International Journal of Ad Hoc and Ubiquitous Computing (29 papers in press)

Regular Issues

• Modeling and Optimization of High-speed KLEIN Architectures on FPGA and ASIC Platforms for IoT Applications  
  by Pulkit Singh, Rahul Kumar Chaurasiya, Bibhudendra Acharya 
  Abstract: Security and privacy are serious issues in the internet of things (IoT) emerging areas. The lightweight cryptographic algorithms are immensely important for secure communication in High-speed IoT applications. The objective of this work is to obtain optimized architectures from scalar and pipelined designs from modified KLEIN cipher implemented on field programmable gate arrays (FPGA) and application specific integrated circuits (ASIC) platforms. This analysis is carried out based on examined hardware metrics such as frequency, area, power, and energy consumption. A one-round scalar implementation shows 73.1% & 93.3% lesser power and 70.7% & 93.1% energy efficient compared to one-round pipelined implementation on both platforms. In addition, this paper demonstrates that modeled and optimized implementations of modified KLEIN cipher show good accuracy compared to state-of-the-art design models. Hence, this paper gives general guidelines for all lightweight block ciphers by noticing the behavior of modified KLEIN cipher.
  Keywords: Security; S-box; lightweight cryptography; block cipher; KLEIN.
  
  
• Comparative Analysis of Image Classification with Retrieval System  
  by JATOTHU BRAHMAIAH NAIK, SivaNagiReddy Kalli, Ravi Boda 
  Abstract: Currently, the term Content-based Image Retrieval seems to be a highly attentive system for handling the broad image datasets since the data storage mechanisms & image acquisition are becoming the most empowered logic in image processing. The previous CBIR system has been proposed under nonlinear similarity matching measure in a logarithmic scale & informative pattern descriptor has quantified the range of similarity content. This article implements a novel CBIR system that emphasizes the classification concept using a Deep Belief Network (DBN) classifier. In this concept, apart from the image retrieval, the used classifier classifies the respective classes of retrieved images. Finally, the Proposed Local Vector Pattern (PLVP) with DBN classifier (PLVP-DBN) compares its performance over other conventional retrieval concepts: PLVP-With Log similarity, PLVP-Without Log Similarity, and also with Neural Network (NN) classifier.
  Keywords: Image retrieval; CBIR system; DBN; NN; PLVP-DBN.
  
  
• Intrusion Detection System using Resampled Dataset - A Comparative Study  
  by N.D. Patel, B.M. MEHTRE, Rajeev Wankar 
  Abstract: Existing machine-learning research aims to improve the predictive capability of datasets using various feature selection and classification models. The intrusion detection data consists of normal data and a minimal number of attack data. This data imbalance causes prediction performance degradation due to factors such as prediction bias of small data presence of outliers. To address this issue, we oversampled the minority class of the existing intrusion detection datasets using four data oversampling methods and tested using three different classifiers. To further ensure the real-time applicability of these oversampling methods with these classifiers, we also generate a real-time testbed (RTT) resampled dataset. It is observed that CTGAN oversampling method, along with the LightGBM classifier, gives outperforming results on the existing CICIDS2018 and RTT resampled dataset. Test results also outperformed over the existing intrusion detection methods and datasets (Credit Card, Gambling Fraud, ISCX-Bot-2014, CICIDS2017) in terms of Accuracy, Precision etc.
  Keywords: Intrusion Detection System; Data Imbalance; SMOTE; BorderlineSMOTE; ADASYN; CTGAN; Oversampling; Classification Model; NSL-KDD;\r\nCIC-IDS2018; Attack Detection System.
  DOI: 10.1504/IJAHUC.2022.10050801
   
