B.Mahesh

@drkvsrit.ac.in

Associate Professor, Department of CSE
Dr.K.V.Subba Reddy Institute of Technology

B.Mahesh


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https://researchid.co/basuthkar

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering
6

Scopus Publications

58

Scholar Citations

4

Scholar h-index

1

Scholar i10-index

Scopus Publications

  • Gaussian filter and CNN based framework for accurate detection of brain tumor by analyzing MRI images
    S Sivakumar, Poonam Chaudhari, Satish Thatavarti, G. Sucharitha, Basuthkar Mahesh, Abhishek Raghuvanshi
    Bulletin of Electrical Engineering and Informatics, 2024
    The diagnosis of cancer can be challenging and time-consuming due to the complex characteristics of tumors and inherent noise in medical imaging. The significance of early detection and localization of tumors must be considered. Radiological imaging techniques can detect and potentially forecast the presence of neoplastic growths at various phases. The expeditiousness of the diagnosis process can be notably enhanced by amalgamating these images with algorithms designed for segmentation and relegation. Early detection of tumors and accurate localization of their position are critical factors. Medical scans, when used with segmentation and relegation procedures, enable the prompt and precise detection of cancerous tumor regions. The identification of malignant tumors enables this achievement. The present article introduces a framework for detecting brain tumors based on a convolutional neural network (CNN). The initial step in processing brain magnetic resonance imaging (MRI) images involves the application of a Gaussian filter to eliminate any noise present. Subsequently, CNN and long short-term memory (LSTM) deep learning methodologies are employed to classify images. CNN has demonstrated improved accuracy in the classification and detection of brain tumors. CNN has achieved an accuracy of 99.25% in cancer image classification. The sensitivity and specificity of CNN are also 98.75% and 99.25%, respectively.
  • Machine Learning Techniques For Design Of Intrusion Detection System For Big Data Networks
    Basuthkar Mahesh, Maninti Venkteswarlu, Akampurira Paul
    2023 Global Conference on Information Technologies and Communications Gcitc 2023, 2023
    As digital technology advances, gigabytes and terabytes of data are now generated every second. Businesses in a variety of industries are finding that using the internet to manage their resources and transactions is useful. Given the value of data and the need to safeguard its security and privacy, securing big data remains a major challenge for all solutions. Due to the exponential expansion of network data, intrusion detection is becoming increasingly important, and manual analysis would be either impossible or take the same amount of time as analyzing it. As a result, there is an urgent need for an automated system capable of extracting relevant information from enormous amounts of hitherto untapped data when it comes to network intrusion detection. Data mining can perform a variety of tasks, such as clustering, prediction, classification, and the extraction of association rules between data pieces. In this research, we explore the application of machine learning methodologies to the task of creating intrusion detection systems for large data networks. As an input for this methodology, the NSL KDD data set is used. In the first step of this process, useful features from the NSL KDD data set are extracted using the CFS-correlation technique to feature selection. There are 41 features included in the NSL KDD data collection. Following the use of the CFS method, the total number of features was cut down to 16. Following this, machine learning methods are used to the NSL KDD data set in order to features the malware data and make predictions based on the data using the 16 characteristics.
  • AI Aero Science Model To Predict Security And To Improve The Fault Space System
    Pankaj Ramakant Kunekar, Mohammed Azam, R.R. Maggavi, Anita Gehlot, Basuthkar Mahesh, Giriraj Kumar Prajapati
    2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering Icacite 2022, 2022
    Over the past two years, information sharing and collaboration between pilots, supervisors, developers and maintenance workers has led to significant improvements in aviation safety. As the volume of information sharing increases, it has become necessary to integrate intelligence (AI) principles and to learn in-depth processes, data-driven structures to predict behavior, search patterns, and discover hidden secrets. In-depth learning systems can be used in the near future. For example, face security systems currently only use surveillance data to predict and report inconsistencies and conflicts, which may result in alarm delays or malfunction. AI, especially machine learning (ML), still had a long way to go before it was widely used in the application field, but was already integrated into new technologies. One area that Al explores is in the field of satellite operations, particularly to support the sale of large satellite stars, which include relative positions, communications, life management, etc.
  • A Review on Data Deduplication Techniques in Cloud
    B. Mahesh, K. Pavan Kumar, Somula Ramasubbareddy, E. Swetha
    Advances in Intelligent Systems and Computing, 2020
  • AES cryptograph for secure cloud storage
    , B. Mahesh, K. Pavan Kumar, , M. Jahir Pasha, and
    International Journal of Engineering and Advanced Technology, 2019
    In cloud computing disseminated assets are shared by means of system in open condition. Subsequently client can without much of a stretch access their information from anyplace. Simultaneously exist protection and security problems because of numerous causes. Initial one is emotional improvement in system advances. Another is expanded interest for computing assets, which make numerous associations to re-appropriate their information stockpiling. So there is a requirement for secure cloud stockpiling administration in open cloud condition where the supplier isn't a confided in one. Our research tends to various information security and protection assurance problems in a cloud computing condition and suggests a technique for giving diverse security administrations like validation, approval and classification alongside checking in postponement. 128 piece Advanced Cryptograph Standard (AES) is utilized to increment information security and classification. In this supported methodology information is encoded utilizing AES and afterward transferred on a cloud. The supported model uses Short Message Service (SMS) ready instrument with keeping away from unapproved access to client information.
  • End-to-end congestion control techniques for router
    Bhasutkar Mahesh, Maninti Venkateswarlu, M. Raghavendra
    Proceedings 2011 International Conference on Communication Systems and Network Technologies Csnt 2011, 2011
    END-TO-END packet delay is one of the canonical metrics in Internet Protocol (IP) networks and is important both from the network operator and application performance points of view. The motivation for the present work is a detailed know-ledge and understanding of such "through-router" delays. A thorough examination of delay leads inevitably to deeper quest-ions about congestion and router queuing dynamics in general. Although there have been many studies examining delay statistics and congestion measured at the edges of the network, very few have been able to report with any degree of authority on what actually occurs at switching elements. In existing system the single-hop packet delay measured and analyzed through operational routers in a backbone IP network. However since the router had only one input and one output link, which were of the same speed, the internal queuing was extremely limited. In this paper work with a data set recording all IP packets traversing a Tier-1 access router. All input and output links were monitored, allowing a complete picture of congestion and in particular router delays to be obtained. This paper provides a comprehensive examination of these issues from the understanding of origins and measurement.

