Muhammad Hameed Siddiqi^1,*, Asfandyar Khan², Muhammad Bilal Khan², Abdullah Khan², Madallah Alruwaili¹, Saad Alanazi¹

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2219-2239, 2023, DOI:10.32604/csse.2023.040212

Abstract The use of the internet is increasing all over the world on a daily basis in the last two decades. The increase in the internet causes many sexual crimes, such as sexual misuse, domestic violence, and child pornography. Various research has been done for pornographic image detection and classification. Most of the used models used machine learning techniques and deep learning models which show less accuracy, while the deep learning model ware used for classification and detection performed better as compared to machine learning. Therefore, this research evaluates the performance analysis of intelligent neural-based deep learning models which are based… More >

Mengmeng Yan¹, Chuang Zhang^1,2,*, Jinqi Chu¹, Haichao Zhang¹, Tao Ge¹, Suting Chen¹

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1433-1449, 2023, DOI:10.32604/csse.2023.040132

Abstract An action recognition network that combines multi-level spatiotemporal feature fusion with an attention mechanism is proposed as a solution to the issues of single spatiotemporal feature scale extraction, information redundancy, and insufficient extraction of frequency domain information in channels in 3D convolutional neural networks. Firstly, based on 3D CNN, this paper designs a new multilevel spatiotemporal feature fusion (MSF) structure, which is embedded in the network model, mainly through multilevel spatiotemporal feature separation, splicing and fusion, to achieve the fusion of spatial perceptual fields and short-medium-long time series information at different scales with reduced network parameters; In the second step,… More >

Li Liu¹, Jing Li¹, Yingchun Wu¹, Chin-Chen Chang^2,*, Anhong Wang¹

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1415-1432, 2023, DOI:10.32604/csse.2023.040039

Abstract Data hiding (DH) is an important technology for securely transmitting secret data in networks, and has increasing become a research hotspot throughout the world. However, for Joint photographic experts group (JPEG) images, it is difficult to balance the contradiction among embedded capacity, visual quality and the file size increment in existing data hiding schemes. Thus, to deal with this problem, a high-imperceptibility data hiding for JPEG images is proposed based on direction modification. First, this proposed scheme sorts all of the quantized discrete cosine transform (DCT) block in ascending order according to the number of non-consecutive-zero alternating current (AC) coefficients.… More >

Nguyen Minh Trieu, Nguyen Truong Thinh^*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2381-2396, 2023, DOI:10.32604/csse.2023.040030

Abstract Nowadays, wood identification is made by experts using hand lenses, wood atlases, and field manuals which take a lot of cost and time for the training process. The quantity and species must be strictly set up, and accurate identification of the wood species must be made during exploitation to monitor trade and enforce regulations to stop illegal logging. With the development of science, wood identification should be supported with technology to enhance the perception of fairness of trade. An automatic wood identification system and a dataset of 50 commercial wood species from Asia are established, namely, wood anatomical images collected… More >

Nizheen A. Ali¹, Ramadhan J. Mstafa^2,3,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1451-1469, 2023, DOI:10.32604/csse.2023.039957

Abstract With the widespread use of the internet, there is an increasing need to ensure the security and privacy of transmitted data. This has led to an intensified focus on the study of video steganography, which is a technique that hides data within a video cover to avoid detection. The effectiveness of any steganography method depends on its ability to embed data without altering the original video’s quality while maintaining high efficiency. This paper proposes a new method to video steganography, which involves utilizing a Genetic Algorithm (GA) for identifying the Region of Interest (ROI) in the cover video. The ROI… More >

Faris Kateb, Mahmoud Ragab^*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2171-2185, 2023, DOI:10.32604/csse.2023.039931

Abstract The recent adoption of satellite technologies, unmanned aerial vehicles (UAVs) and 5G has encouraged telecom networking to evolve into more stable service to remote areas and render higher quality. But, security concerns with drones were increasing as drone nodes have been striking targets for cyberattacks because of immensely weak inbuilt and growing poor security volumes. This study presents an Archimedes Optimization with Deep Learning based Aerial Image Classification and Intrusion Detection (AODL-AICID) technique in secure UAV networks. The presented AODL-AICID technique concentrates on two major processes: image classification and intrusion detection. For aerial image classification, the AODL-AICID technique encompasses MobileNetv2… More >

Mohd Anul Haq^1,*, Siwar Ben Hadj Hassine², Sharaf J. Malebary³, Hakeem A. Othman⁴, Elsayed M. Tag-Eldin⁵

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2689-2705, 2023, DOI:10.32604/csse.2023.039904

Abstract Hyperspectral images can easily discriminate different materials due to their fine spectral resolution. However, obtaining a hyperspectral image (HSI) with a high spatial resolution is still a challenge as we are limited by the high computing requirements. The spatial resolution of HSI can be enhanced by utilizing Deep Learning (DL) based Super-resolution (SR). A 3D-CNNHSR model is developed in the present investigation for 3D spatial super-resolution for HSI, without losing the spectral content. The 3D-CNNHSR model was tested for the Hyperion HSI. The pre-processing of the HSI was done before applying the SR model so that the full advantage of… More >

Muhammad Waqas Nadeem^1,*, Hock Guan Goh¹, Yichiet Aun¹, Vasaki Ponnusamy²

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2201-2217, 2023, DOI:10.32604/csse.2023.039893

Abstract Over the past few years, rapid advancements in the internet and communication technologies have led to increasingly intricate and diverse networking systems. As a result, greater intelligence is necessary to effectively manage, optimize, and maintain these systems. Due to their distributed nature, machine learning models are challenging to deploy in traditional networks. However, Software-Defined Networking (SDN) presents an opportunity to integrate intelligence into networks by offering a programmable architecture that separates data and control planes. SDN provides a centralized network view and allows for dynamic updates of flow rules and software-based traffic analysis. While the programmable nature of SDN makes… More >

Qasem Al-Tashi^1,*, Tareq M Shami², Said Jadid Abdulkadir³, Emelia Akashah Patah Akhir³, Ayed Alwadain⁴, Hitham Alhussain³, Alawi Alqushaibi³, Helmi MD Rais³, Amgad Muneer¹, Maliazurina B. Saad¹, Jia Wu¹, Seyedali Mirjalili^5,6,7,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1937-1966, 2023, DOI:10.32604/csse.2023.039788

Abstract The process of selecting features or reducing dimensionality can be viewed as a multi-objective minimization problem in which both the number of features and error rate must be minimized. While it is a multi-objective problem, current methods tend to treat feature selection as a single-objective optimization task. This paper presents enhanced multi-objective grey wolf optimizer with Lévy flight and mutation phase (LMuMOGWO) for tackling feature selection problems. The proposed approach integrates two effective operators into the existing Multi-objective Grey Wolf optimizer (MOGWO): a Lévy flight and a mutation operator. The Lévy flight, a type of random walk with jump size… More >

Donatien Koulla Moulla^1,2,*, Ernest Mnkandla¹, Alain Abran³

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2455-2479, 2023, DOI:10.32604/csse.2023.039736

Abstract To professionally plan and manage the development and evolution of the Internet of Things (IoT), researchers have proposed several IoT performance measurement solutions. IoT performance measurement solutions can be very valuable for managing the development and evolution of IoT systems, as they provide insights into performance issues, resource optimization, predictive maintenance, security, reliability, and user experience. However, there are several issues that can impact the accuracy and reliability of IoT performance measurements, including lack of standardization, complexity of IoT systems, scalability, data privacy, and security. While previous studies proposed several IoT measurement solutions in the literature, they did not evaluate… More >