Routing Protocols and Their Performance in Mobile Ad hoc Networks: A Quality of Service Optimization Perspective R Hari Sing, V B Narsimha 2022 Opju International Technology Conference on Emerging Technologies for Sustainable Development Otcon 2022, 2023 Mobile Ad Hoc Network (MANET) is the collection of self-configured mobile nodes withoutthe need for any fixed infrastructure. Since mobile nodes participating in MANET can have mobility and topologies change dynamically, it is important to have efficient routing protocols for MANET. It has support for proactive and reactive routing protocols that are widely used. However, there is need for optimization of routing protocols in order to improve Quality of Service (QoS). Therefore, it is indispensable to understand existing routing protocols and their performance prior to optimization of them with different strategies. In this paper we explore different routing protocols with NS-3 simulation study and evaluate their performance in terms of different metrics like Packet Delivery Ratio (PDR), throughput, end to end delay, jitter and packet dropping. Our empirical study has revealed that the protocols do have different performance levels. This paper also provides valuable insights and further routing optimization required towards improving QoS.
Variable item value-based high utility itemset recommendation using statistical approach Abdullah Bokir, V.B. Narasimha International Journal of Business Intelligence and Data Mining, 2023 High utility mining has become an absolute requirement for an efficient corporate management procedure. The challenge persists in identifying the top-out or bottom-out conditions in the context of the available HUM solutions, and it is critical for enterprises to manage adequate inventory to have higher yield outcomes. Taking these aspects into consideration, this paper proposed a comprehensive method named as 'variable item value-based high utility itemset recommendation (VIVHUIR)'. Unlike the contemporary models, which are focusing utility mining by constant utility factor, the proposed model is focusing on variable utility factor to perform utility mining based on profitability for an itemset. In addition, the drift (variability) in utility factor detection methodology is fundamentally based on the average true range for an itemset and the relative strength index (RSI) assessment for analysis, which is unique and novel feature of the proposal. To comprehend the elements influencing profit, the proposed four-layered filtering model depends on quantities, demand, supply, and gain/loss inventory. The experimental research of the model refers to potential solutions that are pragmatic in a real-time situation.
An open-source web-based OWL ontology editing and browsing tool: Swoop Role of Iot and Blockchain Techniques and Applications, 2022
Fusion of diversified utility factors for high utility mining Abdullah Bokir, V.B Narasimha Journal of Intelligent and Fuzzy Systems, 2022 High utility mining is gaining prominence, and with the increasing set of business intelligence models, the scope of such significant practices is high. Rather than focusing only on profitability as one key utility metric, today’s organizations believe in having more robust levels of the multi-objective filtering process. In this manuscript, a contemporary model of the high utility mining process is proposed, wherein the multiple averages are used for grading the recommendation of the itemsets for merchandise. The model’s key advantage is its dynamic approach. The goods-related period of the average time interval can be flexible, alongside the fusion of multiple utility thresholds of diversified features chosen for itemsets recommendation. The performance analysis has been carried out by using a multi-fold cross-validation strategy. The results obtained for cross-validation show that the proposed model is outperforming the contemporary models with significant precision, specificity, sensitivity, and accuracy having values 97%, 95%, 98%, and 97% in respective order. Whereas, the contemporary models HUPM-MUO and MOEA-FHUI have obtained 93% and 90%, 88% and 82%, 89%, and 84%, and 89% and 83% in respective order of the corresponding metrics. The experimental study of the model denotes the effectiveness and ease with which the solution can generate results and produce significant output in the real-time environment for more dynamic and periodic decisions by different organizations.
Secured Multiparty Access Control Model for Online Social Networking using Machine Learning Madhu Nakerekanti, Dr. V B Narsimha Ecs Transactions, 2022 In recent years, Online Social Networks (OSNs) have registered significant growth. They have become part of daily routine life, a phenomenon that received the serious attention of academic, technological, and social research communities. Many OSNs allow its users to post multimedia content, communicate in various ways, and share many aspects of their life in addition to building a virtual network of social relationships. While sharing data to the multiple users, there is no mechanism in place to enforce privacy and security issues in OSNs. Users in OSNs reveal personal information such as their profiles photos, relationship status, phone numbers, dates of birth, and other social activities without being aware of the risks and thefts which may occur. Therefore, this paper aims to capture the concepts of multiparty authorization and policy enforcement in an access control model. The paper deliberates broad-spectrum issues of the multi-users such as privacy and security issues, data integrity, scalability, data authentication, and so on, while sending the data. To overcome such a situation, we need to develop an innovative framework, i.e. Novel Adaptive Privacy Policy Prediction (NA3P), for multi-users access control policies using machine learning classification techniques to provide security and policy prediction for shared content.