  
• Game-based Congestion-Aware Routing Algorithm in Wireless Network on Chips  
  by Esmaeel Tahanian, Alireza Tajary, Mohsen Rezvani 
  Abstract: Wireless Network-on-chip (WiNoC) has been introduced to alleviate some challenges with conventional NoC such as high latency and powerrnconsumption. According to the limited resources, the performance of WiNoCrnis sensitive to routing algorithm. Routing the packet through the wireless linksrnfor arriving to far apart destination leads to a shorter path. Therefore, many ofrnnodes prefer to send their packets to nearest wireless router for routing on thernWiNoC. When the demand for a wireless node increases, the likelihood of therncongestion increases in that node and its neighboring nodes that consequentlyrndegrades the performance of the network. To address this problem, we propose a game-based yet simple routing algorithm to balance the traffic in thisrnpaper. The WiNoC is modeled with a mixed-strategy Bayesian-game in whichrnthe nodes are the players with two valid actions namely, routing the packets with and without the wireless links. By employing the Nash Equilibriumrnproperty, we determine the probability of choosing the valid actions by eachrnplayer. The simulation results show that using the proposed mixed-strategyrnfor routing the packets considerably improves the performance of the network,more precisely, the system performance is improved 10%-42% compared withrnthe previous related works.rn
  Keywords: Wireless Network on Chips (WiNoCs);Routing algorithm;Game theory.
  
  
• A two dimensional Markov chain model for aggregation-enabled 802.11 networks  
  by Kaouther Mansour 
  Abstract: Frame aggregation technique opts for optimizing channel usage efficiency for 802.11-based networks by amortizing the transmission overhead over several aggregated packets. Despite its potential benefit, the gain achieved by this technique is still far from the expected levels. The underlying causes are attributed to certain deficiencies in the specification as well as the implementation of the conventional frame aggregation scheme. Throughout this paper, we focus on MAC Protocol Data Unit aggregation (A-MPDU) technique. We provide a simple, yet, highly accurate mathematical model for the conventional A-MPDU technique that reflects the effect of the Block Acknowledgement (Block Ack) window limit on the maximum aggregation size. The effectiveness of our model is validated by ns-3 simulator. An analytical-based study is further conducted to compare the performance of the greedy A-MPDU aggregation scheme and that of the conservative scheme supported by most of Wireless Fidelity (Wi-Fi) card drivers.
  Keywords: 802.11 WLANs; performance evaluation; analytical model; frame aggregation; A-MPDU.
  
  
• Gene Expression Data Classification with Robust Sparse Logistic Regression using Fused Regularization  
  by KAMPA LAVANYA, Pemula Rambabu, Vijay Suresh, Rahul Bhandari 
  Abstract: Microarray technology has become popular and is extensively used in gene classification. It is essential to identify a set of gene expressions used to classify cancer data with better accuracy. However, microarray data is of kind high dimensional and penalized logistic regression (PLR) is good for variable selection and classification. The Lasso, Ridge and Elastic Net are limited to produce oracle property and sparsity. The regression with Weighted L1 and L2 penalty results the oracle property and sparsity. To extend robustness to the gene classification applied absolute deviation regression. In this work, a Fused Logistic Regression (FLR) has been introduced using Weighted L1 and L2 penalties for gene selection. The proposed work introduces smarter grouping effect by updating regression coefficients with Coordinate Descent Algorithm (CDA). The work tested over the simulated and real data sets and produced superior results than the existing methods.
  Keywords: Microarray Data; Regularization; Feature Selection; Sparse Logistic Regression; and Robust Lasso.
  
  
• XACML-based Semantic Rules Language and ontological model for reconciling semantic differences of access control rules  
  by Manal Lamri, Sabri Lyazid 
  Abstract: Internet of Things interconnects increasing numbers of artefacts (e.g., robot), individuals, etc., allowing therefore set up Ambient Intelligence systems in multi-domains (e.g., homes, hospitals, airports, etc.). Thus, design methodologies and a suitablernarchitecture framework are required to ensure the efficiency and sustainability of the implementation of such systems. Consolidating public services about citizens safety and the authorization decisions when a resource is accessed in an open-dynamic environment (i.e., multi-domain) are the main challenges that can be highlighted. Thus, the semantic heterogeneity between the local policies of the different domains is a crucial lock for implementing this process. Ontology aims to reduce this ambiguity through semantic interoperability by providing a unified knowledge representation. The Semantic Web Languages appear unsuitable for managing dynamics knowledge. Our approach goes beyond the semantic web languages weakness by combing the XACML-based security policy model with a Semantic Rules Language developed during the European SembySem Project.rn
  Keywords: Ontology; Internet of Things; Distributed Systems; Authentication; Access Control; Multi-Domain; XACML.
  
