Channel Network Research Articles

Path Planning in Payment Channel Networks with Multi-Party Channels

Payment Channel Networks (PCNs) provide a means to improve the scaling of cryptocurrency payments by allowing peers to make payments between themselves in an efficient manner. To make a payment between two peers, the task of path planning must first be performed to determine a path in the PCN connecting the peers in question before the payment in question is performed using this path. To date, existing research has focused on the problem of performing path planning in PCNs that contain two-party channels. It has been hypothesised that the scaling of PCNs could be further improved by considering the inclusion of multi-party channels that contain more than two peers. However, the problem of performing path planning in PCNs that contain multi-party channels has not yet been considered. In this article, we address this gap in the research literature and propose a novel path planning method for PCNs containing multi-party channels. This method involves modelling the PCN with multi-party channels as a hypergraph, a type of graph where edges can contain two or more vertices, and using this model to solve the path planning problem in question. We prove that the proposed method is correct and computationally efficient. Furthermore, assuming path planning is performed using this method, we also present theoretical and experimental analyses that demonstrate the scaling benefits of using multi-party channels.

A Review on Network Covert Channel Construction and Attack Detection

ABSTRACTA covert network channel is a communication channel in which the message is secretly transmitted to the recipient. Sometimes, covert network channels are vulnerable to multiple attacks. Therefore, the message must be properly secure. In most cases, the covert channel is used to ensure data protection and allow users to freely access the Internet. In this paper, several recent studies are reviewed on covert network channels and examine the existing works from 2015 to 2024. This review article also discusses the undetectability and reliability of different types of covert network channels. Furthermore, a detailed description of the covert network channel's ability to hide in containers is provided. Existing research on covert network channels explains a few techniques for detecting attacks in secret data communication. However, several machine learning and deep learning techniques have been discussed in this article. Additionally, this article describes the accuracy of detection through an overview of current technologies. In addition, various countermeasures to prevent attacks in covert channels are also discussed in detail. However, in this case, the bandwidth limitations, data set limitations, and covert channel capacity are clearly defined, which will help future researchers build covert network channels and detect attacks. Finally, this work considers the challenges faced by covert network channels and the future scope of application.

Research on X-ray security contraband identification technology based on lightweight YOLOv8

Aiming at the difficulty of identification and localization in the detection of contraband targets in X-ray images, as well as the demand for upgrading and deployment of security equipment during the peak flow stage, a lightweight X-ray security contraband detection algorithm is proposed and optimized for YOLOv8. Firstly, the number of channels in the original network is reduced according to a predetermined ratio, which effectively reduces model parameters and computational complexity and achieves better results than the current mainstream lightweight methods, such as model pruning and detection backbone optimization. Secondly, due to the presence of objects of various scales and sizes in X-ray security inspection images, we introduced the BiFPN feature extraction strategy in the neck. We designed a simplified version of BiFPN based on the YOLOv8 network structure to effectively integrate feature information from different levels and scales. Finally, we incorporated the idea of Focal Loss to address the issue of imbalance between positive and negative samples and proposed a new regression loss function, Focal-GIoU Loss, which combines GIoU Loss. This increases the loss weight for important but difficult-to-detect samples, such as small targets and overlapping targets, making the model more focused on these critical samples. Results show that our proposed YOLO-CBF improves mAP by 1.5%, 0.9%, and 0.5% on three datasets with different levels of occlusion in PIDray, while reducing the parameter count and computational cost from the original 3.0M and 8.1G to 2.1M and 6.3G.Moreover, it performs well in comparative experiments between different models and in generalization experiments across different datasets.