RECENT SCHOLAR PUBLICATIONS

  • Gaussian filter and CNN based framework for accurate detection of brain tumor by analyzing MRI images
    S Sivakumar, P Chaudhari, S Thatavarti, G Sucharitha, B Mahesh, ...
    Bulletin of Electrical Engineering and Informatics 13 (6), 4214-4222 , 2024
    2024.0
    Citations: 4
  • Machine Learning Techniques For Design Of Intrusion Detection System For Big Data Networks
    B Mahesh, M Venkteswarlu, A Paul
    2023 Global Conference on Information Technologies and Communications (GCITC … , 2023
    2023.0
    Citations: 4
  • AI Aero Science Model To Predict Security And To Improve The Fault Space System
    PR Kunekar, M Azam, RR Maggavi, A Gehlot, B Mahesh, GK Prajapati
    2nd International Conference on Advance Computing and Innovative … , 2022
    2022.0
    Citations: 2
  • Evaluating Malware Detection System using Machine Learning Algorithms
    SB Naik, B Mahesh, KD Koilakuntla
    International Journal of Scientific Research in Computer Science … , 2021
    2021.0
    Citations: 1
  • A review on data deduplication techniques in cloud
    B Mahesh, K Pavan Kumar, S Ramasubbareddy, E Swetha
    Embedded Systems and Artificial Intelligence: Proceedings of ESAI 2019, Fez … , 2020
    2020.0
    Citations: 31
  • Cost Optimization Techniques in Cloud Computing [J]
    B Mahesh
    International Journal of Computer Sciences & Engineering 6 (1), 375-380 , 2018
    2018.0
    Citations: 6
  • Dynamic Update and Public Auditing with Dispute Arbitration for Cloud Data
    B Mahesh
    Journal of Advanced Database Management & Systems 4, 14-19 , 2017
    2017.0
    Citations: 3
  • End-to-end congestion control techniques for Router
    B Mahesh, M Venkateswarlu, M Raghavendra
    2011 International Conference on Communication Systems and Network … , 2011
    2011.0
    Citations: 4
  • A Study of Machine Learning and Deep Learning Approaches for Breast Cancer Detection
    B Mahesh, G Nellore
  • Router Aided Congestion Control Techniques
    B Mahesh, KSS Reddy
    Second International Conference on Information Systems and Technology, 72 , 0
    Citations: 3
  • An Active Approach for Load Balancing in Grid Computing
    B Mahesh

MOST CITED SCHOLAR PUBLICATIONS

  • A review on data deduplication techniques in cloud
    B Mahesh, K Pavan Kumar, S Ramasubbareddy, E Swetha
    Embedded Systems and Artificial Intelligence: Proceedings of ESAI 2019, Fez … , 2020
    2020.0
    Citations: 31
  • Cost Optimization Techniques in Cloud Computing [J]
    B Mahesh
    International Journal of Computer Sciences & Engineering 6 (1), 375-380 , 2018
    2018.0
    Citations: 6
  • Gaussian filter and CNN based framework for accurate detection of brain tumor by analyzing MRI images
    S Sivakumar, P Chaudhari, S Thatavarti, G Sucharitha, B Mahesh, ...
    Bulletin of Electrical Engineering and Informatics 13 (6), 4214-4222 , 2024
    2024.0
    Citations: 4
  • Machine Learning Techniques For Design Of Intrusion Detection System For Big Data Networks
    B Mahesh, M Venkteswarlu, A Paul
    2023 Global Conference on Information Technologies and Communications (GCITC … , 2023
    2023.0
    Citations: 4
  • End-to-end congestion control techniques for Router
    B Mahesh, M Venkateswarlu, M Raghavendra
    2011 International Conference on Communication Systems and Network … , 2011
    2011.0
    Citations: 4
  • Dynamic Update and Public Auditing with Dispute Arbitration for Cloud Data
    B Mahesh
    Journal of Advanced Database Management & Systems 4, 14-19 , 2017
    2017.0
    Citations: 3
  • Router Aided Congestion Control Techniques
    B Mahesh, KSS Reddy
    Second International Conference on Information Systems and Technology, 72 , 0
    Citations: 3
  • AI Aero Science Model To Predict Security And To Improve The Fault Space System
    PR Kunekar, M Azam, RR Maggavi, A Gehlot, B Mahesh, GK Prajapati
    2nd International Conference on Advance Computing and Innovative … , 2022
    2022.0
    Citations: 2
  • Evaluating Malware Detection System using Machine Learning Algorithms
    SB Naik, B Mahesh, KD Koilakuntla
    International Journal of Scientific Research in Computer Science … , 2021
    2021.0
    Citations: 1
  • A Study of Machine Learning and Deep Learning Approaches for Breast Cancer Detection
    B Mahesh, G Nellore
  • An Active Approach for Load Balancing in Grid Computing
    B Mahesh