  
• Identity-Based Ring Signature Scheme With Multi-Designated Verifiers  
  by Yunyun Qu, Jiwen Zeng 
  Abstract: As far as we know, there is only one ring signature scheme with multi-designated verifiers in the literature and the scheme is based on the bilinear pairings which need to consume a lot of computation and under the traditional public key infrastructure(PKI). In order to improve computational efficiency and solve the problem of certificate management in PKI, in this paper, we propose the first identity-based ring signature scheme with multi-designated verifiers without pairings. We prove that our novel schemes unforgeability, anonymity in the random oracle model and indistinguishability in the standard model under the intractability assumption of discrete logarithm problem and decisional Diffie-Hellman problem, and we prove that our novel schemes non-transferability in the standard model. We compare the new scheme with a previous scheme in terms of computation and communication at last. The results show that our new scheme is more efficient than the previous scheme and is more suitable for the multi-user setting.
  Keywords: Identity-based ring signature; Multi-designated verifiers; Discrete logarithm problem; Decision Diffie-Hellman problem.
  
  
• Satisfaction-Driven Cooperative Trajectory Optimization for Multi-UAV-Assisted Mobile Edge Computing  
  by Cuntao Liu, Yan Guo, Ning Li, Weibo Yu 
  Abstract: This paper investigates an unmanned aerial vehicle (UAV)-assisted mobile edge computing scenario, where multiple UAVs provide computational services for user devices (UDs) with different service priorities. Taking into account UDs' different service priorities as well as diverse computation-offloading demands, a satisfaction-model is proposed, which gives consideration to UDs' satisfaction degree toward the offloading services as well as the fairness of their offloading amount. We aim to maximize UDs' sum satisfaction by jointly optimizing the offloading time allocation, computing time allocation, users' transmit power, as well as UAV trajectory. A non-convex optimization problem is formulated and an effective solution framework is proposed, where the problem is decomposed into three sub-problems that are solved alternately and iteratively by applying successive convex approximation (SCA) technique. Numerical results show that the proposed scheme achieves higher satisfaction with lower standard deviation as compared to benchmark schemes.
  Keywords: Unmanned Aerial Vehicle (UAV); Satisfaction; Cooperative trajectory optimization; Mobile Edge Computing (MEC).
  
  
• Storage space reduction in Picture Archiving and Communication System using Generative Adversarial Network  
  by Bejoy Varghese, Krishnakumar S. 
  Abstract: This paper presents a new architecture of Picture Archiving and Communication System (PACS) based on Generative Adversarial Network (GAN) and Fractal Image Compression (FIC). The GAN architecture is modified to be a conditional GAN by conditioning the generator with the uncompressed image. Both the generator and discriminator networks utilize the Convolutional Neural Network (CNN) which enable the system to capture the similarity measures without using any handcrafted functions. Performance of the proposed design is evaluated by comparing it with the commonly used compression techniques in PACS and recently reported best performing machine learning compression techniques. The efficiency of the proposed architecture is tested by using a custom client program that sends the modality images to the PACS server. The simulation runs on computers in multiple networks to gather the data similar to real time healthcare institutions. The simulation shows that the storage space consumption of the proposed design is only 30% in comparison with PACS, which uses the latest Machine learning and conventional non fractal compression methods. It is also observed that the GAN based FIC can drastically reduce the compression time compared to the conventional fractal and non fractal compression methods. The empirical analysis shows that the proposed GAN architecture can be a promising method to reduce the space complexity of the system such as PACS.
  Keywords: Image Compression; Picture Archiving and Communication System ; Generative Adversarial Network ; Fractal Compression.
  
  
• Efficacious Tuning in Energy Efficient Street Lighting  
  by Pragna Labani Sikdar, Abhinav Anurag, Parag Kumar Guha Thakurta 
  Abstract: An energy efficient street lighting system is proposed in this paper to obtain a balance between energy savings and utility in terms of illumination by the street lights. The finite coverage of every street light equipped with the sensor is divided into zones according to the distance of the nearest pedestrian or vehicle with respect to that street light. The illumination of the street light is adjusted accordingly with respect to zones. Every street is divided into sections depending on the average distance between street lights. The parameters namely the energy savings as well as the utility of the lights in a section are defined in terms of the values of length of a zone and the factor of brightness decrement per zone. The best value of this decrement factor is determined by tuning to obtain energy efficiency. Simulation results highlight that the proposed work outperforms the existing method. As an outcome, the proposed scheme obtains a superior % of energy savings over existing work without falling below minimum utility for a small inter-distance.
  Keywords: Street Lights; Energy; Power; Brightness; Tuning; Illumination.
  
