Yuancong Chai, Yuefei Zhu^*, Wei Lin, Ding Li

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1223-1243, 2024, DOI:10.32604/cmc.2024.049904

Abstract With the increasing proportion of encrypted traffic in cyberspace, the classification of encrypted traffic has become a core key technology in network supervision. In recent years, many different solutions have emerged in this field. Most methods identify and classify traffic by extracting spatiotemporal characteristics of data flows or byte-level features of packets. However, due to changes in data transmission mediums, such as fiber optics and satellites, temporal features can exhibit significant variations due to changes in communication links and transmission quality. Additionally, partial spatial features can change due to reasons like data reordering and retransmission. Faced with these challenges, identifying… More >

Yuyuan Li^1,2, Lang Li^1,2,*, Yu Ou^1,2

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1245-1262, 2024, DOI:10.32604/cmc.2024.049882

Abstract The Inner Product Masking (IPM) scheme has been shown to provide higher theoretical security guarantees than the Boolean Masking (BM). This scheme aims to increase the algebraic complexity of the coding to achieve a higher level of security. Some previous work unfolds when certain (adversarial and implementation) conditions are met, and we seek to complement these investigations by understanding what happens when these conditions deviate from their expected behaviour. In this paper, we investigate the security characteristics of IPM under different conditions. In adversarial condition, the security properties of first-order IPMs obtained through parametric characterization are preserved in the face… More >

Jinlin Xu^1,2, Wansu Pan^1,*, Longle Cheng^1,2, Haibo Tan^1,2, Munan Yuan^1,*, Xiaofeng Li^1,2

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1399-1418, 2024, DOI:10.32604/cmc.2024.049622

Abstract The existing multipath routing in Software Defined Network (SDN) is relatively blind and inefficient, and there is a lack of cooperation between the terminal and network sides, making it difficult to achieve dynamic adaptation of service requirements and network resources. To address these issues, we propose a multi-constraint path optimization scheme based on information fusion in SDN. The proposed scheme collects network topology and network state information on the network side and computes disjoint paths between end hosts. It uses the Fuzzy Analytic Hierarchy Process (FAHP) to calculate the weight coefficients of multiple constrained parameters and constructs a composite quality… More >

Siyuan Liu^1,*, Jinying Huang², Jiancheng Ma¹, Licheng Jing², Yuxuan Wang²

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 761-777, 2024, DOI:10.32604/cmc.2024.049484

Abstract Recent research in cross-domain intelligence fault diagnosis of machinery still has some problems, such as relatively ideal speed conditions and sample conditions. In engineering practice, the rotational speed of the machine is often transient and time-varying, which makes the sample annotation increasingly expensive. Meanwhile, the number of samples collected from different health states is often unbalanced. To deal with the above challenges, a complementary-label (CL) adversarial domain adaptation fault diagnosis network (CLADAN) is proposed under time-varying rotational speed and weakly-supervised conditions. In the weakly supervised learning condition, machine prior information is used for sample annotation via cost-friendly complementary label learning.… More >

Deming Lei, Surui Duan, Mingbo Li^*, Jing Wang

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 47-63, 2024, DOI:10.32604/cmc.2024.049481

Abstract Bottleneck stage and reentrance often exist in real-life manufacturing processes; however, the previous research rarely addresses these two processing conditions in a scheduling problem. In this study, a reentrant hybrid flow shop scheduling problem (RHFSP) with a bottleneck stage is considered, and an elite-class teaching-learning-based optimization (ETLBO) algorithm is proposed to minimize maximum completion time. To produce high-quality solutions, teachers are divided into formal ones and substitute ones, and multiple classes are formed. The teacher phase is composed of teacher competition and teacher teaching. The learner phase is replaced with a reinforcement search of the elite class. Adaptive adjustment on… More >

Yiming Tang^1,2, Jianwei Gao^1,*, Yifan Huang¹

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1063-1088, 2024, DOI:10.32604/cmc.2024.049341

Abstract The α-universal triple I (α-UTI) method is a recognized scheme in the field of fuzzy reasoning, which was proposed by our research group previously. The robustness of fuzzy reasoning determines the quality of reasoning algorithms to a large extent, which is quantified by calculating the disparity between the output of fuzzy reasoning with interference and the output without interference. Therefore, in this study, the interval robustness (embodied as the interval stability) of the α-UTI method is explored in the interval-valued fuzzy environment. To begin with, the stability of the α-UTI method is explored for the case of an individual rule,… More >

Qixiang Tong, Zhipeng Zhu, Min Zhang, Kerui Cao, Haihua Xing^*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1353-1375, 2024, DOI:10.32604/cmc.2024.049187

Abstract High-resolution remote sensing image segmentation is a challenging task. In urban remote sensing, the presence of occlusions and shadows often results in blurred or invisible object boundaries, thereby increasing the difficulty of segmentation. In this paper, an improved network with a cross-region self-attention mechanism for multi-scale features based on DeepLabv3+ is designed to address the difficulties of small object segmentation and blurred target edge segmentation. First, we use CrossFormer as the backbone feature extraction network to achieve the interaction between large- and small-scale features, and establish self-attention associations between features at both large and small scales to capture global contextual… More >

Dingping Chen¹, Zhiheng Zhu², Jinyang Fu^1,3, Jilin He^1,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1679-1703, 2024, DOI:10.32604/cmc.2024.049048

Abstract The detection of crack defects on the walls of road tunnels is a crucial step in the process of ensuring travel safety and performing routine tunnel maintenance. The automatic and accurate detection of cracks on the surface of road tunnels is the key to improving the maintenance efficiency of road tunnels. Machine vision technology combined with a deep neural network model is an effective means to realize the localization and identification of crack defects on the surface of road tunnels. We propose a complete set of automatic inspection methods for identifying cracks on the walls of road tunnels as a… More >

Aodi Liu, Na Wang^*, Xuehui Du, Dibin Shan, Xiangyu Wu, Wenjuan Wang

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1705-1726, 2024, DOI:10.32604/cmc.2024.049011

Abstract Big data resources are characterized by large scale, wide sources, and strong dynamics. Existing access control mechanisms based on manual policy formulation by security experts suffer from drawbacks such as low policy management efficiency and difficulty in accurately describing the access control policy. To overcome these problems, this paper proposes a big data access control mechanism based on a two-layer permission decision structure. This mechanism extends the attribute-based access control (ABAC) model. Business attributes are introduced in the ABAC model as business constraints between entities. The proposed mechanism implements a two-layer permission decision structure composed of the inherent attributes of… More >

Jiajun Yan, Ying Zhou^*, Anchen Dai, Tao Wang

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 563-580, 2024, DOI:10.32604/cmc.2024.048922

Abstract As an emerging network paradigm, the software-defined network (SDN) finds extensive application in areas such as smart grids, the Internet of Things (IoT), and edge computing. The forwarding layer in software-defined networks is susceptible to eavesdropping attacks. Route hopping is a moving target defense (MTD) technology that is frequently employed to resist eavesdropping attacks. In the traditional route hopping technology, both request and reply packets use the same hopping path. If an eavesdropping attacker monitors the nodes along this path, the risk of 100% data leakage becomes substantial. In this paper, we present an effective route hopping approach, called two-day… More >