Communication
Rawia Abdullah Muhammed; Maisa'a Abid Ali Al-Dabbas; Ashwak Mahmood Alabaichi
Abstract
The Internet of things (IoT) is one of those emerging technologies, which aregoing to rule the world in the next few decades. The IoT environment not only enablesHuman to Machine interaction but also fosters Machine to Machine connectivity.Numerous IoT devices have poor security and insufficient computing ...
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The Internet of things (IoT) is one of those emerging technologies, which aregoing to rule the world in the next few decades. The IoT environment not only enablesHuman to Machine interaction but also fosters Machine to Machine connectivity.Numerous IoT devices have poor security and insufficient computing power, making themprime targets for hackers. The IoT environment uses lightweight cryptographic techniquesto address security requirements. Another security method for IoT devices issteganography. In the contemporary Internet era, the ability to secure private informationis crucial, and steganography offers this capability. Due to its great ability to concealsensitive data, video has drawn the attention of numerous academics among all forms ofdigital media. The main goal of this work is to examine several methods for fusing videosteganography and cryptography techniques. Additionally, a thorough investigation andevaluation of a variety of video steganography methods in both compressed and rawdomains are also emphasized. The comprehensive analysis of prior material makes iteasier to have in-depth knowledge while creating approaches that combine cryptographywith steganography.
Computer
Asmaa Hasan Alrubaie; Maisa'a Abid Ali Khodher; Ahmed Talib Abdulameer
Abstract
Target detection, one of the key functions of computer vision, has grown in importance as a study area over the past two decades and is currently often employed. In a certain video, it seeks to rapidly and precisely detect and locate a huge amount of the objects according to redetermined categories. ...
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Target detection, one of the key functions of computer vision, has grown in importance as a study area over the past two decades and is currently often employed. In a certain video, it seeks to rapidly and precisely detect and locate a huge amount of the objects according to redetermined categories. The two forms of deep learning (DL) algorithms that are used in the model training algorithm are single-stage and 2-stage algorithms of detection. The representative algorithms for every level have been thoroughly discussed in this work. The analysis and comparison of numerous representative algorithms in this subject is after that explained. Last but not least, potential obstacles to target detection are anticipated.