  
• Routing Techniques for Millimeter Wave Communications  
  by Faisal Alanazi 
  Abstract: In this paper, we propose three routing protocols for millimeter wave communications. One Hop Routing Protocol (OHRP) consists to choose the best relay in each hop. Optimal Routing Protocol (ORP) consists to activate the path with the highest end-to-end Signal to Interference plus Noise Ratio (SINR) among all available $N^{L-1}$ paths where $N$ is the the number of branches (number of relays in each hop) and $L$ is the number of hops. SubOptimal Routing Protocol (SORP) decomposes the network in $K$ subnetworks then the best path is activated in each subnetwork. Our analysis is valid for millimeter wave communications in the presence of $P$ interferers at each relay node.
  Keywords: Routing; Millimeter wave; outage probability.
  
  
• Fitness approximation with RF algorithm dedicated to WSN node deployment for a soil monitoring application  
  by Soumaya Ferhat Taleb, Nour-El-Houda Benalia, Rabah Sadoun 
  Abstract: In order to solve the Wireless Sensor Network (WSN) node deployment optimization for an agricultural application, an hybridized Strength Pareto Evolutionary Algorithm II with the Random Forest Regressor (RF-SPEA II) was used. The SPEA II intended to optimize the deployment according to the classical constraints of coverage, over-coverage, connectivity and node number, in addition to the nodes separating distance constraint, which affects the predicted physical parameters models quality. Furthermore, the RF regressor was applied as a fitness approximation surrogate model, with the use of evolutionary control rate to avoid convergence to false optimums. Moreover, the application of RF features selection skill that helped to only keep important characteristics and gain more time. Consequently, this hybridization allowed finding results that exceeded the unaltered SPEA II in terms of solutions qualities and computational time. For example, for an agricultural plot of 400 m$^2$ of surface, the RF-SPEA II hybridized algorithm gave better constraint rates and was 5.82 times faster than the unaltered SPEA II.
  Keywords: Precise Agriculture; Wireless Sensor Network; Node Deployment; Fitness approximation; Random Forest; Strength Pareto Evolutionary Algorithm II.
  
  
• A Novel Reformed Normalizer Free Network with U-Net Architecture for Semantic Segmentation  
  by Sai Prabanjan Kumar Kalvapalli, C. Mala, V. Punitha 
  Abstract: Recently developed semantic segmentation network architectures include BatchNorm layer and skip connections. They are outperforming with latest training techniques, but the BatchNorm has implicit limitations such as gradients calculation and memory overhead. Hence this paper proposes a novel architecture named as NF-Unet, that combines the simple, flexible and general framework of NF-Nets and the unique architecture of encoder decoder format of U-Net network that can train with huge batch sizes. The backbone of the contracting path consists of NF-net UNet for encoding the image, for identifying the objects in the image. The proposed architecture achieved 87.37 and 70.12 mean Intersection over Union (mIoU) on train and test dataset and outperforms the other approaches in the literature in terms of number of parameters.
  Keywords: BatchNorm; Nf-Nets; U-Net; mean Intersection over Union.
  
  
• An Optimized Darknet Traffic Detection System using Modified Locally Connected CNN - BiLSTM Network  
  by Abdullah Abdul Sattar Shaikh, M.S. Bhargavi, Pavan Kumar C 
  Abstract: The contents of the darkweb have always been a major breach of security and privacy. Due to its anonymous nature, detection of traffic from Darknet becomes difficult. A robust classifier system that accurately predicts and classifies such traffic is a necessity. This research work aims to study the effects of the convolutional-long-short-term memory (CNN-LSTM) system of classification of Darknet through various deep layer modifications on the Nadam optimiser. Experimentations were carried out on different combinations of locally-connected CNNs (LcCNN) and bi-directional LSTM (BiLSTM) to improve accuracy. Data was subjected to various levels of synthetic minority oversampling techniques (SMOTE) to reduce overfitting, data imbalance and achieve better generalisation. A custom decaying call-back function implemented, cut down the learning rate by half and tended to improve accuracy. Results obtained outperformed the base CNN-LSTM system for traffic categorisation with an improved accuracy of 92.57% from 89% using the custom LcCNN-BiLSTM architecture.
  Keywords: Darknet; deep learning; convolutional neural network; CNN; bi-directional long short term memory; BiLSTM.
  DOI: 10.1504/IJAHUC.2022.10051751
   
