V K Pachghare

Scopus Publications

Intelligent Audit Log Query Chatbot for Database Forensics Using LLM
Anushree Krishna Suryavanshi, Vinod Pachghare
Lecture Notes in Networks and Systems, 2026
Explainability-Driven Trust Enhancement in Medical AI for Radiological and Neurophysiological Prognostics with SimulationBased Validation
Khushbu Trivedi, Rupali Chopade, V.K. Pachghare
2026 International Conference on Emerging Technologies and Future Innovations Etfi 2026, 2026
A MAGIQ-TOPSIS-Fuzzy-Logic Based Cloud Service Providers Ranking Model for Federated Cloud Computing Environment
V. SARAF, R. ADHAO, V. PACHGHARE
Advances in Electrical and Computer Engineering, 2026
In the era of multi-cloud environments, the challenge for end users or organizations is to select the most appropriate cloud service provider (CSP) due to the complexity and variability of service-level offerings by various CSPs. In this paper, we propose a MAGIQ-TOPSIS-Fuzzy-logic based Cloud Service Provider Ranking (MTF-CSPR) model, which provides a more robust and intelligent decision-making system in CSP selection. The proposed model addresses both qualitative and quantitative evaluation criteria by capturing and processing the inherent vagueness of linguistic assessments through fuzzy logic. MAGIQ is employed to derive optimal weights for evaluation criteria that reflect their relative importance towards the alternatives. TOPSIS is applied to rank CSPs where the ideal and anti-ideal solutions are derived, and then based on CSP's proximity to the ideal solution, the ranks are derived. The proposed model ensures accuracy, scalability, and context-awareness for the CSP ranking by integrating subjective expert opinions with objective performance metrics. Experimental evaluation demonstrates that the proposed MTF-CSPR model provides more consistent and accurate rankings compared to conventional standalone approaches, as well as the other ranking models under consideration, providing better decision-support for enterprises to adopt the hybrid or multi-cloud strategies.
Cross-Fruit Disease Image Generation using CycleGAN: From Pomegranate to Apple
Amey S Khurdekar, Charulata J Patil, Vinod K Pachghare
2026 International Conference on Emerging Smart Computing and Informatics Esci 2026, 2026
SUSPICIOUS TRANSACTION IDENTIFICATION AND RECOVERY IN CASSANDRA DATABASE
Rupali Chopade, Vinod Pachghare, Damini Sheth, Nikhil Dhavase, Yogita Sinkar
Asean Engineering Journal, 2025
Forensic analysis of databases is a challenging and important research field in digital forensics. Most of the applications use databases to store the data. Cassandra is a NoSQL database that offers data replication for high availability, fault-tolerance and ensures no single point of failure. Given its growing popularity, financial institutions have begun to consider Cassandra as a potentially useful database for their organization. Considering the abundant amount of fraud and its implications that can occur at financial institutions, it is needed to ensure that no suspicious transaction on the Cassandra database goes unnoticed by the organization. In addition, being able to recover lost data due to malicious activities is equally necessary. This article presents a tool which helps in identifying suspicious transactions in a financial institution and an option to recover that data.
User Preference Based Cumulative Trust (UPBCT) Computation Model
Vinod Saraf, Vinod Pachghare
2025 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation Iatmsi 2025, 2025
Cloud Computing is the biggest buzz word in the Computer and Information Technology industries. Almost every IT organization has adopted cloud computing technologies. There are multiple Cloud Service Providers (CSP) in the market like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), IBM Cloud (Kyndryl) and many more. Every CSP provides various cloud services to Cloud Users (CU). It is a big challenge today for cloud users to decide on which CSP will be suitable for their requirements. Trust values for cloud services helps cloud users to choose the most suitable cloud service and CSP. Trust computation has several methodologies like reputation based, SLA verification based, self-assessment based, policy based, societal trust based, and evidence based. Among all these methodologies, evidence-based trust computation is considered as the effective and most trustworthy as it computes the trust values based on QoS attributes of the cloud services. We have studied many of evidence-based models proposed by various researchers. Among many we found that the approach of weightage-based normalization of QoS attribute values is more effective and accurate while calculating the trust values. Also, we found that these models are missing on what user is expecting with respect to values of QoS attributes. Accordingly, in this paper we have proposed a User Preference Based Cumulative Trust (UPBCT) computation model which is evidence-based, follows weightage-based normalization of QoS attribute values approach, and takes in account the user preferred values for QoS attributes. The results support the efficiency of the proposed model compared to other models, helps cloud users to choose better cloud service as per their requirements and helps CSP with the desired value for QoS attributes so that they can enhance their cloud services to meet those desired values of QoS attributes and increase the trust values of their cloud services.
