{"title":"Adaptive grouped balanced binary tree based multi user secure data transmission on cloud","authors":"P. Pavithra, B. Hariharan","doi":"10.1007/s41870-024-02165-6","DOIUrl":"https://doi.org/10.1007/s41870-024-02165-6","url":null,"abstract":"<p>Secure multi-keyword search for outsourced cloud data has gained popularity, especially for scenarios involving multiple data owners. This work proposes a method for secure multi-keyword searches across encrypted cloud data from various owners, utilizing an administrator or trustworthy third party for key management. The approach employs the TF-IDF model and Vector Space Model (VSM) to generate index and query vectors, and uses an advanced Attribute-Based Encryption (ABE) algorithm for data privacy. The Improved Dingo Optimization Algorithm (IDOA) optimally selects the key value. Encrypted emails are sent to a cloud server, and a Grouped Balanced Binary (GBB) tree structure is used for index construction. The Greedy Depth-First Search (GDFS) method efficiently searches the index, grouping relevant documents to exclude unnecessary ones. Performance is evaluated based on memory usage, execution time, encryption and decryption times, and search times, implemented in Java and tested on a cloud simulator.</p>","PeriodicalId":14138,"journal":{"name":"International Journal of Information Technology","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"RAMD and transient analysis of a juice clarification unit in sugar plants","authors":"Kanak Saini, Monika Saini, Ashish Kumar, Dinesh Kumar Saini","doi":"10.1007/s41870-024-02147-8","DOIUrl":"https://doi.org/10.1007/s41870-024-02147-8","url":null,"abstract":"<p>The main objective of present work is to analyse the reliability measures of a juice clarification unit in sugar plants under the concepts of various redundancy polices. The juice clarification unit (JCU) is a complex system having eight subsystems configured according to various redundancies internally. It is assumed that all the associated random variables follow exponential distribution. The Markov birth–death process and basic reliability arguments are used to derive Reliability, Availability, Maintainability, and Dependability (RAMD) measures as well as Runge–Kutta forth order is used to derive transient solution. The numerical results for reliability, availability, maintainability, Mean Time Between Failure (MTBF), Mean Time to Repair (MTTR), and dependability are derived to identify the most sensitive component. The system attains transient availability 0.995881 at 5-time units. To highlight the importance of the study numerical results of transient availability are derived by making 10% and 50% variation in failure and repair rates. The derived numerical results of the proposed model draw significant insights that can be directly used in the design and maintenance process of juice clarification unit. It will improve the plant efficiency. It will give designers a solid plan to use resources intelligently and make strategies that make juice clarification unit live to work better.</p>","PeriodicalId":14138,"journal":{"name":"International Journal of Information Technology","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohammad Ubaidullah Bokhari, Abeer Masroor, Basil Hanafi
{"title":"Securing data transmission channels between smart devices and the cloud using homomorphic encryption for blood pressure monitoring sensors","authors":"Mohammad Ubaidullah Bokhari, Abeer Masroor, Basil Hanafi","doi":"10.1007/s41870-024-02195-0","DOIUrl":"https://doi.org/10.1007/s41870-024-02195-0","url":null,"abstract":"<p>Ensuring the secure transmission of data between smart devices and the cloud is paramount in the context of Blood Pressure Monitoring Sensors. In the realm of “Securing Data Transmission Channel between Smart Devices and Cloud using Homomorphic Encryption for Blood Pressure” “Monitoring sensors play a crucial role in various applications.” The incorporation of homomorphic encryption is considered essential to guarantee the privacy and security of health data. In smart cities, where mobile healthcare networks play a vital role, concerns arise over the transmission of sensitive health information to untrusted cloud servers. Our focus lies in the development of a specialized architecture explicitly designed for the unique requirements of Blood Pressure Monitoring Sensors. Within this paper, a concise yet comprehensive framework, for mobile healthcare networks is outlined, emphasizing three secure medical calculations encompassing tasks such as computing average heart rate detecting long QT syndrome, and performing Chi-square tests are integral aspects of healthcare. Through this methodology, a distinctive and innovative solution is provided, tailored specifically to the challenges of securing data transmission channels for Blood Pressure Monitoring Sensors.</p>","PeriodicalId":14138,"journal":{"name":"International Journal of Information Technology","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Design of ultra-wideband Sziklai pair based LNAs for wireless communication applications","authors":"Syed Shamroz Arshad, Geetika Srivastava, SachchidaNand Shukla","doi":"10.1007/s41870-024-02188-z","DOIUrl":"https://doi.org/10.1007/s41870-024-02188-z","url":null,"abstract":"<p>Noise figure (NF) and linearity at higher frequencies are challenging tasks in Low Noise Amplifiers (LNAs) design. The existing LNAs impose limits on these parameters resulting in enhanced NF. In this paper, two ultra-wide band (UWB) small signal Sziklai pair based LNAs are proposed with improved linearity and minimum NF for high frequency wireless communication. Theses LNAs use NMOS Sziklai and PMOS Sziklai pairs as amplifying components with bandwidth boosting arrangement in common source mode. The simulation results indicate that NMOS LNA exhibits bandwidth of 