  
• A Trusted and Adaptive Security Mechanism for Wearable E-Healthcare Systems  
  by Geetanjali Rathee, Hemraj Saini, Shishir K. Shandilya, S. Rajasoundaran 
  Abstract: The wearable e-healthcare systems are a critical IoT mission having wearable sensors, wireless devices and intelligent monitoring of surroundings. The ultimate goal of e-healthcare systems is to identify or diagnose the patients by recognising their various features that are correlated among each other. The involvement of several malicious objects may try to hide the actual recognition of wearable objects for benefiting their own purposes. Though various researchers have proposed various security and efficient schemes, however, it may lead to several computations, management overhead. The aim of this paper is to propose a trusted and efficient e-healthcare communication mechanism while recognising the exact identification of wearable objects. In addition, the proposed mechanism is associated with blockchain mechanism to ensure the transparency and security inside the network while sharing the information. The proposed mechanism is further validated over several security threats against number of security parameters.
  Keywords: wearable devices; AHP; security mechanism; analysis process; secure e-healthcare systems.
  DOI: 10.1504/IJAHUC.2023.10052372
   
  
• Ubiquitous monitoring of liver transplantation patients  
  by Javier Navarro-Alaman, Raquel Lacuesta, Jose M. Jimenez, Jaime Lloret Mauri, Iván García-Magariño, Trinidad Serrano 
  Abstract: Currently, liver transplantation is the most effective treatment available for patients with end-stage liver disease. Patients, after being transplanted, require immunosuppressive treatment that must be monitored. mHealth systems reduce costs and increase the effectiveness of monitoring. Wireless body sensor networks are used to connect personal monitoring devices in the health environment. In this work, we present a system with a specific software application to monitor liver transplant patients remotely through the data gathered from a body sensor network. The main objective of the application is to carry out the out-of-hospital follow-up of patients who are receiving postoperative treatment. The application also provides a forum, frequently asked questions, and direct communication with health specialist personnel. We have observed that the degree of activity and the emotions of the patients are related to the information provided by the collected parameters through the devices of the body sensor network.
  Keywords: mHealth; app; wearable devices; monitoring; liver; transplantation.
  DOI: 10.1504/IJAHUC.2023.10052490
   
  
• Research on the Matching of Environmental Emergency Prediction and Emergency Rescue Resources Based on Deep Learning  
  by Xifei Huang, Xiaowu Huang 
  Abstract: Most of the current environmental safety emergency predictions rely on experienced experts or staff, and are highly subjective. Therefore, this paper proposes a deep learning-based regional risk assessment method. Based on domestic and foreign research results, this paper adopts comparative analysis, neural network, storage theory in operations research and multi-objective programming as research methods, and establishes a research model for regional hazard prediction and emergency rescue resource matching based on deep learning. By comparing the advantages and disadvantages of several methods, this paper studies the matching of regional hazard control and emergency rescue resources. The results show that after using the research model in this paper, the overall research efficiency is increased by 20%, and compared with the previous research model, the overall efficiency is higher and has certain practical value.
  Keywords: regional risk estimation; neural network method; storage theory; multi-objective programming method; emergency rescue resource matching.
  DOI: 10.1504/IJAHUC.2022.10052528
   
  
• A hybrid approach for feature selection using SFS with Extra-Tree and Classification using Adaboost with Extra-Tree  
  by Ankit Kharwar, Devendra Thakor 
  Abstract: Cyberattack is a new trend in data security. Intrusion detection systems gather different information from PCs and networks to recognize security risks and evaluate an attacks information. The discovery rate is low despite an enormously large amount of data. The problem can be overcome by feature selection. In this research study, the proposed contains a hybrid model for intrusion detection. This research shows hybrid model involves three sections: preprocessing, feature selection, and classification. We combined sequential forward search (SFS) & an Extra-Tree algorithm for feature selection. For classification, we combined Adaboost & Extra-Tree algorithm. The proposed model was implemented on various datasets like KDD99, NSL-KDD, UNSW-NB15, CICIDS2017, and CICIDS2018 datasets. The proposed model evaluated parameters are false alarm rate, detection rate, and accuracy. The comparative result study displays that the proposed model defeats the existing algorithm.
  Keywords: Intrusion Detection; Anomaly Detection; Machine Learning; Ensemble methods; Extra-Tree; Feature Selection; Sequential Forward Search(SFS); Boosting Algorithm; Adaboost Algorithm; Network Security.
  