User Preference Based Cumulative Trust (UPBCT) Computation Model
Vinod Saraf, Vinod Pachghare
2025 8th International Conference on Electronics Materials Engineering and Nano Technology Iementech 2025, 2025
Cloud Computing is the biggest buzz word in the Computer and Information Technology industries. Almost every IT organization has adopted cloud computing technologies. There are multiple Cloud Service Providers (CSP) in the market like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), IBM Cloud (Kyndryl) and many more. Every CSP provides various cloud services to Cloud Users (CU). It is a big challenge today for cloud users to decide on which CSP will be suitable for their requirements. Trust values for cloud services helps cloud users to choose the most suitable cloud service and CSP. Trust computation has several methodologies like reputation based, SLA verification based, selfassessment based, policy based, societal trust based, and evidence based. Among all these methodologies, evidence-based trust computation is considered as the effective and most trustworthy as it computes the trust values based on QoS attributes of the cloud services. We have studied many of evidence-based models proposed by various researchers. Among many we found that the approach of weightage-based normalization of QoS attribute values is more effective and accurate while calculating the trust values. Also, we found that these models are missing on what user is expecting with respect to values of QoS attributes. Accordingly, in this paper we have proposed a UPBCT computation model which is evidence-based, follows weightage-based normalization of QoS attribute values approach, and takes in account the user preferred values for QoS attributes. The results support the efficiency of the proposed model compared to other models, helps cloud users to choose better cloud service as per their requirements and helps CSP with the desired value for QoS attributes so that they can enhance their cloud services to meet those desired values of QoS attributes and increase the trust values of their cloud services.
A Digital Twin and User-Preference Based Trust Computation (DTUPTC) Model for Federated Cloud Computing Environment
V. SARAF, V. PACHGHARE
Advances in Electrical and Computer Engineering, 2025
Cloud computing has become an integral part for many organizations as well as cloud users. There are several cloud service providers hosting numerous cloud services. The challenge for the cloud users is to find the suitable cloud service among all cloud service providers which is most trusted and meets user expectations. The authentic and accurate trust values for such cloud services can help organizations and cloud users to choose appropriate cloud services. In this paper, we propose a Digital Twin and User-Preference Based Trust Computing (DTUPTC) model which is based on evidence-based strategy of trust computation. The novelty of our DTUPTC model is that we get the user inputs on their preferred quality of service (QoS) attributes which will be used for trust score computation and also provide their desired values for those QoS attributes. The weights assigned to each QoS attributes while computing trust score are calculated and assigned automatically without any manual intervention. The comparison results of our DTUPTC model with other models proves that the trust scores computed by DTUPTC model are more accurate than the other models.