580.554 GHz with noise figure of 1.66 dB at 63.09 GHz, whereas PMOS LNA shows bandwidth of 299.956 GHz, with noise figure of 11.71 dB at 283.09 GHz, at 180 nm CMOS technology. Furthermore, NMOS and PMOS LNAs show high linearity with input 1 dB compression point (P1dB) of 0.883 dBm and 0.822 dBm while input third order intercept point (IIP3) are 10.22 dBm and 6.72 dBm respectively. Compared to CMOS LNA, bulk CMOS LNA, GaAs pHEMT LNA, and SiGe BiCMOS LNA, the proposed LNAs significantly improve power gain, bandwidth, noise figure, linearity, and area. To further expand the bandwidth, three stage broadband distributed amplifiers (DAs) are also configured using the designed LNAs which measures the bandwidth of 0–7.5 GHz and 10,000–800,000 THz. The performance of these LNAs is verified through designing D-band microwave tuneable second order band reject filter (BRF) which exhibits ultra-wide band (UWB) of 110.362 GHz, notch depth of 10.3 GHz while consuming DC power of 68.32 pW at a supply voltage of ± 3 V.</p>","PeriodicalId":14138,"journal":{"name":"International Journal of Information Technology","volume":"74 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A hybrid framework for heterogeneous object detection amidst diverse and adverse weather conditions employing Enhanced-DARTS","authors":"Anuj Kumar, Sarita Gautam","doi":"10.1007/s41870-024-02164-7","DOIUrl":"https://doi.org/10.1007/s41870-024-02164-7","url":null,"abstract":"<p>Autonomous vehicles face significant challenges in accurately identifying vehicles, objects, and traffic signals under adverse weather conditions and poor lighting. To address these issues, we introduce a novel detection system utilizing automatic white balance techniques, specifically the Adaptive Retinex algorithm, to restore visibility and enhance color. This system is integrated with a Faster R-CNN framework enhanced by non-maximum suppression to improve the accuracy of object detection. Employing a combination of three datasets—Dawn, MCWRD, and Indian Roads Dataset (IRD)—our method includes over 6000 augmented images representing diverse environmental conditions. We also implement an optimized version of Differentiable ARchiTecture Search (DARTS) to dynamically fine-tune the architectural parameters of our detection model. This approach has successfully achieved a detection accuracy of 97.43% with a minimal loss rate, demonstrating significant potential for enhancing navigation safety in autonomous vehicles across various challenging environments.</p>","PeriodicalId":14138,"journal":{"name":"International Journal of Information Technology","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Detecting the undetectable: GAN-based strategies for network intrusion detection","authors":"Ruchi Bhatt, Gaurav Indra","doi":"10.1007/s41870-024-02172-7","DOIUrl":"https://doi.org/10.1007/s41870-024-02172-7","url":null,"abstract":"<p>This study addresses the challenge of enhancing network security by proposing a novel intrusion detection system using Generative Adversarial Networks. Traditional intrusion detection system often fail to keep up with rapidly evolving cyber threats. Our approach integrates Generative Adversarial Networks to dynamically learn and adapt to both genuine and adversarial network traffic patterns. Using the KDD Cup 1999 dataset for validation, we design a sophisticated Generative Adversarial Network architecture with a generator and discriminator to improve the resilience of intrusion detection system. Our experimental results demonstrate the model’s effectiveness, evaluated through metrics such as F1 score, accuracy, precision, and recall. This research advances the state-of-the-art in cybersecurity by showcasing the potential of Generative Adversarial Networks to fortify intrusion detection system against evolving threats, underscoring the necessity for adaptive defense mechanisms in modern network security.</p>","PeriodicalId":14138,"journal":{"name":"International Journal of Information Technology","volume":"113 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142224070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Muthubalaji, Vijaykumar Kamble, Vaishali Kuralkar, Tushar Waghmare, T. Jayakumar
{"title":"An innovative muted ant colony optimization (MAPO) controlling for grid PV system","authors":"S. Muthubalaji, Vijaykumar Kamble, Vaishali Kuralkar, Tushar Waghmare, T. Jayakumar","doi":"10.1007/s41870-024-02178-1","DOIUrl":"https://doi.org/10.1007/s41870-024-02178-1","url":null,"abstract":"<p>Reducing the power quality problems and regulating the output DC voltage are considered as the essential problems need to be addressed for ensuring the increased performance of grid-PV systems. Different converter topologies and controlling strategies have been developed for this purpose in conventional works, but they are constrained by the major issues of increased computation complexity, high output error, harmonic distortions, and decreased voltage gain. Hence, this research work objects to develop a novel Mutated Ant Province Optimization (MAPO) algorithm incorporated with the modified SEPIC DC-DC converter techniques for solving the regulating the output voltage with reduced harmonics. In order to maximize the power output from the solar PV systems, the Perturb & Observe (P&O) Maximum Peak Point Tracking (MPPT) controlling technique is developed. Subsequently, the photovoltaic (PV) output voltage exhibits a stochastic behavior, necessitating effective regulation to enhance the output gain. The modified SEPIC DC-DC converter is employed for this specific objective, since it effectively adjusts the output voltage with minimized harmonics. However, the performance of the converter is solely dependent on the controller, as it generates controlling signals by optimally selecting parameters. Also, the switching components used in the converter circuit are operated based on the controlling signals. During simulations, Various measurements are used to validate and compare the effectiveness of the suggested converter and controlling mechanisms.