  
• A hybrid approach for feature selection using SFFS and SBFS with Extra-Tree and Classification using XGBoost  
  by Ankit Kharwar, Devendra Thakor 
  Abstract: Network data security is a global issue for governments, businesses, and individuals. The frequency of attacks is rapidly growing, and attackers techniques are evolving. Many network security technologies utilize many techniques. An Intrusion Detection System (IDS) is a robust network security system that detects illegal and irregular network activity. This paper analyses feature selection methods and present an ensemble method to increase detection performance to address this issue. In the proposed model, we incorporate Sequential Forward Floating Selection (SFFS) with Extra-Tree and Sequential Backward Floating Selection (SBFS) with the Extra-Tree feature selection model by lowering the feature and XGBoost for higher classification accuracy. The proposed model achieves 98.68%, 98.94%, 95.25%, 99.91%, and 99.00% accuracy on the KDD99, NSL-KDD, UNSW-NB15, CICIDS2017, and CICIDS2018 datasets. The comparative result analysis of proposed models outperforms other existing models in KDD99, NSL-KDD, and UNSW-NB15 datasets in terms of accuracy, detection rate, and false alarm rate.
  Keywords: Intrusion Detection; Anomaly Detection; Machine Learning; Ensemble methods; Extra-Tree; Feature Selection; Sequential Forward Floating Search(SFFS); Sequential Backward Floating Search(SBFS); Boosting Algorithm; XGBoost; Network Security.
  
  
• Hop-based Void Avoidance Routing Protocol for Underwater Acoustic Sensor Networks  
  by Pradeep Nazareth, B.R. Chandavarkar 
  Abstract: More than 70% of the earth's surface is covered by water. There is a need to explore the underwater in various applications like disaster detection, environmental monitoring, resource detection, surveillance applications, etc. Underwater Acoustic Sensor Networks (UASNs) are the prominent technology used in exploring underwater. Despite many applications of UASNs, it faces several challenges, such as low bandwidth, energy constraint on networks, high bit error rate, and increased routing complexity due to dynamic network topology and void node results in increased complexity. The void node poses a major challenge in the routing of UASNs. A void node not being handled properly leads to a lower Packet Delivery Ratio (PDR), higher end-to-end delay, and lower throughput. This paper proposes a Hop-based Void Avoidance Routing (HVAR) protocol, which is a sender-based, void-avoidance routing protocol. HVAR efficiently distributes void node information in the networks and avoids data transmission to such nodes in the network. Further, HVAR selects the next hop based on the neighboring nodes' hop count and depth information. HVAR is implemented using UnetStack, and its performance is compared with the state-of-the-art Interference-aware routing (Intar) in terms of an average hop count to reach the sink, latency, end-to-end delay, PDR, energy consumption, and throughput.
  Keywords: Underwater routing; Void node; Depth-based routing; UnetStack.
  
  
• Wireless Communications with Hybrid Solar and RF Energy Harvesting  
  by RAED ALHAMAD 
  Abstract: Energy harvesting consists to use different source of powers such as radio frequency (RF) signals, the sun and the wind. The harvested energy can be used to recharge the battery of the source used for wireless communications. In this paper, we derive the throughput of wireless communications when the source harvests energy using a solar panel as well as RF signals. We compute the performance when the source uses hybrid energy harvesting using solar energy and RF signals. We derive the signal to noise ratio (SNR) and signal to interference plus noise ratio (SINR) statistics to deduce the packet error probability (PEP) and the throughput. Harvesting duration is optimised to maximise the throughput. We show that the harvested power from RF signals is proportional to the squared absolute value of the channel coefficient. The harvested power from the sun is proportional to the radiation intensity
  Keywords: RF energy harvesting; solar energy; wireless communications; Rayleigh channels.
  DOI: 10.1504/IJAHUC.2022.10052806
   
