International Journal of Communication Networks and Distributed Systems (21 papers in press)

Regular Issues

• Relatively Strong Barrier Coverage for β-Breadth Intruder in Hybrid Visual IoT  
  by Gong Chen, Yonghua Xiong, Jinhua She, Anjun Yu 
  Abstract: In the pursuit of reducing the costs associated with barrier coverage construction while maintaining surveillance quality, we propose a robust barrier coverage strategy for visual applications within the Internet of Things (IoT), considering the varying breadth of intruder paths. When coverage gaps arise or mission requirements evolve, it becomes imperative to reconfigure the network topology to sustain coverage through the rescheduling of sensor nodes. To minimize the rescheduling costs in hybrid networks, we develop a two-phase hybrid node rescheduling algorithm to achieve strong barrier coverage. The initial phase of our algorithm enables the static sensor nodes to optimize their operational directions, effectively reducing barrier gaps. In the second phase, we strategically reposition mobile sensor nodes to achieve a relatively strong barrier with the least number of nodes and the shortest total movement distance. Simulation results demonstrate that our algorithm outperforms existing methods in terms of efficiency and effectiveness.
  Keywords: IoT; Hybrid Network; Coverage Holes; Nodes Rescheduling.
  DOI: 10.1504/IJCNDS.2025.10062558
   
  
• Context-aware enhancement of buffer utilization in MQTT-based IoT communication  
  by P.S. Akshatha, S.M. Dilip Kumar 
  Abstract: This paper explores Internet of Things (IoT) communication and the crucial role of buffer utilization in enhancing the Message Queuing telemetry Transport (MQTT) protocol. Unlike traditional approaches that highlight the benefits of buffering, this study takes a distinctive perspective by addressing the limitations of buffer usage in IoT communication. The research introduces a context-aware strategy to employ buffers judiciously, considering specific data requirements and network connectivity scenarios. Experimental setups involving Node-RED, Wireshark, and prominent MQTT brokers (HiveMQ, EMQx, and Mosquitto) facilitate comprehensive performance analysis. Parameters such as connection setup time, subscription time, mean delay, mean jitter, and bandwidth consumption are evaluated. The findings consistently demonstrate performance degradation after broker reconnection, with more prolonged network failures leading to more significant degradation. The study emphasizes the importance of using buffers wisely, especially for prioritizing critical messages, to ensure reliability and enhance overall MQTT network performance.
  Keywords: IoT; Internet of Things; MQTT; message queuing telemetry transport; Node-RED; MQTT broker; buffer; QoS levels.
  DOI: 10.1504/IJCNDS.2025.10062897
   
  
• An innovative approach based on clustering and digital signature to prevent black hole attack from vehicular ad-hoc network  
  by Shahjahan Ali, Parma Nand, Shailesh Tiwari 
  Abstract: Due to broad development in wireless technology, the vehicular ad-hoc networks (VANETs) came into existence which can reduce the road accident, traffic jam and can increase the road safety. Because of dynamic topology, wireless medium, decentralised infrastructure, VANET is much more suspected towards various security attacks such as black hole in which control or data packets can be dropped by misbehaving vehicle, by which the safe path/link becomes compromised. In this research paper an innovative approach based on clustering and digital signature (CDS) is proposed to prevent black hole attack on reactive routing, i.e., ad-hoc on demand distance vector (AODV) and dynamic source routing (DSR) of VANET. The proposed approach is implemented and evaluated in SUMO-0.32.0 and NS-3.24.1 simulators. The novelty of this research work is that till now there is no approach (based on CDS) existed to prevent the black hole assault (BHA) from reactive routing in VANET.
  Keywords: VANET; vehicular ad-hoc network; routing; AODV; ad-hoc on demand distance vector; DSR; dynamic source routing; black hole; SUMO-0.32.0; NS-3.24.1; digital signature.
  DOI: 10.1504/IJCNDS.2025.10063476
   