Ancient Channel-Mouth Bifurcation Angles on Earth and Mars

Channel mouth bifurcation angles on modern river deltas are remarkably consistent with a theoretical prediction of 72°. However, the persistence of this angle through channel evolution and preservation into the stratigraphic record remains untested. Ancient channel mouth bifurcations were measured using stratal slices from 3D seismic volumes as well as outcropping delta deposits in Mars orbital imagery. We find that channel mouth bifurcations interpreted from terrestrial strata exhibit a mean angle of 71.9° ± 3.8° (95% confidence interval), consistent with modern deltas as well as theoretical and numerical predictions. Angles from martian strata preserved as inverted topography exhibit a mean angle of 80.1° ± 4.8°. A larger angle on Mars may be biased by measurements on eroding outcrops, or possibly the signature of altered sediment transport processes on Mars. Expanding channel network analysis into the stratigraphic archive for the first time provides a new mechanism interpreting paleohydraulics on Earth and Mars.

Integrating NMSA based advanced light-weight aggregated fusion channel network for robust tomato leaf disease detection

Integrating NMSA based advanced light-weight aggregated fusion channel network for robust tomato leaf disease detection

Parametric evaluation of line-of-sight (LOS) channel in LiFi networks

Parametric evaluation of line-of-sight (LOS) channel in LiFi networks

Computational approaches for identifications of altered ion channels in keratoconus.

Keratoconus is an etiologically complex, degenerative corneal disease that eventually leads to loss of corneal integrity. Cells in corneal epithelium and endothelium express various types of ion channels that play important roles in ocular pathology. This emphasizes the need of understanding alterations of ion channels in keratoconus. Differential gene expression analysis was performed to identify deregulated ion channels in keratoconus patients using transcriptomic data. Thereafter correlation analysis of ion channel expression was performed to obtain the changed correlation between ion channels' expression in keratoconus patients versus control samples. Moreover, Protein-protein interaction networks and a pathway map was constructed to identify cellular processes altered due to the deregulation of ion channels. Furthermore, drugs interacting with deregulated ion channels were identified. Total 75 ion channels were found to be deregulated in keratoconus, of which 12 were upregulated and 63 were downregulated. Correlations between ion channel expressions found to be different in control and keratoconus samples. Thereafter, protein-protein interactions network was generated to identify hub ion channels in network. Furthermore, the pathway map was constructed to depict calcium signalling, MAPK signalling, synthesis and secretion of cortisol, and cAMP signalling. The 19 FDA- approved drugs that interact with the 6 deregulated ion channels were identified. Down-regulation of voltage-gated calcium channels can be attributed to reduced cell proliferation and differentiation. Additionally, deregulated ion channels in 3',5'- cyclic adenosine monophosphate signalling may be responsible for elevated cortisol level in progressive keratoconus patients.

Fuzzy Adaptive Event-Triggered Consensus Control for Nonlinear Multiagent Systems Under Jointly Connected Switching Networks.

This article studies the fuzzy adaptive event-triggered (ET) consensus control issue of nonlinear multiagent systems (NMASs) under jointly connected switching networks. Since the leader and its high-order derivatives are unknown under jointly connected switching networks, a novel distributed ET reference generator equipped with an ET mechanism is constructed to estimate them. Meanwhile, the continuous information transmission among agents is avoided and the network channel utilization is optimized. Subsequently, fuzzy logic systems (FLSs) are employed to approximate unknown dynamics, and a fuzzy adaptive ET consensus control algorithm only using intermittent communication is designed by backstepping control methodology. It is demonstrated that all the closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB), with the tracking errors converging to a small neighborhood around zero. Finally, we apply the developed fuzzy adaptive ET consensus control algorithm to unmanned surface vehicles (USVs), and the simulation results verify the effectiveness of the proposed ET consensus control algorithm.