  
• A Bigraphical Approach to Model and Verify Ontology Alignment  
  by Manel KOLLI 
  Abstract: Dealing with diverse ontologies by means of semantic alignment stills always an attractive research axe. This allows performing the semantic interoperability among ontologies. A semantic network of ontologies is made of a set of different ontologies related by semantic alignments. Indeed, the design and the realisation of alignment-based ontological network systems are very challenging and delicate tasks. In this paper, a new approach is proposed, based on bigraphic reactive systems and their sorting logic, to provide a formal modelling of ontological network systems architecture and their behaviours. Another contribution of this paper consists of providing a new way for the ontology networking verification using the computation tree logic, or CTL for short, model checking for expressing the incoherencies of mappings in order to minimise the amount of errors and make the mappings of concepts more pertinent while ensuring the consistency of the ontology networking system. The obtained results show a good performance of the networking system after detecting and repairing incoherencies of mappings. The comparison of these results demonstrates that the proposed approach is useful, and the quality of mappings results is improved significantly in most cases.
  Keywords: ontology networking; ontology alignment; ontology matching; mappings; bigraphs.
  DOI: 10.1504/IJAHUC.2022.10052920
   
  
• Efficient Area and Throughput Implementations of Lightweight Simeck Cipher for Resource-constrained Applications  
  by Kaluri Praveen Raja, Pulkit Singh, Zeesha Mishra, Bibhudendra Acharya 
  Abstract: Each secure device is provided with an exclusive identifier and the ability to individually communicate with other devices over the network. Simeck is one of those ciphers that offer great security features while contributing a decent lightweight performance. In this paper, several efficient hardware architectures of Simeck cipher such as round-based, inner-round pipeline and mixed pipeline designs are proposed. Among these architectures, round-based architecture provides a better throughput to area trade-off and pipelining architecture gives high throughput for high-speed resource-constrained applications. All three architectures are evaluated and compared on the basis of throughput, area, and power consumption on different FPGA platforms. The proposed Simeck256 round-based design is 10 times more efficient than LEA cipher implementation, in terms of efficiency and throughput is almost 12 times higher than HIGHT cipher implementation. An approximately 200% improvement in throughput is archived as compared to XTEA cipher implementation.
  Keywords: Simeck; cipher; lightweight cryptography; pipelining; round based; FPGA.
  
  
• DATA SECURITY ENHANCEMENT IN INTERNET OF THINGS USING OPTIMIZED HASHING ALGORITHM  
  by Arun Kumar Udayakumar, Premkumar R, Sivakumar S. A, Maruthi Shankar B, Mahendran G 
  Abstract: The internet of things (IoT) has advanced quickly, providing customers with significant convenience in a variety of areas, including smart homes, smart transportation, and more. It might potentially pose security issues too. Significant security difficulties for the communications between such devices are brought on by the development of smart devices in IoT networks. As the IoT ecosystems develop, blockchain will become a platform for their security. Blockchain is a decentralised, distributed technology that may be able to address the IoT network security issues. Blockchain can address IoT restrictions on privacy and data protection. IoT is not a good fit for blockchain because of its high computing complexity, limited scalability, significant bandwidth overhead, and latency. This study develops an effective blockchain paradigm to address IoT requirements. Initially, the dataset is collected from the IoT sensors and pre-processed using the normalisation method. The pre-processed data is validated using smart contracts and stored in the blockchain network. Proof of work (PoW) consensus protocol is employed for the validation of the blocks. We propose an optimal key search fuzzy hashing algorithm (OKSFHA) for enhancing the security of the data. To optimise the security enhancement Spider monkey optimisation (SMO) is employed. The proposed algorithm is compared with traditional algorithms to prove the efficiency of the suggested system.
  Keywords: internet of things; IoT; blockchain; smart contracts; proof of work; PoW; optimal key search fuzzy hashing algorithm; OKSFHA; spider monkey optimisation; SMO.
  DOI: 10.1504/IJAHUC.2023.10053339
   