  
• Blocking performance comparison under hard handoff constraint using optimal guard channel in GSM standards  
  by Promod Kumar Sahu, Hemanta Kumar Pati, Sateesh Kumar Pradhan 
  Abstract: In the current mobile networks voice service in 2G coexists with voice over long term evolution (VoLTE) in 4G and voice over new radio (VoNR) in 5G. In wireless networks usually handoff call (HC)s receive higher priority than new call (NC)s. So, some radio resources may be reserved in each cell to handle HCs. If more channels are reserved for HCs, then the handoff call dropping probability (HCDP) will be decreased and at that time the new call blocking probability (NCBP) will be increased. Instead, if channels will be reserved for HCs by considering the target HCDP, then HCDP will be below the target and will incur minimum NCBP. In this paper, we proposed an optimal channel reservation (OCR) policy to reserve guard channels according to the given target HCDP. Further, we have made a comparison study of optimal blocking performances applying this OCR policy on different GSM standards.
  Keywords: global system for mobile communication; handoff call dropping; mobile cellular network; new call blocking; optimal channel.
  DOI: 10.1504/IJCNDS.2025.10063481
   
  
• Self energised UAV-assisted wireless communication using NOMA over Nakagami-m fading channel  
  by G. Sivakannu, R.S. Anju, J. Anandpushparaj, P. Muthuchidambaranathan 
  Abstract: In a cooperative relay network, replacing the relay with an unmanned aerial vehicle (UAV) offers several advantages. In this work, a UAV-assisted communication network based on non orthogonal multiple access (NOMA) system that incorporates simultaneous wireless information and power transfer (SWIPT) technique is investigated. The performance of the proposed system is analysed by deriving the closed form expression for performance metrics like outage probability (OP), throughput and bit error rate (BER) under imperfect successive interference cancellation (SIC) with selection combining (SC) diversity technique at the receiver. In addition to that, a Multiple UAV based system model is considered with relay selection algorithms like max-min selection and the variation in the outage probability performance is also studied. The analytical expressions are also validated using Monte Carlo simulation. The results show that the proposed system has better performance even under imperfect SIC and reduces the wastage of resources.
  Keywords: NOMA; non orthogonal multiple access; cooperative relaying system; SWIPT; simultaneous wireless information and power transfer; time splitting; SIC; successive interference cancellation; selection combining; outage probability; BER; bit error rate.
  DOI: 10.1504/IJCNDS.2025.10063634
   
  
• Secure emergency MAC protocol for wireless body area networks  
  by Bhavana Alte, Amarsinh Vidhate 
  Abstract: Wireless body area networks (WBANs) connect many small body sensors for Internet of Things healthcare applications. In vivo and on-body sensor nodes allow WBANs to detect and gather biometric data on bodily changes. Wireless transmission sends observed data. This information can help patients in critical condition or who cannot reach to hospitals due to physical handicap, traffic, and receive immediate care. Another crucial requirement for WBANs is capacity to provide quality of service (QoS) for different traffic data. Security and privacy are needed for healthcare professionals to use and store patient records securely. It is crucial for WBANs to address privacy and security concerns. The proposed method introduces the emergency MAC (E-MAC) super-frame architecture, enabling QoS. E-MAC accelerates and reliably transmits emergency data via an emergency information management system. To address security concerns, the approach is protected using elliptic curve cryptography. Results show that E-MAC outperforms IEEE 802.15.6.
  Keywords: WBAN; wireless body area network; ECC; elliptic curve cryptography; MAC protocols; emergency traffic; duty-cycle MAC.
  DOI: 10.1504/IJCNDS.2025.10064449
   
  
• Blockchain-based privacy-preserving technology to secure shared data in vehicular communication  
  by Omessaad Slama, Walid Dhifallah, Salah Zidi, Jaime Lloret , Bechir Alaya, Mounira Tarhouni 
  Abstract: In vehicular ad-hoc networks (VANETs), securely exchanging sensitive data like misbehaviour detection models faces significant security and privacy hurdles. Our solution, machine learning model blockchain-based privacy-preserving (MBPP), combines Blockchain technology and advanced cryptography to tackle this. MBPP ensures data confidentiality and integrity while improving detection model reliability. It involves securely storing ML models on the blockchain using cryptographic hash functions. Our study meticulously evaluates transactional time and computational costs, vital for smooth blockchain transactions. This research not only presents a conceptual framework for blockchain use in VANETs but also offers insights into managing transactions via smart contracts, addressing VANETs' security and privacy challenges effectively.
  Keywords: blockchain; smart contract; computational costs; artificial intelligence algorithms; VANETs; vehicular ad-hoc networks; data sharing; privacy preservation; cryptography hash function.
  DOI: 10.1504/IJCNDS.2025.10064597
   