YOLO-Based Automatic Detection and Binary Grading of Lumbar Spinal Canal Stenosis from Sagittal T2/STIR MRI
Rohit Chaudhari, Vinod Pachghare
2025 Global Conference in Emerging Technology Ginotech 2025, 2025
A Trust Computation Model for Collaborative Cloud Environment
Nikhil Kamble, Vinod Saraf, Vinod Pachghare, Rahul Adhao
Procedia Computer Science, 2025
Cloud computing has revolutionized the IT industry, with businesses of all sizes, from major corporations to local pizza shops and retail stores, increasingly relying on cloud services. This technology provides on-demand access to various computing resources over the Internet, including databases, development tools, applications, and physical and virtual servers. However, ensuring service uptime and accurately predicting application performance on cloud infrastructure remain significant challenges. Securing applications and data on the cloud while maintaining user privacy adds to these concerns. From the perspective of cloud consumers, issues such as service unavailability when needed, slower-than-expected response times, and the inherent security and privacy risks associated with cloud services can lead to a lack of trust in cloud providers. This research project addresses these concerns by proposing various methods for computing trust in cloud service providers. The trustworthiness evaluation will consider multiple factors, including reputation, service level agreements (SLAs), self-assessments, and cloud audits. Agents responsible for monitoring trust will observe and collect data on the different services offered by cloud providers. This data will be analyzed, and a trust computation engine will assess the provider’s trustworthiness. Key quality of service (QoS) features such as availability, dependability, data integrity, and reliability are crucial for users, as they play a significant role in determining the trustworthiness of a cloud service. The research mainly focuses on calculating trust as a numerical value by considering availability, response time, throughput, and Reliability. Trust will be the percentage value for the cloud. The authors have taken only the above four factors for better trust value.
Next-Generation Predictive Maintenance: Transforming Oil & Gas with Iot-Driven Deep Learning and Industry 5.0 Innovations
Rajesh Sivaraman Iyer, Sanjaykumar L. Patil, Uttam M. Chaskar, Vinod K. Pachghare
2025 International Conference on Computational Intelligence and Knowledge Economy Iccike 2025, 2025
Maintenance 5.0: IoT-Enabled Smart Maintenance Systems in Oil & Gas
Rajesh Sivaraman Iyer, Sanjaykumar L. Patil, Uttam M. Chaskar, Vinod K. Pachghare
Proceedings of IEEE International Conference on Modelling Simulation and Intelligent Computing Mosicom 2025, 2025
Security threats and mitigation techniques affecting trust computation in cloud computing
Vinod Saraf, Vinod Pachghare
Journal of Discrete Mathematical Sciences and Cryptography, 2024
Enhancing missing facts inference in knowledge graph using triplet subgraph attention embeddings
Anish Khobragade, Shashikant Ghumbre, Vinod Pachghare
Applied Intelligence, 2024
Infer the missing facts of D3FEND using knowledge graph representation learning
Anish Khobragade, Shashikant Ghumbre, Vinod Pachghare
International Journal of Web Information Systems, 2023
Statistical feature selection based intrusion detection system for internet of things environment
Rahul B. Adhao, Mayur Tayde, Vinod Pachghare
Aip Conference Proceedings, 2023
A Review on Trust-Based Resource Allocation in Cloud Environment: Issues Toward Collaborative Cloud
Pooja Shashank Pol, Vinod K. Pachghare
International Journal of Semantic Computing, 2023
Feature Engineering for Flow-Based IDS
Rahul B. Adhao, Vinod K. Pachghare
Wireless Communication Security, 2023
Survey on Data Privacy Preserving Techniques in Blockchain Applications
