Yudong Zhang¹, Muhammad Attique Khan², Ziquan Zhu¹, Shuihua Wang^1,*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 13-26, 2023, DOI:10.32604/csse.2023.034172

Abstract (Aim) The COVID-19 has caused 6.26 million deaths and 522.06 million confirmed cases till 17/May/2022. Chest computed tomography is a precise way to help clinicians diagnose COVID-19 patients. (Method) Two datasets are chosen for this study. The multiple-way data augmentation, including speckle noise, random translation, scaling, salt-and-pepper noise, vertical shear, Gamma correction, rotation, Gaussian noise, and horizontal shear, is harnessed to increase the size of the training set. Then, the SqueezeNet (SN) with complex bypass is used to generate SN features. Finally, the extreme learning machine (ELM) is used to serve as the classifier due to its simplicity of usage,… More >

Samah Alshathri¹, Ayman El-Sayed², Walid El-Shafai^3,4,*, Ezz El-Din Hemdan²

Computer Systems Science and Engineering, Vol.46, No.1, pp. 819-834, 2023, DOI:10.32604/csse.2023.034095

Abstract Recently, the Internet of Things (IoT) has been used in various applications such as manufacturing, transportation, agriculture, and healthcare that can enhance efficiency and productivity via an intelligent management console remotely. With the increased use of Industrial IoT (IIoT) applications, the risk of brutal cyber-attacks also increased. This leads researchers worldwide to work on developing effective Intrusion Detection Systems (IDS) for IoT infrastructure against any malicious activities. Therefore, this paper provides effective IDS to detect and classify unpredicted and unpredictable severe attacks in contradiction to the IoT infrastructure. A comprehensive evaluation examined on a new available benchmark TON_IoT dataset is… More >

Muhammad Akram¹, Muhammad Waseem Iqbal^2,*, M. Usman Ashraf³, Erssa Arif¹, Khalid Alsubhi⁴, Hani Moaiteq Aljahdali⁵

Computer Systems Science and Engineering, Vol.46, No.1, pp. 1021-1038, 2023, DOI:10.32604/csse.2023.034085

Abstract The Learning management system (LMS) is now being used for uploading educational content in both distance and blended setups. LMS platform has two types of users: the educators who upload the content, and the students who have to access the content. The students, usually rely on text notes or books and video tutorials while their exams are conducted with formal methods. Formal assessments and examination criteria are ineffective with restricted learning space which makes the student tend only to read the educational contents and videos instead of interactive mode. The aim is to design an interactive LMS and examination video-based… More >

Mesfer Alduhayyem^1,*, Mrim M. Alnfiai^2,3, Nabil Almalki⁴, Fahd N. Al-Wesabi⁵, Anwer Mustafa Hilal⁶, Manar Ahmed Hamza⁶

Computer Systems Science and Engineering, Vol.46, No.1, pp. 475-489, 2023, DOI:10.32604/csse.2023.034067

Abstract Visual impairment is one of the major problems among people of all age groups across the globe. Visually Impaired Persons (VIPs) require help from others to carry out their day-to-day tasks. Since they experience several problems in their daily lives, technical intervention can help them resolve the challenges. In this background, an automatic object detection tool is the need of the hour to empower VIPs with safe navigation. The recent advances in the Internet of Things (IoT) and Deep Learning (DL) techniques make it possible. The current study proposes IoT-assisted Transient Search Optimization with a Lightweight RetinaNet-based object detection (TSOLWR-ODVIP)… More >

P. Prathap Nayudu, Krovi Raja Sekhar^*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 1079-1092, 2023, DOI:10.32604/csse.2023.033961

Abstract The cloud allows clients to store and share data. Depending on the user’s needs, it is imperative to design an effective access control plan to share the information only with approved users. The user loses control of their data when the data is outsourced to the cloud. Therefore, access control mechanisms will become a significant challenging problem. The Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is an essential solution in which the user can control data access. CP-ABE encrypts the data under a limited access policy after the user sets some access policies. The user can decrypt the data if they satisfy the… More >

Jingwei Hao^*, Senlin Luo, Limin Pan

Computer Systems Science and Engineering, Vol.46, No.1, pp. 719-734, 2023, DOI:10.32604/csse.2023.033923

Abstract The byte stream is widely used in malware detection due to its independence of reverse engineering. However, existing methods based on the byte stream implement an indiscriminate feature extraction strategy, which ignores the byte function difference in different segments and fails to achieve targeted feature extraction for various byte semantic representation modes, resulting in byte semantic confusion. To address this issue, an enhanced adversarial byte function associated method for malware backdoor attack is proposed in this paper by categorizing various function bytes into three functions involving structure, code, and data. The Minhash algorithm, grayscale mapping, and state transition probability statistics… More >

S. J. Sangeetha^1,*, T. Rajendran²

Computer Systems Science and Engineering, Vol.46, No.1, pp. 1169-1181, 2023, DOI:10.32604/csse.2023.033392

Abstract Mobile Ad-hoc Networks (MANETs) connect numerous nodes to communicate data from the sender node to the target node. Due to the lack of an infrastructure network, mobile nodes communicate through wireless without an access point. MANET does not have a centralized controller and has a dynamic network topology, which increases link failure and energy consumption resulting in excessive path delay, loss of Quality of service (QoS), and reduced throughput during data communication. Congestion is a significant problem when the QoS of the link carrying the data is degraded. Routing is one of the vital challenges of MANET due to the… More >

N. Alsadhan^*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 241-253, 2023, DOI:10.32604/csse.2023.033375

Abstract Tax fraud is one of the substantial issues affecting governments around the world. It is defined as the intentional alteration of information provided on a tax return to reduce someone’s tax liability. This is done by either reducing sales or increasing purchases. According to recent studies, governments lose over $500 billion annually due to tax fraud. A loss of this magnitude motivates tax authorities worldwide to implement efficient fraud detection strategies. Most of the work done in tax fraud using machine learning is centered on supervised models. A significant drawback of this approach is that it requires tax returns that… More >

X. Zhang¹, H. Liu¹, Z. H. Liu¹, J. R. Ming^1,*, Y. Zhou²

Computer Systems Science and Engineering, Vol.46, No.1, pp. 357-369, 2023, DOI:10.32604/csse.2023.033251

Abstract To meet the needs of today’s library users, institutions are developing library mobile apps (LMAs), as their libraries are increasingly intelligent and rely on deep learning. This paper explores the influencing factors and differences in the perception of LMAs at different time points after a user has downloaded an LMA. A research model was constructed based on the technology acceptance model. A questionnaire was designed and distributed twice to LMA users with an interval of three months to collect dynamic data. The analysis was based on structural equation modeling. The empirical results show that the perceived ease of use, the… More >

Aparna Gullapelly, Barnali Gupta Banik^*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 1127-1139, 2023, DOI:10.32604/csse.2023.032904

Abstract The field of object tracking has recently made significant progress. Particularly, the performance results in both deep learning and correlation filters, based trackers achieved effective tracking performance. Moreover, there are still some difficulties with object tracking for example illumination and deformation (DEF). The precision and accuracy of tracking algorithms suffer from the effects of such occurrences. For this situation, finding a solution is important. This research proposes a new tracking algorithm to handle this problem. The features are extracted by using Modified LeNet-5, and the precision and accuracy are improved by developing the Real-Time Cross-modality Correlation Filtering method (RCCF). In… More >