  
• Harnessing machine learning for dynamic defence in the battle against 5G cybersecurity threats  
  by V. Aanandaram , P. Deepalakshmi 
  Abstract: The evolution mobile network highlighted by means of 5G networks, has caused advanced cyber threats necessitating modern security features. The adaptive multi-layer threat defence machine addresses these threats with machine getting to know (ML), presenting robust resilience. It surpasses traditional strategies via deploying ML algorithms throughout more than one network layers. Network behaviour profiling (NBP) establishes baselines for customers/gadgets, detecting deviations as early malicious signs. Intent prediction (IP) visually anticipates person purpose, while anomaly detection (AD) identifies subtle anomalies. The systems centre, decentralised associative learning (federated learning), keeps confidentiality and model integrity. Continuous Threat Intelligence Integration (TII) permits proactive responses to rising threats. This integrated approach provides better protection for 5G networks, creating an adaptive defence via profiling, prediction and anomaly detection. The adaptive multi-layer threat defence system, combining flexibility, privacy, and scalability, ushers in a generation in which ML supports technological development.
  Keywords: AML-TDS; adaptive multi-layered threat defence system; threat intelligence; anomaly detection; privacy preservation; 5G network security; NBP; network behaviour profiling; cyber threats.
  DOI: 10.1504/IJCNDS.2025.10065033
   
  
• A linear regression based prediction model for load distribution and quality of service improvement with different resource utilisation in cloud environment  
  by Gopa Mandal, Santanu Dam, Kousik Dasgupta, Paramartha Dutta 
  Abstract: Cloud computing is a delivery-based consumption model rely over the internet Uses of cloud enabled devices increasing rapidly So, to maintain quality of service (QoS), throughput of the entire system with service level agreements(SLA) is major concern between the service providers and the end users Alternative techniques for virtual machine (VM) consolidation and proper workload allocation may beneficial This study proposes a linear regression-based prediction model for load distribution and QoS improvement The model aims to enhance system throughput and QoS by predicting resource utilization levels using historical consumption data Experiments conducted using CloudSim and CloudAnalyst platforms demonstrate positive results, outperforming existing methodologies The study also evaluates Service Level Agreement Violation (SLAV) and delays to assess the QoS provided by the CSP Overall, this research contributes to the enhancement of QoS in cloud and cloud enabled systems like IoT, CoT, addresses the challenges of optimize resource utilization while ensuring QoS.
  Keywords: CoT; cloud of thing; IoT; Internet of Things; VM consolidation; cloud computing; QoS; quality of service; CloudSim; CloudAnalyst; linear regression.
  DOI: 10.1504/IJCNDS.2025.10065020
   
  
• Joint coded caching and distributed storage with product matrix non-systematic code  
  by Natasa Paunkoska-Dimoska, Venceslav Kafedziski 
  Abstract: The coded caching technique and data distribution on multiple servers, known as a distributed storage system (DSS), are two separate concepts that bring various improvements to the communication environment. Combining the two techniques enhances the user network performance by decreasing the peak rate, optimizing the user memory and decreasing the latency. This paper investigates the benefits of merging coded caching and distributed storage in various multiserver systems. Hence, we propose a new construction called the non-systematic. This approach considers using a multi-server system consisting of only parity servers and encoded linear combinations of popular file segments based on a predefine non-systematic code in the placement and delivery phases making this concept attractive in terms of security. The proposed concept achieves optimized results regarding the peak rate and the user cache memory and tremendously improves the data security compared to other multi-server systems.
  Keywords: coded caching; cache memory; distributed storage; multi-server system; peak rate; security; systematic code; non-systematic code.
  DOI: 10.1504/IJCNDS.2025.10065568
   
  
• Enhancing road safety: UAV-enabled warning message dissemination in urban and rural environments for VANETS  
  by Leila Bouchrit, Sajeh Zairi, Ikbal C. Msadaa, Amine Dhraief 
  Abstract: Vehicular ad hoc networks (VANETs) safety applications aim to mitigate the growing frequency of daily road accidents. These applications require the prompt dissemination of warning messages among vehicles, regardless of traffic conditions or environment. The limited terrestrial coverage in sparsely populated rural regions challenges the timely receipt of warnings during accidents. To address these issues, integrating unmanned aerial vehicles (UAVs) into VANETs offers a promising solution. UAVs can function as flying relays, meeting necessary delay limitations and overcoming communication problems. In prior work, we introduced a unified UAVs-VANET architecture, using UAVs to relay safety messages among vehicles in rural settings. This paper extends that work by integrating UAVs in rural and urban environments. Our approach includes determining the minimal residual UAV energy needed to connect to a charging station, ensuring continuous UAV operation. This extended framework ensures all vehicles on a 25 km urban highway receive alerts within 1.95 seconds.
  Keywords: VANET; vehicular ad hoc network; urban environment; rural environment; UAV; unmanned aerial vehicle; LTE/4G D2D; long term evolution device-to-device; IEEE 802.11p; energy optimisation.
  DOI: 10.1504/IJCNDS.2025.10065615
   