Swine flu Detection and Location using Machine Learning Techniques and GIS P. Nagaraj, A. V. Krishna Prasad, V. B. Narsimha, B. Sujatha International Journal of Advanced Computer Science and Applications, 2022 The H1N1 virus, more commonly referred to as swine flu, is an illness that is extremely infectious and can in some cases be fatal. Because of this, the lives of many individuals have been taken. The disease can be transmitted from pigs to people. This research presents an artificial neural network (ANN) classifier for disease forecasting, as well as a technique for detecting people who are sick based on the geographic region in which they are found. The source codes for these two algorithms are provided below. These coordinates serve as the foundation for the GIS coordinates that are utilized in the method for assessing the extent to which the illness has spread. The ICMR and NCDC datasets were utilized in the study. They used Dynamic Boundary Location algorithm to detect swine flu affected person’s location, the researchers discovered that the accuracy of the proposed classifier was 96 standard classifiers.
High Utility Mining of Streaming Itemsets in Data Streams Abdullah Bokir, V B Narasimha Journal of Physics Conference Series, 2021 The traditional models for mining frequent itemsets mainly focus on the frequency of the items listed in the respective dataset. However, market basket analysis and other domains generally prefer utility obtained from items regardless of their frequencies in the transactions. One of the main options of utility in these domains could be profit. Therefore, it is significant to extract items that generate more profit than items that occurs more frequently in the dataset. Thus, mining high utility itemset has emerged recently as a prominent research topic in the field of data mining. Many of the existing researches have been proposed for mining high utility itemset from static data. However, with the recent advanced technologies, streaming data has become a good source for data in many applications. Mining high utility itemset over data streams is a more challenging task because of the uncertainty in data streams, processing time, and many more. Although some works have been proposed for mining high utility itemset over data streams, many of these works require multiple database scans and they require long processing time. In respect to this, we proposed a single-pass fast-search model in which we introduced a utility factor known as utility stream level for tracing the utility value of itemsets from data streams. The simulation study shows that the performance of the proposed model is more significant compared with the contemporary method. The comparison has been performed based on metrics like process-completion time and utilized search space.
A contextual deep clustering based intrusion detection method for cloud International Journal of Advanced Science and Technology, 2019
Detection of intrusion using hybrid feature selection and flexible rule based machine learning Reserach Scholar-JNTUH & Associate Professor, Department of CSE-GNIT, B. Sudhakar*, V. B. Narsimha, Associate Professor, Department of CSE- University College of Engineering, OU, Dr. G. Narsimaha, Professor, Department of CSE- JNTUH College of Engineering, JNTUH. International Journal of Engineering and Advanced Technology, 2019
Steganography images detection using different steganalysis techniques with markov chain features International Journal of Applied Engineering Research, 2016
Application maintenance and support International Journal of Applied Engineering Research, 2014
RECENT SCHOLAR PUBLICATIONS
Analyzing consumer behavior and shopping preferences using bootstrap aggregated neural regressor G Redapangu, VB Narsimha Journal of applied research on industrial engineering 12 (1), 16-35 , 2025 2025 Citations: 3
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NETWORK INTRUSION DETECTION USING CONTINUOUS DEEP LEARNING INTRUSION DETECTION MODEL AND DISTRIBUTED HONEYPOT FRAMEWORK DVBN Harisingh Ratnavath ANVESAK 53 (1), 102-112 , 2023 2023
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Arriving at the Results by Comparing with Traditional Approach to My Approach in Deriving Function Points for ETL Operations v b narasimha Akula Rakesh Phanindra International Journal of Recent Technology and Engineering (IJRTE) 11 (5), 53-57 , 2023 2023
Variable item value-based high utility itemset recommendation using statistical approach A Bokir, VB Narasimha International Journal of Business Intelligence and Data Mining 23 (2), 101-124 , 2023 2023 Citations: 1
Fusion of diversified utility factors for high utility mining A Bokir, VB Narasimha Journal of Intelligent & Fuzzy Systems 43 (3), 2391-2405 , 2022 2022
Secured multiparty access control model for online social networking using machine learning M Nakerekanti, DVB Narsimha Electrochemical Society Transactions 107 (1), 9359-9372 , 2022 2022 Citations: 4
Arriving at the General System Characteristics required for Value Adjustment Factor for ETL operations using Function Point Analysis DVBN A. Rakesh Phanindra Indian Institution of Industrial Engineering (IIIE) 51 (12) , 2022 2022
Accurate Document Retrieval with Sub-Topic Attention Using Term Frequancy - Inverse Document Frequancy Badamoni Srinaiah TELEMATIQUE 21 (1), 6230-6239 , 2022 2022
Secured Multiparty Access Control Model for Online Social Networking Using Machine Learning MNDVB Narsimha INTERNATIONAL CONFERENCE ON TECHNOLOGIES FOR SMART GREEN CONNECTED … , 2022 2022
