Preferred Language
Articles
/
bsj-5112
Advanced Intelligent Data Hiding Using Video Stego and Convolutional Neural Networks
...Show More Authors

Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus, the exact way by which the network will hide the information is unable to be known to anyone who does not have the weights.  The second goal is to increase hiding capacity, which has been achieved by using CNN as a strategy to make decisions to determine the best areas that are redundant and, as a result, gain more size to be hidden. Furthermore, In the proposed model, CNN is concurrently trained to generate the revealing and hiding processes, and it is designed to work as a pair mainly. This model has a good strategy for the patterns of images, which assists to make decisions to determine which is the parts of the cover image should be redundant, as well as more pixels are hidden there. The CNN implementation can be done by using Keras, along with tensor flow backend. In addition, random RGB images from the "ImageNet dataset" have been used for training the proposed model (About 45000 images of size (256x256)). The proposed model has been trained by CNN using random images taken from the database of ImageNet and can work on images taken from a wide range of sources. By saving space on an image by removing redundant areas, the quantity of hidden data can be raised (improve capacity). Since the weights and model architecture are randomized, the actual method in which the network will hide the data can't be known to anyone who does not have the weights. Furthermore, additional block-shuffling is incorporated as an encryption method to improved security; also, the image enhancement methods are used to improving the output quality. From results, the proposed method has achieved high-security level, high embedding capacity. In addition, the result approves that the system achieves good results in visibility and attacks, in which the proposed method successfully tricks observer and the steganalysis program.

Scopus Clarivate Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Mon Oct 19 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
The effect of using the interactive video accompanying the static training in learning some basic skills of a model school in squash
...Show More Authors

Lately great interests have emerged to find educational alternatives to teach and improve motor skills according to modern educational methods that take into account individual differences and speed in learning for the learner through individual learning that the learner adopts by teaching himself by passing through various educational situations to acquire skills and information in the way he is The learner is the focus of the educational process and among these alternatives the interactive video, the researchers noted through the educational training units at the Model Squash School of the Central Union, and that most of the methods and methods used in learning basic skills take a lot of time in the educational program and do not involve

... Show More
View Publication Preview PDF
Publication Date
Mon Oct 13 2025
Journal Name
Mesopotamian Journal Of Cybersecurity
Improvement of the Face Recognition Systems Security Against Morph Attacks using the Developed Siamese Neural Network
...Show More Authors

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

... Show More
View Publication Preview PDF
Scopus Crossref
Publication Date
Thu May 05 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Classification SINGLE-LEAD ECG by using conventional neural network algorithm
...Show More Authors

View Publication
Scopus Crossref
Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Development an Anomaly Network Intrusion Detection System Using Neural Network
...Show More Authors

Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

... Show More
View Publication Preview PDF
Crossref
Publication Date
Wed Apr 20 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Text image secret sharing with hiding based on color feature
...Show More Authors

View Publication
Scopus (1)
Crossref (1)
Scopus Crossref
Publication Date
Mon Apr 03 2023
Journal Name
Aro-the Scientific Journal Of Koya University
The Most Common Characteristics of Fragile Video Watermarking
...Show More Authors

The progress of network and multimedia technologies has been phenomenal during the previous two decades. Unauthorized users will be able to copy, retransmit, modify reproduction, and upload the contents more easily as a result of this innovation. Malicious attackers are quite concerned about the development and widespread use of digital video. Digital watermarking technology gives solutions to the aforementioned problems. Watermarking methods can alleviate these issues by embedding a secret watermark in the original host data, allowing the genuine user or file owner to identify any manipulation. In this study, lots of papers have been analyzed and studied carefully, in the period 2011–2022. The historical basis of the subject shou

... Show More
View Publication
Scopus (4)
Crossref (3)
Scopus Clarivate Crossref
Publication Date
Tue Jan 01 2013
Journal Name
International Journal Of Innovation, Management And Technology
Intelligent Magneto-Rheological Fluid Directional Control Valve
...Show More Authors

There are many configurations of directional control valve. Directional control valve has complex construction, such as moving spool to control the direction of actuator and desired speed. Magneto-rheological (MR) fluid is one of controllable fluids. Utilizing the MR fluid properties, direct interface can be realized between magnetic field and fluid power without the need for moving parts like spool in directional control valves. This paper presents the design of multi configuration MR directional control valve. The construction and the principle of work of the valve are presented. The experiment was conducted to show the working principle of the valve functionally. The valve worked proportionally to control the direction and speed of hydra

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Engineering
Intelligent Dust Monitoring System Based on IoT
...Show More Authors

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

... Show More
View Publication
Crossref (3)
Crossref
Publication Date
Sat Jun 30 2018
Journal Name
Proceedings Of The International Conference On Intelligent Science And Technology
The nature of intelligent system in buildings
...Show More Authors

View Publication
Scopus (1)
Scopus Crossref
Publication Date
Wed Oct 29 2025
Journal Name
Clean Energy Science And Technology
Edge-intelligent leak detection in water distribution systems using CatBoost: A sustainable solution for reducing infrastructure losses
...Show More Authors

Water supply networks are marred by serious risks of imperceptible pipeline leakage, posing ‎sustainability ‎and ‎performance ‎threats.  This article highlights the use of vibratory signal features to get around the drawbacks of traditional methods in a highly detailed framework for leak detection based on CatBoost. demonstrated excellent diagnostic performance and carried out a thorough test performance evaluation on five leakage configurations  . The expected system achieved an accuracy of 98.1% (variance (well within x/3% of expected):, beating traditional competitors such as Random Forest (97.3%) and Support Vector Machine (93.8%). ‎For example, the area under the receiver-operating characteristic curve was 0.995, in

... Show More
View Publication
Scopus (3)
Crossref (2)
Scopus Crossref