Akash Sakhare, Avinash Kshirsagar, Vinod Pachghare
9th International Conference on Smart Computing and Communications Intelligent Technologies and Applications Icscc 2023, 2023
Balance Relation-Aware Attention Embedding Model for Knowledge Graph Completion
Anish Khobragade, Shashikant Ghumbre, Vinod Pachghare
2023 IEEE Pune Section International Conference Punecon 2023, 2023
Sharding-Based Scalability Enhancement of Blockchain-Based Health Application
Adarsh Vernekar, Avinash Kshirsagar, V.K. Pachghare
Proceedings of the International Conference on Circuit Power and Computing Technologies Iccpct 2023, 2023
Quality of Service Estimation Enabled With Trust-Based Resource Allocation in Collaborative Cloud Using Improved Grey Wolf Optimization
Pooja Shashank Pol, Vinod K Pachghare
Computer Journal, 2022
CaneSat dataset to leverage convolutional neural networks for sugarcane classification from Sentinel-2
Shyamal S. Virnodkar, Vinod K. Pachghare, V.C. Patil, Sunil Kumar Jha
Journal of King Saud University Computer and Information Sciences, 2022
Performance Evaluation of Proof of Scope Consensus Mechanisms on Hyperledger
Avinash Kshirsagar, Vinod Pachghare
2022 IEEE International Conference on Blockchain and Distributed Systems Security Icbds 2022, 2022
NER in Hindi Language Using Transformer Model:XLM-Roberta
Aditya A Choure, Rahul B Adhao, Vinod K Pachghare
2022 IEEE International Conference on Blockchain and Distributed Systems Security Icbds 2022, 2022
Ensemble Based Feature Selection Technique For Flow Based Intrusion Detection System
Mayur V Tayde, Rahul B Adhao, Vinod Pachghare
2022 IEEE 7th International Conference for Convergence in Technology I2ct 2022, 2022
An Intrusion Detection System for Zero-Day Attacks to Reduce False Positive Rates
Priya Pitre, Arya Gandhi, Vaishnavi Konde, Rahul Adhao, Vinod Pachghare
2022 International Conference for Advancement in Technology Iconat 2022, 2022
Blockchain-based Crowdfunding for Cyber-Product Insurance
Srushti Nemade, Abhijit Kamble, Sharvil Sopal, Pragati Bhale, Vinod Pachghare
Proceedings 2022 2nd International Conference on Innovative Sustainable Computational Technologies Cisct 2022, 2022
An Efficient and Secure Consensus Mechanism for Peer-to-Peer Networks
Avinash Kshirsagar, Vinod Pachghare
ACM International Conference Proceeding Series, 2021
A data recovery technique for Redis using internal dictionary structure
Rupali Chopade, Vinod Pachghare
Forensic Science International Digital Investigation, 2021
DenseResUNet: An architecture to assess water-stressed sugarcane crops from sentinel-2 satellite imagery
Shyamal S. Virnodkar, Vinod K. Pachghare, Virupakshagouda C. Patil, Sunil Kumar Jha
Traitement Du Signal, 2021
Performance Analysis of Proposed Database Tamper Detection Technique for MongoDB
Rupali Chopade, Vinod Pachghare
Advances in Intelligent Systems and Computing, 2021
Evaluation of Digital Forensic Tools in MongoDB Database Forensics
Rupali Chopade, Vinod Pachghare
Advances in Intelligent Systems and Computing, 2021
A technique to analyze a cassandra tombstone for identification of operations
Vinod Pachghare, Rupali Chopade
Advances in Intelligent Systems and Computing, 2021
Data Tamper Detection from NoSQL Database in Forensic Environment
Rupali Chopade, Vinod Pachghare
Journal of Cyber Security and Mobility, 2021
Database Security Enhancement by Eliminating the Redundant and Incorrect Spelled Data Entries
Rupali Chopade, Vinod Pachghare
Journal of Cyber Security and Mobility, 2021
Feature Selection Based on Hall of Fame Strategy of Genetic Algorithm for Flow-Based IDS
Rahul Adhao, Vinod Pachghare
Lecture Notes in Networks and Systems, 2021
A Technique to Classify Sugarcane Crop from Sentinel-2 Satellite Imagery Using U-Net Architecture
Shyamal Virnodkar, V. K. Pachghare, Sagar Murade
Advances in Intelligent Systems and Computing, 2021