  
• Transcend: An Ownership Based Resource Allocation Strategy for Service Function Chaining in NFV Empowered 6G Network Using Latency and User Cost-awareness  
  by Mahfuzulhoq Chowdhury 
  Abstract: By providing software-based network function services, network function virtualisation (NFV) has gained a lot of popularity due to its flexible deployment and lower operational/maintenance costs. To realise better results from the NFV, the service function chaining (SFC) requires suitable order-based virtual network functions (VNFs) execution on the virtual machines. The SFC provisioning literary works suffer from higher latency as they rely on non-dedicated resources rather than both dedicated and non-dedicated resources. An effective resource allocation approach for multiple SFC provisioning by considering associated delays, payment, deadlines, time-sensitive, non-sensitive requests, SFC sorting order were out of their investigations. To tackle these issues, this paper yields ownership, latency, and cost-based resource allocation approach for SFC provisioning for NFV-assisted networks by taking different requests, service requirements, and resources, into account. The results validate that the proposed approach achieves up to 54% SFC delay and 47% energy cost gain than the traditional approaches.
  Keywords: resource allocation; network-function virtualisation networks; NFV; service function chaining; SFC; SFC delay; profit; energy cost; ownership; throughput.
  DOI: 10.1504/IJAHUC.2023.10053812
   
  
• Analysis of Sponsoring and Caching Data: the Case of Competing ISPs in Information-centric Networks  
  by Khadija TOUYA, Hamid Garmani, Mohamed BASLAM, Rachid El Ayachi, Mostafa Jourhmane 
  Abstract: In recent years, the majority of mobile data users choose to subscribe to social networks, as content providers, to view a large number of contents. This viewing is done through an accessing request transmitted by the user. As the number of users is becoming very huge, this demand tends towards an explosion. This pushes the infrastructure of the internet to its limits. To fix this problem, the ICN intervenes to guarantee the availability of the wanted contents. In this work, we are interested in analysing the competition between internet service providers using game theory. These providers compete towards sponsoring and caching contents. This competitive situation is modelled as a non-cooperative game taking into account several parameters. We prove the existence and the uniqueness of the Nash equilibrium. We use the best response algorithm to achieve the equilibrium points. Finally, the numerical results validate the model.
  Keywords: internet services provider; ISP; content provider; game theory; caching; sponsoring; ICN; quality of service; price of anarchy; Nash equilibrium.
  DOI: 10.1504/IJAHUC.2023.10054346
   
  
• Messed up(): A Key Generator based image cryptosystem  
  by Durgabati Podder, Keya Chowdhury, Subhrajyoti Deb, Nirmalya Kar 
  Abstract: With exponential growth in digital image communication, a cryptosystem with high confusion and diffusion is essential to ensure privacy and security throughout network transmission. A new chaotic-based image encryption scheme is introduced in this paper using a unique block scrambling function named Messed up() and Diffie-Hellman Key Generator. The proposed approach achieves double confusion by scrambling and circular shift operation, and the diffusion process is carried out with the help of the Henon map. Based on the theory of the DiffieHellman Key Exchange algorithm, the secret key has been produced to apply the initial parameters in both the Henon map and circular shift operation. These adaptive techniques make the cryptosystem more challenging to penetrate. Simulation results and cryptographic attack analyses show that the proposed cryptosystem has high-security performance and low computing overhead, making it suitable for real-time multimedia applications.
  Keywords: Henon map; Security; Image encryption; Diffie-Hellman; Chaos; confusion; diffusion; NPCR; UACI.
  DOI: 10.1504/IJAHUC.2023.10054456
   
  
• A Comparative Analysis of Elliptic Curve Based Cryptographic Techniques for Internet of Things  
  by Dilip Kumar, Manoj Kumar 
  Abstract: The internet of things (IoT) technology has changed the modern digital world. Devices connected to the IoT have sensors embedded within them. Data sharing among IoT devices needs some security protocol to maintain the privacy and confidentiality of data. Traditional public-key cryptographic techniques have been used to achieve data security while transmitting data. The application of traditional public-key cryptographic techniques is not feasible in an IoT environment. Therefore, there is a requirement for lightweight cryptographic approaches which produce a feasible solution. Elliptic curve-based cryptographic techniques are used to provide privacy and authenticity of data. The lightweight properties of elliptic curve cryptography (ECC) reduce the communicational and computational complexities of resource-constrained IoT devices. This paper presents an analytical approach for discussing various elliptic curve-based cryptographic techniques. Analysis of cryptographic techniques has been done by selecting different parameters. The results show the feasibility of cryptographic algorithms in the IoT environment.
  Keywords: internet of things; IoT; cryptographic techniques; ElGamal cryptosystem; elliptic curve cryptography; Paillier cryptosystem; complexity.
  DOI: 10.1504/IJAHUC.2023.10054813