  
• Parallel iterative algorithms for Markovian systems on distributed architectures  
  by Mohamed Jarraya 
  Abstract: This paper explores parallel iterative methods for solving Markovian systems, aiming to tackle computational challenges in scientific and industrial contexts. Two strategies for parallelising the Gauss-Seidel iterative scheme in the circuit-switching networks model are deployed and evaluated on both shared memory multiprocessor systems and networks of shared memory multiprocessor machines. The first strategy involves modifying the Gauss-Seidel iterative scheme, while the second employs a colouring technique for components in red and black. An activation message-based termination method is introduced for asynchronous iterations on networks of shared memory multiprocessor machines. Additionally, a novel parallel iterative method for general Markovian systems is proposed and evaluated for both synchronous and asynchronous implementations. This method distributes computational workload differently from the conventional approach used in circuit switching networks.
  Keywords: Markovian systems; asynchronous iterations; synchronous iterations; termination algorithms; shared memory multiprocessor; network of shared memory multiprocessor; relaxation method; over-relaxation method; parallel alternate components relaxation method.
  DOI: 10.1504/IJCNDS.2025.10066711
   
  
• Adoption of Internet of Things (IoT) among manufacturing SMEs in developing countries: a TOE framework perspective  
  by Syeda Khadija Mubeen, Ali Vafaei-Zadeh, Azlan Amran, Chang Ruiqi 
  Abstract: This study develops and validates an eight-driver framework by integrating Technology-Organisation-Environment (TOE) theory with institutional theory to enhance understanding of IoT adoption intentions. SMEs in developing nations face challenges such as inadequate technological infrastructure, limited organizational resources, and external support. Focusing on Pakistani manufacturing SMEs, this research investigates the influence of the TOE framework and institutional theory on IoT adoption intentions, using data from 207 firms analysed through PLS-SEM. The analysis supported seven of the proposed hypotheses, demonstrating positive impacts of TOE drivers on IoT adoption intentions, except for cost. Limitations include the restricted scope of data collection and the omission of pre-adoption phases. This research provides valuable insights into how IoT can strategically benefit manufacturing SMEs in Pakistan, offering guidance for policymakers, researchers, and practitioners. Recommendations include the need for SMEDA and the Pakistani government to improve technology adoption processes and implementation at the global level.
  Keywords: TOE framework; technology adoption; IoT; Internet of Things; manufacturing SME sector; institutional theory; PLS-SEM; partial least squares structural equation modelling.
  DOI: 10.1504/IJCNDS.2025.10067141
   
  
• Weight possibilistic fuzzy C-means energy-efficient clustering (WPFCM-EEC) and fuzzy osprey optimisation algorithm (FOOA) for IoT-WSN  
  by T. Kanimozhi , S. Belina V.J. Sara, S.Albert Antony Raj 
  Abstract: The wireless sensor network (WSN) is a key component of IoT systems. Wireless sensing nodes in WSNs have energy limitation issues since replacing or recharging their batteries and upgrading their transmitting and memory capacity is difficult. Thus, clustering algorithms efficiently save node energy and lengthen IoT-based WSN lifespan. These protocols cluster nodes to communicate with a BS at a shorter distance. However, clustering structure concerns hurt current clustering methods. In this research, the weight possibilistic fuzzy C-means-energy efficient clustering (WPFCM-EEC) protocol is presented to extend IoT-based WSN lifetime. The WPFCM-EEC protocol has three parts. First, the optimal cluster count and overlap are established. Next, a weight possibilistic fuzzy C means algorithm creates balanced and static clusters to ensure sensor node energy balance. A unique Cluster Head selection and rotation algorithm that combines the fuzzy osprey optimisation algorithm (FOOA) with a rotation mechanism selects CH in optimal locations by rotating the cluster head function across cluster members. The methods are tested in MATLAB R2023a. Protocol evaluation indicators include first node dies (FND), last node dies (LND), weighted first node dies (WFND), half of the nodes dies (HND), average energy consumption, and throughput.
  Keywords: WSN; wireless sensor network; WPFCM-EEC; weight possibilistic fuzzy C-means-energy efficient clustering; IoT; Internet of Things; FND; first node dies; FOOA; fuzzy osprey optimisation algorithm; LND; last node dies; WFND; weighted first node dies.
  DOI: 10.1504/IJCNDS.2025.10067367
   
