Computer Networks and Communications, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Science Applications
19
Scopus Publications
152
Scholar Citations
6
Scholar h-index
6
Scholar i10-index
Scopus Publications
Advancing Multimodal Emotion Detection: A Comprehensive Survey of Techniques, Challenges and Applications 16th International Conference on Advances in Computing Control and Telecommunication Technologies Act 2025, 2025
Anomaly based intrusion detection using ensemble machine learning and block-chain Srinivasa Rao Mekala, Shaik Nazma, Kumbhagiri Nava Chaitanya, Thota Ambica Iaes International Journal of Artificial Intelligence, 2024 <p>A major issue facing the quickly evolving technological world is the surge in security concerns, particularly for critical Internet-of-Things (IoT) applications like health care and the military. Early security attack detection is crucial for safeguarding important resources. Our research focuses on developing an anomaly-based intrusion detection system (IDS) using machine learning (ML) models. With the use of voting strategies, Bagging Ensemble, Boosting Ensemble, and Random Forest, we created a robust and long-lasting IDS. The F1 score is a crucial metric for measuring accurate predictions at the class level and serves as the focus of these ML systems. Maintaining a high F1 score in critical applications highlights the constant need for development. Make use of the latest CICIoT2023 data-set employ Hyper-ledger Fabric to create a private channel in order to bolster the security of our IDS through the usage of block-chain technology. We use block-chain's immutable record and cryptographic techniques to establish a decentralized, tamper-proof environment. Consequently, our proposed approach provides an efficient intrusion detection system that significantly enhances resource protection and alerting the user in prior with intruder information incritical regions for Internet of Things security applications.</p>
SCS: A Secure Cloud Storage Framework with Enhanced Integrity and Auditability Using Consortium Blockchain System Aguru Aswani Devi, Erukala Suresh Babu, Mekala Srinivasa Rao, Rajesh Kaluri, Thippa Reddy Gadekallu Proceedings 2024 IEEE International Conference on Smart Internet of Things Smartiot 2024, 2024 The widespread adoption of cloud storage enables users to remotely access resources through a self-service model. Utilizing pay-per-use storage services provided by cloud service providers (CSPs) requires users to commit financially to their resources. This paper introduces a Secure Cloud Storage (SCS) framework, offering a secure architecture for cloud storage using a consortium blockchain network to address trust issues. This framework substitutes the third-party auditor with peers of a consortium blockchain network, which handles the role of data storage and verification. Storage space is divided into uncommitted and committed segments. Uncommitted storage is used for storing unverified documents, while committed storage is reserved for documents that have been validated through a consensus mechanism. In contrast, committed storage is des-ignated for the storage of committed documents. Documents validated by a consensus threshold of peer nodes are moved from uncommitted to committed storage. The implementation of the SCS framework is conducted using Hyperledger Fabric, a modular blockchain platform optimized for permissioned networks. The security analysis demonstrates that SCS effectively protects cloud storage against attacks, including unauthorized access attacks, data integrity attacks, and malicious server attacks, while maintaining data integrity and auditability. The performance evaluation shows that document upload and retrieval times, block acceptance, execution times, and latency are all improved compared to state-of-the-art cloud storage techniques.
Fog-Sec: Secure end-to-end communication in fog-enabled IoT network using permissioned blockchain system Erukala Suresh Babu, Mekala Srinivasa Rao, Gandharba Swain, A. Kousar Nikhath, Rajesh Kaluri International Journal of Network Management, 2023 The technological integration of the Internet of Things (IoT)‐Cloud paradigm has enabled intelligent linkages of things, data, processes, and people for efficient decision making without human intervention. However, it poses various challenges for IoT networks that cannot handle large amounts of operation technology (OT) data due to physical storage shortages, excessive latency, higher transfer costs, a lack of context awareness, impractical resiliency, and so on. As a result, the fog network emerged as a new computing model for providing computing capacity closer to IoT edge devices. The IoT‐Fog‐Cloud network, on the other hand, is more vulnerable to multiple security flaws, such as missing key management problems, inappropriate access control, inadequate software update mechanism, insecure configuration files and default passwords, missing communication security, and secure key exchange algorithms over unsecured channels. Therefore, these networks cannot make good security decisions, which are significantly easier to hack than to defend the fog‐enabled IoT environment. This paper proposes the cooperative flow for securing edge devices in fog‐enabled IoT networks using a permissioned blockchain system (pBCS). The proposed fog‐enabled IoT network provides efficient security solutions for key management issues, communication security, and secure key exchange mechanism using a blockchain system. To secure the fog‐based IoT network, we proposed a mechanism for identification and authentication among fog, gateway, and edge nodes that should register with the blockchain network. The fog nodes maintain the blockchain system and hold a shared smart contract for validating edge devices. The participating fog nodes serve as validators and maintain a distributed ledger/blockchain to authenticate and validate the request of the edge nodes. The network services can only be accessed by nodes that have been authenticated against the blockchain system. We implemented the proposed pBCS network using the private Ethereum 2.0 that enables secure device‐to‐device communication and demonstrated performance metrics such as throughput, transaction delay, block creation response time, communication, and computation overhead using state‐of‐the‐art techniques. Finally, we conducted a security analysis of the communication network to protect the IoT edge devices from unauthorized malicious nodes without data loss.
