir. Son olarak alıcı tarafa ulaşan mesaj paketindeki görüntü sahnesi içerisindeki nesnelerin tespit bilgilerini içeren yapılandırılmış veri değişim ve aktarım dosyasından görüntünün kodlanmış hali ve üst veri bilgileri ayıklanarak şifre çözümlemesi yapılmaktadır. Alıcı tarafta derin öğrenme modelinin nesne tespit sonuçları bu dosyadan elde edilen deşifrelenmiş bilgi ile kıyaslanarak mesajın doğruluğunun geçerlemesi şeklinde nesnel sağlaması da yapılmaktadır. Yapılan deneylerdeki ortalama değerler göz önüne alındığında üç farklı veri kümesinden elde edilen veriler için ortalama değerler olarak Piksel Sayısı Değişim Hızı (NPCR) %99,61, Birleşik Ortalama Değişme Yoğunluğu (UACI) %14,70 ve ortalama entropi değeri ise şifrelenmiş görüntüler için azami 7,9999 değerinde ölçülmüştür. Çalışmamızda bilimsel bulgulara dayanan tartışma ve değerlendirmelere yer verilmektedir.

Keywords

Rastgele sayı, şifreleme, derin öğrenme, veri iletişimi

Secure Message Transmission Via Object Detection Verification Using Images Encoded With Lehmer Algorithm Based Random Key

Abstract

Nowadays, the successful transmission of data between end users, data protection and confidentiality are important issues. In our study, a system that ensures the transmission of bitwise encrypted images in pixel color matrix information based on the Lehmer algorithm for the generation of random keys over an end-to-end reliable communication channel and guarantees accuracy validation has been created. Using the deep learning model, metadata is created with the properties of the detected objects in the image scene. In the study, structured data is created in Base64 encoding format after encryption is done by the sender end of the message using the Lehmer algorithm. This message is transmitted end-to-end to the receiving party over the secure transmission channel. Finally, the encoded version of the image and the metadata information are extracted from the structured data exchange and transfer file containing the detection information of the objects in the image scene in the message packet reaching the receiver end, and also, decryption is performed. On the receiver end, object detection results of the deep learning model are compared with the decrypted information obtained from this file, and an objective verification of the accuracy of the message is also performed. Considering the average values in the experiments, the average values with the data obtained from three different data sets are for the Number of Pixels Change Rate (NPCR) 99.61%, the Unified Average Changing Intensity (UACI) 14.70%, and also, the maximum average entropy value is obtained 7.9999 for encrypted images. In our study, discussions and evaluations based on scientific findings are included.

Keywords

Random number, encryption, deep learning, data communication

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