  
• Integration of GRU Features with Q-Learning based VARMA for Protocol DDoS Attack Analysis  
  by Meghana Solanki, Sangita Chaudhari 
  Abstract: Network security faces severe threats from attacks on distributed denial of service (DDoS), necessitating attack detection and mitigation. This study introduces a novel approach by integrating Gated Recurrent Unit (GRU) features with a Q-Learning basedVector Autoregressive Moving-Average (VARMA) process for protocol DDoS attack analysis. Traditional models could not deal with complex temporal dependencies in network traffic data, whereas deep learning models lack interpretability and incremental learning. Our model combines Q-Learning based VARMA and GRU, accurately capturing temporal dynamics to detect protocol DDoS attacks. It facilitates incremental learning for adaptation over time. With applicability across diverse contexts, the model offers real-time attack identification, enhancing network security. Experimental results demonstrate superior performance in recall, precision and accuracy compared to existing machine learning and deep learning models.
  Keywords: protocol DDoS attacks; GRU features; Q-learning; VARMA and process; traffic volume; patterns; internet protocol (IP) address; port number; packet size; data rate.
  DOI: 10.1504/IJCNDS.2025.10067549
   
  
• Wireless communication interference signal recognition model based on deep CNN  
  by Bo Liang 
  Abstract: A complex neural network model based on deep convolutional neural networks is proposed to enhance recognition and suppression of interference signals in wireless communications. The model introduces a signal suppression network to address poor reception due to signal interference during transmission, which is a significant challenge in maintaining communication quality in increasingly complex wireless environments. Results show higher recognition accuracy for different interference signals at varied decibels. In complex networks, interference signal recognition accuracy is superior, with noise recognition accuracy surpassing other networks by 5% and 2%. The research method exhibits a lower bit error rate and 0.5dB better amplitude suppression compared to traditional methods. The approach excels in interference signal identification and suppression, improving wireless communication signal recognition performance significantly. This advancement is crucial in ensuring the reliability and security of wireless communication systems, offering a novel solution to the growing challenges posed by interference in modern communication networks.
  Keywords: wireless communication signal; BER; bit error rate; signal interference; CNN; convolutional neural network; accuracy; noise.
  DOI: 10.1504/IJCNDS.2025.10067633
   
  
• A hybrid zone-based routing protocol based on ZRP and DSR for emergency applications  
  by Sanjoy Debnath, Wasim Arif 
  Abstract: Mobile ad-hoc networks (MANET) can be rethought for use in disaster relief operations due to their attractive features, such as no infrastructure, fast deployment, and self-organisability. It has also been observed that improving scalability, mobility, bandwidth, and energy efficiency has always been a challenging aspect of ad-hoc routing protocols like MANET. This paper presents a comprehensive survey of all the promising routing protocols in MANET, considering key constraints such as energy efficiency and throughput delivery in disaster relief operations. After that, we proposed HZDL, a hybrid routing protocol based mainly on ZRP and DSR with cluster hierarchy features from the LEACH algorithm. The key controlling parameters include the mobile node's processing speed, background running applications, data storage capacity, and residual battery power. The results of a comprehensive simulation encompassing several performance measurement matrices reveal that the proposed algorithm provides significantly improved results towards improving the node's lifetime and achievable throughput.
  Keywords: MANET; mobile ad-hoc networks; hybrid routing protocol; energy efficiency; disaster management.
  DOI: 10.1504/IJCNDS.2025.10061546
   