The Holocene evolution of the fluvial system of the southern Hessische Ried (Upper Rhine Graben, Germany) and its role for the use of the river Landgraben as a waterway during Roman times

Abstract. Intensive human intervention in the natural drainage system of the Hessische Ried (Upper Rhine Graben, Germany) resulted in the transformation of a large wetland into an intensively used cultural landscape. At least since the first century CE, when Romans conducted early river regulation and water management, the natural water network has experienced extensive anthropogenic re-organisation. The LandGraben project focuses on the reconstruction of the natural and anthropogenic watercourse systems along the river Landgraben, a tributary to the river Rhine in the northern Hessische Ried. Several rivers from the southern Hessische Ried could have fed the river Landgraben during Roman times via the meandering Palaeo-Neckar depression, thus increasing both length and discharge of the Roman waterway. In this study, we present results of our investigations within the southern Hessische Ried to reconstruct the former channel network that was used by Romans for the transportation of troops, wares and border security. Our approach integrates the use of high-resolution digital elevation models (DEMs) as a base for geophysical measurements (electrical resistivity tomography, ERT), direct push sensing and sediment coring in combination with sedimentological and geochemical analyses of the encountered sedimentary units. Local chronostratigraphies were established based on radiocarbon dating. Based on our results, we are able to differentiate a palimpsest of several abandoned fluvial channels throughout the southern Hessische Ried and to reconstruct the spatio-temporal development of the corresponding fluvial systems. Chronostratigraphic data show that the Palaeo-Neckar stopped flowing through the Hessische Ried around 10 000 cal BCE. Moreover, we found that the river Weschnitz, the largest of the possible Landgraben tributaries, stopped flowing through the Palaeo-Neckar depression at ca. 3000 cal BCE. Instead, it took a right-angled shortcut westwards to the river Rhine, north of the city of Lorsch. For the first time, we present geomorphological evidence that the river Weschnitz was not diverted by the Romans as speculated so far. This is corroborated by numerous wooden posts of human-made construction crossing an E–W running water course at the modern Weschnitz knee, with the oldest posts being dendrochronologically dated to the fourth and third millennia BCE. We further argue that the river Winkelbach/Lauter formed its knee towards the river Rhine and thus left the Palaeo-Neckar depression not later than the second century CE but most probably even contemporaneously with the formation of the Weschnitz diversion. In the case of the Winkelbach/Lauter, a high-energy flood event presumably related to strong rainfall and/or meltwater processes in the Odenwald Mountains is assumed to be responsible for the initiation of the new, diverted water course. With regard to the Landgraben and its use as a waterway within the Roman fluvioscape of the Hessische Ried, we therefore conclude that the Romans successfully collected water from several smaller rivers, such as from the rivers Modau and Darmbach and from even smaller tributaries, to make the river Landgraben a navigable waterway. The rivers Weschnitz and Winkelbach/Lauter, however, did not contribute any water to the Landgraben system during Roman times.

CSA-Net: Channel and Spatial Attention-Based Network for Mammogram and Ultrasound Image Classification.

Breast cancer persists as a critical global health concern, emphasizing the advancement of reliable diagnostic strategies to improve patient survival rates. To address this challenge, a computer-aided diagnostic methodology for breast cancer classification is proposed. An architecture that incorporates a pre-trained EfficientNet-B0 model along with channel and spatial attention mechanisms is employed. The efficiency of leveraging attention mechanisms for breast cancer classification is investigated here. The proposed model demonstrates commendable performance in classification tasks, particularly showing significant improvements upon integrating attention mechanisms. Furthermore, this model demonstrates versatility across various imaging modalities, as demonstrated by its robust performance in classifying breast lesions, not only in mammograms but also in ultrasound images during cross-modality evaluation. It has achieved accuracy of 99.9% for binary classification using the mammogram dataset and 92.3% accuracy on the cross-modality multi-class dataset. The experimental results emphasize the superiority of our proposed method over the current state-of-the-art approaches for breast cancer classification.