Performance Evaluation of RF and SVM for Sugarcane Classification Using Sentinel-2 NDVI Time-Series
Shyamal Virnodkar, V. K. Pachghare, V. C. Patil, Sunil Kumar Jha
Advances in Intelligent Systems and Computing, 2021
Ensemble-Based Filter Feature Selection Technique for Building Flow-Based IDS
Ishita Karna, Aniket Madam, Chinmay Deokule, Rahul Adhao, Vinod Pachghare
Access 2021 Proceedings of 2021 2nd International Conference on Advances in Computing Communication Embedded and Secure Systems, 2021
Remote sensing and machine learning for crop water stress determination in various crops: a critical review
Shyamal S. Virnodkar, Vinod K. Pachghare, V. C. Patil, Sunil Kumar Jha
Precision Agriculture, 2020
Feature selection using principal component analysis and genetic algorithm
Rahul Adhao, Vinod Pachghare
Journal of Discrete Mathematical Sciences and Cryptography, 2020
Trust Computing Model Based on Meta-Heuristic Approach for Collaborative Cloud Environment
Pooja Pol, V. K. Pachghare
Lecture Notes in Electrical Engineering, 2020
MongoDB Indexing for Performance Improvement
Rupali Chopade, Vinod Pachghare
Advances in Intelligent Systems and Computing, 2020
Automatic Selenium Code Generation for Testing
Nikhil Rathi, Rohith Srivathsav, Rishabh Chitlangia, V. K. Pachghare
Advances in Intelligent Systems and Computing, 2020
Application of Machine Learning on Remote Sensing Data for Sugarcane Crop Classification: A Review
Shyamal S. Virnodkar, Vinod K. Pachghare, V. C. Patil, Sunil Kumar Jha
Lecture Notes in Networks and Systems, 2020
Performance-Based Feature Selection Using Decision Tree
Rahul B Adhao, Vinod K Pachghare
Proceeding 1st International Conference on Innovative Trends and Advances in Engineering and Technology Icitaet 2019, 2019
Of Meta-heuristic Optimization Approaches: In Virtue of Grey Wolf Optimization
Pooja Pol, V. K. Pachghare
2019 Global Conference for Advancement in Technology Gcat 2019, 2019
Ten years of critical review on database forensics research
Rupali Chopade, V.K. Pachghare
Digital Investigation, 2019
Survey on Private Blockchain Consensus Algorithms
Sunny Pahlajani, Avinash Kshirsagar, Vinod Pachghare
Proceedings of 1st International Conference on Innovations in Information and Communication Technology Iciict 2019, 2019
Feature reduction in flow based intrusion detection system
Gayatri V. Patil, K. Vinod. Pachghare, Deepak D. Kshirsagar
2018 3rd IEEE International Conference on Recent Trends in Electronics Information and Communication Technology Rteict 2018 Proceedings, 2018
Malware detection based on string length histogram using machine learning
Snehalkumar K. Sawaisarje, Vinod K. Pachghare, Deepak D. Kshirsagar
2018 3rd IEEE International Conference on Recent Trends in Electronics Information and Communication Technology Rteict 2018 Proceedings, 2018
Road traffic prediction and congestion control using Artificial Neural Networks
Rohan More, Abhishek Mugal, Sheetal Rajgure, Rahul B. Adhao, V K. Pachghare
International Conference on Computing Analytics and Security Trends Cast 2016, 2017
Pattern based IDS using supervised, semi-supervised and unsupervised approaches
Vinod K. Pachghare, Vaibhav K. Khatavkar, Parag Kulkarni
Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering Lnicst, 2012
Pattern based network security using decision trees and support vector machine
V. K. Pachghare, Parag Kulkarni
Icect 2011 2011 3rd International Conference on Electronics Computer Technology, 2011
Performance analysis of Pattern Based network security
V. K. Pachghare, Parag Kulkarni
Icctd 2010 2010 2nd International Conference on Computer Technology and Development Proceedings, 2010
Intrusion detection system using self organizing maps
V. K. Pachghare, Parag Kulkarni, Deven M. Nikam
2009 International Conference on Intelligent Agent and Multi Agent Systems Iama 2009, 2009

V K Pachghare

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