High Utility Pattern Mining: A Survey on Current and Possible Areas of Applications A Bokir, V Narasimha Review of Information Engineering and Applications 9 (1), 38-49 , 2022 2022 Citations: 1
Label Based Access Control for Cloud Service Security and Attack Detection S Radharani, VB Narasimha Design Engineering, 5641-5664 , 2021 2021
Feature-Based Learning Model for Fake News Detection and Classification GPC Rao, VB Narasimha 2021
Feature-Based Learning Model for Fake News Detection and Classification VBN G. Purna Chandar Rao International Journal of Scientific Research in Science and Technology 8 (6 … , 2021 2021
Geo Spatial Imported System for Online Payments M Nakerekanti, VB Narsimha International Journal of Advanced Research in Science, Communication and … , 2021 2021
Fake news detection by Coupling Count Vectorizer and TF-IDFswith Bi-directional Gated Recurrent Unit DVBN G.Purna chandar Rao The International journal of analytical and experimental modal analysis 13 … , 2021 2021
High Utility Mining of Streaming Itemsets in Data Streams A Bokir, VB Narasimha Journal of Physics: Conference Series 1962 (1), 012027 , 2021 2021 Citations: 1
A Research on Online Fake News Detection using Machine Learning Techniques GPCRVB Narasimha Turkish Journal of Computer and Mathematics Education 12 (10), 2790-2796 , 2021 2021 Citations: 3
A novel framework for cloud based virtual machine security by change management using machine S Radharani, VB Narasimha International Journal of Advanced Computer Science and Applications 12 (12) , 2021 2021 Citations: 1
MOST CITED SCHOLAR PUBLICATIONS
Analysis on malware issues in online social networking sites (sns) M Nakerekanti, VB Narasimha 2019 5th International Conference on Advanced Computing & Communication … , 2019 2019 Citations: 13
Steganography image detection using different steganalysis techniques with Markov chain features K Rajendraprasad, VB Narasimha International Journal of Applied Engineering Research 11 (1), 392-395 , 2016 2016 Citations: 6
Technology implementation in public sectors units of Andhra Pradesh RP Akula, VB Narasimha, M Chandrashekar International Journal of Advanced Computer Research 4 (2), 518 , 2014 2014 Citations: 6
A review on application security management using web application security standards A Rakesh Phanindra, VB Narasimha, CV PhaniKrishna Software Engineering: Proceedings of CSI 2015, 477-486 , 2018 2018 Citations: 5
Optimizing identity and access management through 1D-SCNN-based anomaly detection P Cheruku, VB Narasimha Journal of Applied Research on Industrial Engineering 11 (4), 574-592 , 2024 2024 Citations: 4
Secured multiparty access control model for online social networking using machine learning M Nakerekanti, DVB Narsimha Electrochemical Society Transactions 107 (1), 9359-9372 , 2022 2022 Citations: 4
Analyzing consumer behavior and shopping preferences using bootstrap aggregated neural regressor G Redapangu, VB Narsimha Journal of applied research on industrial engineering 12 (1), 16-35 , 2025 2025 Citations: 3
Network intrusion detection using ensemble weighted voting classifier based honeypot and ids framework H Ratnavath, V Narasimha Network 52, 3 , 2023 2023 Citations: 3
A Research on Online Fake News Detection using Machine Learning Techniques GPCRVB Narasimha Turkish Journal of Computer and Mathematics Education 12 (10), 2790-2796 , 2021 2021 Citations: 3
Optimized key management scheme for sensor networks using genetic algorithm B Hari Krishna, VB Narasimha Innovations in Computer Science and Engineering: Proceedings of the Fifth … , 2018 2018 Citations: 3
Survey on design challenges and analysis of service architecture of DRM TS Srinivas, VB Narasimha, ME Puroshothammam 2017 International Conference on Trends in Electronics and Informatics (ICEI … , 2017 2017 Citations: 3
Analysis of interoperability services of various DRM schemes and associations with Marlin scheme TS Srinivas, VB Narasimha, ME Puroshothammam Indian Journal of Science and Technology 10 (17), 1-8 , 2017 2017 Citations: 3
An Approach to Multi-Cloud Securities P Sabitha, VB Narasimha Int. J. Adv. Res. Ideas Innov. Technol. 4, 89-92 , 2018 2018 Citations: 2
Variable item value-based high utility itemset recommendation using statistical approach A Bokir, VB Narasimha International Journal of Business Intelligence and Data Mining 23 (2), 101-124 , 2023 2023 Citations: 1
High Utility Pattern Mining: A Survey on Current and Possible Areas of Applications A Bokir, V Narasimha Review of Information Engineering and Applications 9 (1), 38-49 , 2022 2022 Citations: 1
High Utility Mining of Streaming Itemsets in Data Streams A Bokir, VB Narasimha Journal of Physics: Conference Series 1962 (1), 012027 , 2021 2021 Citations: 1
A novel framework for cloud based virtual machine security by change management using machine S Radharani, VB Narasimha International Journal of Advanced Computer Science and Applications 12 (12) , 2021 2021 Citations: 1
Mining Web Graphs for Large Scale Meta Search Engine Results B Krishna International Journal Of Engineering And Computer Science , 2017 2017 Citations: 1
NETWORK INTRUSION DETECTION USING CONTINUOUS DEEP LEARNING INTRUSION DETECTION MODEL AND DISTRIBUTED HONEYPOT FRAMEWORK DVBN Harisingh Ratnavath ANVESAK 53 (1), 102-112 , 2023 2023
Arriving at the Results by Comparing with Traditional Approach to My Approach in Deriving Function Points for ETL Operations v b narasimha Akula Rakesh Phanindra International Journal of Recent Technology and Engineering (IJRTE) 11 (5), 53-57 , 2023 2023