Assessing Irrigation Efficiency Improvements in Paddy Fields Using Granular SWMM Simulations

As water scarcity intensifies due to climate change, improving the efficiency of agricultural water use has become increasingly critical. Current irrigation systems often experience significant water losses, especially in paddy fields in South Korea that largely rely on open-channel water supply networks. However, previous studies have simulated irrigation improvement strategies by aggregating multiple paddy fields into larger unites rather than modeling them individually, which limits the accurate representation of field conditions. To address this limitation, we applied a granular simulation approach, collecting detailed input data through field surveys. Using this granular model, the study evaluated strategies to enhance irrigation efficiency in paddy fields serviced by the Baekma Agricultural Reservoir in South Korea. We assessed four scenarios: the current open-channel system, conversion of open channels to closed conduits, installation of farm ponds, and a combination of closed conduits and farm ponds. These scenarios were simulated using the Strom Water Management Model (SWMM), meticulously configured to represent individual paddy fields and channel networks. The results show that converting open channels to closed conduits increased irrigation efficiency by 5.4% compared to the current open-channel system. Combining closed conduits with farm ponds achieved the highest efficiency, although the independent effect of farm ponds was minimal. These findings suggested that converting open-channels to closed conduits was a highly effective solution for reducing water losses, while farm ponds played a limited role. This study provides valuable insights into the development of precise irrigation strategies, offering a detailed assessment of real-world conditions in paddy fields.

Polarity management of multicore fiber-based optical devices in unidirectional and bidirectional spatial channel networks

Polarity management of multicore fiber-based optical devices in unidirectional and bidirectional spatial channel networks

Color restoration of mural images based on a reversible neural network: leveraging reversible residual networks for structure and texture preservation

AbstractThe Mogao Grottoes in Dunhuang, a treasure of China's and the world's cultural heritage, contains rich historical and cultural deposits and has left precious relics of the history of human art. Over centuries, the Mogao Caves have been affected by natural and human factors, resulting in irreversible fading and discoloration of many murals. In recent years, deep learning technology has shown great potential in the field of virtual mural color restoration. Therefore, this paper proposes a mural image color restoration method based on a reversible neural network. The method first employs an automatic reference selection module based on structural and texture similarity to choose suitable reference mural images for the faded murals. Then, it utilizes a reversible residual network to extract deep features of the mural images without information loss. Next, a channel refinement module is used to eliminate redundant information in the network channels. Finally, an unbiased color transfer module restores the color of the faded mural images. Compared to other image color restoration methods, the proposed method achieves superior color restoration effects while effectively preserving the original structure and texture details of the mural images. Compared to baseline methods, the Structural Similarity Index (SSIM), Feature Similarity Index (FSIM), and Perception-based Image Quality Evaluator (PIQE) values are improved by 7.97%, 3.46%, and 13.98%, respectively. The color restoration of the Dunhuang Mural holds significant historical, artistic, cultural, and economic values, and plays a positive role in the preservation and inheritance of Chinese culture, as well as in the promotion of cultural exchange and mutual understanding.

Разработка DLP-модуля для защиты персональных данных в распределенной автоматизированной системе

The importance of personal data protection in automated systems is being considered. A study is provided on the development of a software module for protecting confidential information, including personal data, in a distributed automated system. The primary goal of the study: to create is to create software that prevents leaks of confidential information. The developed software module is designed to block the leakage of confidential information through network channels and removable media using a machine learning model with centralized security administrator management. The practical significance: the use of this module in organizations includes ensuring centralized information security management, reducing the risk of confidential data leaks, and supporting the investigation of security incidents. The research can be used as a temporary measure during the period of updating and adapting the system to new realities until a full-fledged protection system is achieved.