  
• An efficient attack detection approach for software defined Internet of Things using Jaya optimisation based feature selection technique  
  by Pinkey Chauhan, Mithilesh Atulkar 
  Abstract: Software defined Internet of Things (SD-IoT) has drawn several attacks because of its novelty. To counter such attacks, this paper presents a study on feature selection using Jaya Optimisation for making the lightweight intrusion detection system (IDS) for the data plane of SD-IoT. To check the effectiveness of the selected features, an ensemble of tree-based classifiers that uses a boosting approach called light gradient boosting machine (LGBM) is trained and tested with all features (AF) and then with selected features (SF) using 10-fold cross-validation. It was found that LGBM gave better performance when it was trained with SF. For performance evaluation, some well-known metrics have been used, namely recall, accuracy, false alarm rate (FAR), F1, precision, Cohen's Kappa coefficient (CKC), and prediction time. This trained model is deployed for attack detection in the OpenFlow-enabled devices of data plane of SD-IoT where it can detect the attacks in a distributed manner.
  Keywords: OpenFlow; Ryu Controller; SD-IoT; software defined Internet of Things; Jaya Optimisation; machine learning; distributed denial of service attack.
  DOI: 10.1504/IJCNDS.2025.10062282
   
  
• Network-aware cache provisioning and request routing in heterogeneous cellular networks  
  by Marisangila Alves, Guilherme Piêgas Koslovski 
  Abstract: In past years there has been an increase in the number of mobile devices and data traffic triggered by the popularisation of multimedia applications. In parallel, new applications and services with restricted requirements of delay and throughput have been developed. The 5G architecture is an enabler for such evolution, however, some fundamental management tasks deserve deep research, especially the cache placement. There are still challenges concerning the design of caching policies, such as limited storage space, content popularity, users requirements, and network congestion. In this context, we propose, implement, and evaluate a model of network-aware cooperative cache policy to decrease the latency experienced by heterogeneous cellular network (HCN) end-users. The model was formulated through integer linear programming (ILP) and performs both cache placement and request routing tasks. To compose a baseline for comparisons, we improved state-of-the-art policies by adding network-based attributes. Later, numerical simulations showed that the policy successfully chose paths decreasing the network latency and overcoming the counterparts.
  Keywords: caching; heterogeneous cellular networks; placement; routing.
  DOI: 10.1504/IJCNDS.2025.10062283
   
  
• The intelligent object detection framework for detecting fish from underwater images  
  by Kalyani Peddina, Ajay Kumar Mandava 
  Abstract: Marine applications heavily rely on underwater object detection, yet challenges like complex backgrounds and image quality issues impede deep learning-based detectors. Monitoring feed pellet utilisation in aquaculture is vital for efficient resource management. This study introduces a novel framework, DYNFS, merging underwater object detection and image reconstruction using YOLO-V5. Initially, we curate an underwater image dataset, refining it to remove noise, and then employ DYNFS for classification. Our approach achieves a 98.93% accuracy rate in identifying submerged feed pellets, crucial for aquaculture efficiency. However, locating pellets remains challenging due to poor image quality and small object sizes. The enhanced YOLO-V5 networks show promise in real-world aquaculture scenarios. This framework enhances underwater object detection, offering potential benefits for marine applications and aquaculture management.
  Keywords: detection; image data; convolutional neural network confusion matrix; YOLO network; recurrent neural network.
  DOI: 10.1504/IJCNDS.2025.10062690
   
  
• Addressing escalating threats: a secret image sharing scheme with adjustable threshold resilience against external adversaries and colluding participants  
  by Krishnaraj Bhat, Devesh Jinwala, Yamuna Prasad, Mukesh A. Zaveri 
  Abstract: We propose a novel threshold changeable secret image sharing (TCSIS) scheme based on univariate and asymmetric bivariate polynomials for securing greyscale and colour secret images in the semi-honest model. The proposed scheme supports increasing the threshold number of shares needed to reveal the secret image using the share update mechanism. Unlike the existing TCSIS schemes, the proposed scheme can prevent the revealing of a secret image before the end of its lifespan. This revelation is possible due to the increasing capabilities of an external adversary and the increasing number of colluding participants. Furthermore, in contrast to some existing TCSIS schemes, each share generated using the proposed scheme does not leak visual information about the secret image. We prove the properties of the proposed scheme using theoretical analysis. We also provide experimental results supporting the implications of theoretical analysis corresponding to the execution time and the randomness of shares.
  Keywords: image security; secret image; TCSIS; threshold changeable secret image sharing; external adversary; colluding participants; information leakage; univariate polynomial; asymmetric bivariate polynomial.
  DOI: 10.1504/IJCNDS.2025.10063445