</p>","PeriodicalId":14138,"journal":{"name":"International Journal of Information Technology","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Securing FANET using federated learning through homomorphic matrix factorization","authors":"Aiswaryya Banerjee, Ganesh Kumar Mahato, Swarnendu Kumar Chakraborty","doi":"10.1007/s41870-024-02197-y","DOIUrl":"https://doi.org/10.1007/s41870-024-02197-y","url":null,"abstract":"<p>As Flying Ad Hoc Networks (FANETs) continue to advance, ensuring robust security, privacy, and data reliability remains a significant challenge. This research presents a novel framework known as HE-FSMF-short for Homomorphic Encrypted Federated Secure Matrix Factorization-specifically designed to tackle these challenges. HE-FSMF integrates matrix factorization with federated learning and homomorphic encryption to enhance both security and efficiency in FANET environments. Matrix factorization, commonly used in recommendation systems, is adapted here to address the unique complexities of FANETs. By leveraging detailed feature extraction through the VGG-16 model, HE-FSMF ensures precise and secure data processing even in dynamic and high-mobility settings. The incorporation of homomorphic encryption protects data throughout cloud-based computations, maintaining privacy and integrity without compromising performance. Additionally, HE-FSMF features mechanisms to verify the accuracy and authenticity of results, which is crucial for establishing trust in distributed systems. This framework not only enhances learning efficiency and improves data transmission rates but also provides strong safeguards for sensitive information. HE-FSMF offers a robust solution for advancing FANET capabilities, making it a valuable tool for secure and efficient communication in the increasingly interconnected and rapidly evolving landscape of networked systems.</p>","PeriodicalId":14138,"journal":{"name":"International Journal of Information Technology","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142184687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Enhancing VANET communication using squid game optimization based energy aware clustering approach","authors":"R. Rajakumar, T. Suresh, K. Sekar","doi":"10.1007/s41870-024-02176-3","DOIUrl":"https://doi.org/10.1007/s41870-024-02176-3","url":null,"abstract":"<p>Vehicular Ad-Hoc Networks (VANETs) are studied wireless networks that enable communication among vehicles and roadside infrastructure. The role a vital play in improving on-road safety, efficacy, and convenience by enabling real-time data interchange for controlling traffic, infotainment services, and collision avoidance. Energy efficiency in VANETs is vital because of the restricted power resources of vehicles. Methods like clustering, vehicles are categorized into groups to decrease communication overhead, and meta-heuristic approaches that optimize network performance by intelligent problem-solving approaches are deployed to exploit energy efficiency while preserving network reliability and responsiveness. These methodologies contribute to the effective implementation of VANETs, ensuring sustainable and dependable communication in dynamic vehicular environments. In this study, a new Squid Game Optimization based Energy Aware Clustering Approach (SGO-EACA) technique for VANET is introduced. The goal of the SGO-EACA technique is to optimally choose the cluster heads (CHs) and produce clusters in the VANET in such a way as to realize energy efficiency. In the SGO-EACA technique, the concept of typical Korean sport is used where the attackers try to achieve their goal, but players try to eliminate each other. Moreover, the SGO-EACA approach derives a fitness function (FF) containing multiple metrics such as Residual Energy (RE), Trust Level, Degree Difference, Total Energy consumption, Distance to Base Station (DBS), and Mobility. The simulation values exposed that the SGO-EACA approach surpassed earlier state-of-the-art approaches with respect to various aspects.</p>","PeriodicalId":14138,"journal":{"name":"International Journal of Information Technology","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142265769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Unveiling social network clans: improving genealogical clan classification with SVM neural classifiers and enhanced kernels","authors":"S. N. Deepa, Karam Ratan Singh, Arun Joram","doi":"10.1007/s41870-024-02183-4","DOIUrl":"https://doi.org/10.1007/s41870-024-02183-4","url":null,"abstract":"<p>In this study, we developed a variant of the support vector machine (SVM) neural classifier and utilized it to categorize clans in a genealogical dataset. For each of the five kernels, all four variants, twin SVM (TSVM), proximal SVM (PSVM), twin proximal SVM (TPSVM), and multi-class SVM (MCSVM) classifier are simulated and tested. The analysis of variance - radial basis function (ANOVA RBF) kernel outperformed all other SVM variants, in terms of classification accuracy with the lowest error value. Additionally, it is found that for the considered dataset, TPSVM neural classifier with ANOVA RBF Kernel generated 98.91% classification accuracy, and the TPSVM classifier has achieved the minimized mean square error (MSE) value of 0.00015. The Twin Proximal SVM classifier has produced enhanced classification accuracy with better precision and F1-score in comparison to all other developed and simulated SVM classifier models.</p>","PeriodicalId":14138,"journal":{"name":"International Journal of Information Technology","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142184739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}