Ways to Organize and Identify Steganographic Channels in IP Networks

The article is devoted to an overview of network steganography methods that can be used to build hidden message transmission channels in IP networks, as well as methods aimed at identifying such hidden channels. The article gives the concept of a stegocontainer, and provides classification of network steganography methods. The article discusses the following methods of organizing hidden channels: the method of changing the contents of network packet headers, the Transcoding Steganography (TranSteg) method, the delay modulation method, the Lost Audio Packet Steganography (LACK) method, the Retransmission Steganography (RSTEG) method. In the review of the method of changing the contents of network packet headers, the principle of implementing changes in values in some service fields of IP (Internet Protocol) and TCP (Transmission Control Protocol) packet headers, which do not lead to data transmission failure, are considered. In the overview of the TranSteg method, the principle of transcoding the contents of network packets delivering real-time traffic is considered in order to free up space in the packet, which will be used to transmit hidden information. In the review of the delay modulation method, the principles of hidden message encoding are considered, which is carried out by changing the delay value of sending packets in the network. In the review of the LACK method, the mechanism of deliberate retention of RTP packets with an embedded steganographic message is considered. In the review of the RSTEG method, the principle of TCP segment exchange is considered, which provides the possibility of transmitting a steganogram. A number of parameters are given by which it is possible to conclude that there is a hidden channel in the network. The applicability of statistical methods and the methods with a classifier for detecting hidden channels in IP networks is considered. The expediency of implementing statistical methods and methods with a classifier in integration with systems for capturing and analyzing network traffic is indicated.

Stealthy Messaging: Leveraging Message Queuing Telemetry Transport for Covert Communication Channels

Covert channel methods are techniques for improving privacy and security in network communications. These methods consist of embedding secret data within normal network channels, making it more difficult for unauthorized parties to detect such data. This paper presents a new approach for creating covert channels using the Message Queuing Telemetry Transport (MQTT) protocol, widely used in the context of the Internet of Things (IoT). The proposed method exploits storage channels by altering the field length of MQTT messages. Our solution leverages well-known one-way mathematical functions to ensure that data remain hidden from third parties observing the MQTT stream. In this way, we ensure that not only the content of the communication is preserved but also that the communication itself takes place. We conducted a security analysis to show that our solution offers the above-mentioned property even against severe threats, such as an adversary being able to observe all the messages exchanged in the network (even in the clear). Finally, we conducted an overhead analysis of our solution both in terms of the time required to perform the required operations and of the bytes to send. Our study shows that our solution adds no significant time overhead, and the additional overhead in terms of transmitted bytes remains within acceptable limits.

Mangrove‐Saltmarsh Ecotones: Are Species Shifts Determining Eco‐Morphodynamic Landform Configurations?

AbstractMangrove‐saltmarsh ecotones are experiencing rapid alterations due to climate change and human activities, however, the ecological and morphological implications of these shifts remain largely unknown. This study systematically explores how interspecific interactions and herbivory influence the dominant wetland species, as well as the resultant morphological evolution and landscape configuration. To achieve this, we develop a new eco‐morphodynamic model that integrates hydrodynamics, sediment transport, bed‐level change, and vegetation dynamics. The novelty of the current model lies in newly incorporated modules to simulate biotic interactions between mangroves and saltmarshes, enabling exploration of eco‐morphodynamic feedback in mangrove‐saltmarsh ecotones in response to tidal flows and species interactions. Our results show that vertical growth rates of coexisting vegetation species are dominant factors in determining wetland dominance. When mangroves and saltmarshes exhibit comparable growth rates, mangroves typically become the dominant wetland species. Conversely, if mangroves grow more slowly than saltmarshes, they are unable to outcompete saltmarshes. Additionally, herbivory can fundamentally alter wetland dominance depending on herbivore food preferences. Our simulations further underline that saltmarsh‐dominated wetlands develop channel networks more extensively and rapidly than mangrove‐dominated systems. This pattern is also observed during species invasions, with invading saltmarshes extending channel networks, while invading mangroves inhibit ongoing network expansion. This study highlights the pivotal roles of relative growth properties and herbivory in driving ecotone development in respect to wetland dominance and channel network development at the intertidal scale.

Fast-Fading Channel and Power Optimization of the Magnetic Inductive Cellular Network

Fast-Fading Channel and Power Optimization of the Magnetic Inductive Cellular Network

Toward Aggregated Payment Channel Networks

Toward Aggregated Payment Channel Networks

Deadlock Prevention in Payment Channel Networks

Deadlock Prevention in Payment Channel Networks