Multimedia Concealed Data Detection Using Quantitative Steganalysis

Author:

Rupa Ch. 1,Shaikh Sumaiya1,Chinta Mukesh1

Affiliation:

1. V. R. Siddhartha Engineering College (Autonomous), Vijayawada, India

Abstract

In current days, there is a constant evolution in modern technology. The most predominant usage of technology by society is the internet. There are many ways and means on the internet through which data is transmitted. Having such rapid and fast growth of communicating media also increases the exposure to security threats, causing unintellectual information ingress. Steganography is the main aspect of communicating in an aspect that hides the extent of communication. Steganalysis is another essential concern in data concealing, which is the art of identifying the existence of steganography. A framework has been designed to identify the concealed data in the multimedia file in the proposed system. This work's main strength is analyzing concealed data images without embedding and extracting the image's payloads. A quantitative steganalysis approach was considered to accomplish the proposed objective. By using this approach, the results were achieved with 98% accuracy.

Publisher

IGI Global

Subject

Software

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Comprehensive survey on image steganalysis using deep learning;Array;2024-07

2. Robust steganographic framework for securing sensitive healthcare data of telemedicine using convolutional neural network;CAAI Transactions on Intelligence Technology;2024-03-28

3. Toward the Confidential Data Location in Spatial Domain Images via a Genetic-based Pooling in a Convolutional Neural Network;2024 16th International Conference on Computer and Automation Engineering (ICCAE);2024-03-14

4. Convolutional Neural Network with Multi-scale Pooling for the Efficient Steganalysis in Images of Arbitrary Sizes;2023 14th International Conference on Information & Communication Technology and System (ICTS);2023-10-04

5. Botnet Attack Intrusion Detection In IoT Enabled Automated Guided Vehicles;2022 IEEE International Conference on Big Data (Big Data);2022-12-17

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