Cross-Site Request Forgery as an Example of Machine Learning for Web Vulnerability Detection Mekala Srinivasa Rao, Birudugadda Kalyani, Baswani Vathsalya, Karri Dhanunjay, Alasandalapalli Lakshmi Narayana Proceedings 2023 3rd International Conference on Smart Data Intelligence Icsmdi 2023, 2023 This paper presents a strategy for discovering flaws in web applications through Machine Learning (ML). Web-based applications are especially troublesome to examine attributed to their variety and extensive usage of custom development methodologies. As little more than a basis, machine learning is extremely useful in website safety: It just might combine cognitive knowledge of web app terminology with automated software approaches based on verbally reported information. Mitch tool is the foremost machine learning strategy towards black-box investigation for Cross-Site Request Forgery (C.S.R.F) problems, was built using these principles. Mitch-helped us find Thirty-five recently developed cross-site request forgeries (C.S.R. Fs) in twenty wide fields, together with 3 main C.S.R. Fs in industry applications.
Change detection of pulmonary embolism using isomeric cluster and computer vision Mekala Srinivasa Rao, Sagenela Vijaya Kumar, Rambabu Pemula, Anil Kumar Prathipati Iaes International Journal of Artificial Intelligence, 2022 <p>Visual change detection functions in X-ray analytics and computer vision attempt to divide X-ray images toward front and backside areas. There are various difficulties in change detection such as weather changes and shadows; real-time processing; intermittent object motion; lighting variation; and diverse object forms. Traditionally, this issue has been addressed via backdrop modeling methods and the creation of custom features. We present a new feature descriptor called pulmonary embolism detection using isomeric cluster (PEDIC), uses the concept of isomerism. The isomeric and cluster isomerism characteristics of the PEDIC are distinguish it from other graphs. At isomeric thetical orientations, the cluster pattern corresponds to consecutive differences in pixel intensity between the two images. Also, the clusters are oppositely orientated, and both clusters conform to a specified isomeric feature. The local area's lines and corner point information are identified and recorded using the PEDIC in several different directions. We introduced multiresolution PEDIC, which incorporates the multiresolution Gaussian filter to achieve increased resilience in the system. We expanded our research to include rotation-invariant characteristics. We also proposed inter-PEDIC and intra-PEDIC to identify motion changes in X-ray sequences, which allowed them to extract spatiotemporal characteristics.</p>
Ant Cat Swarm Optimization-Enabled Deep Recurrent Neural Network for Big Data Classification Based on Map Reduce Framework Satyala Narayana, Suresh Babu Chandanapalli, Mekala Srinivasa Rao, Kalyanapu Srinivas Computer Journal, 2022 The amount of data generated is increasing day by day due to the development in remote sensors, and thus it needs concern to increase the accuracy in the classification of the big data. Many classification methods are in practice; however, they limit due to many reasons like its nature for data loss, time complexity, efficiency and accuracy. This paper proposes an effective and optimal data classification approach using the proposed Ant Cat Swarm Optimization-enabled Deep Recurrent Neural Network (ACSO-enabled Deep RNN) by Map Reduce framework, which is the incorporation of Ant Lion Optimization approach and the Cat Swarm Optimization technique. To process feature selection and big data classification, Map Reduce framework is used. The feature selection is performed using Pearson correlation-based Black hole entropy fuzzy clustering. The classification in reducer part is performed using Deep RNN that is trained using a developed ACSO scheme. It classifies the big data based on the reduced dimension features to produce a satisfactory result. The proposed ACSO-based Deep RNN showed improved results with maximal specificity of 0.884, highest accuracy of 0.893, maximal sensitivity of 0.900 and the maximum threat score of 0.827 based on the Cleveland dataset.
Verifiable Authentication and Issuance of Academic Certificates Using Permissioned Blockchain Network Erukala Suresh Babu, B. K. N. Srinivasarao, Ilaiah Kavati, Mekala Srinivasa Rao International Journal of Information Security and Privacy, 2022 Fake certificates pose a severe problem in today's world; they vouch for an individual's false skillset and put an organization's reputation at risk. Moreover, the existing verification process is performed in a centralized manner, often too cumbersome and time-consuming to the end-user, lacking transparency in the educational institutions' Issuance of certificates. Of-late, blockchain is a promising technology that provides transparent, secure, and reliable features, which offers solutions to the education sector. This paper provides the solution to the educational certification problem by employing the blockchain network. We proposed a permissioned blockchain network that identifies, authenticates the Issuer, adequate verification, securely shares academic records to the recipients, and stores the certificate credentials in the blockchain in a distributed manner.
An Analytical Hierarchy Process Investigation on High Speed Data Implementations Using Big Data Yugandhar Garapati, G.Charles Babu, K. Venkata Murali Mohan, Mekala Srinivasa Rao, J Kavitha 2022 International Conference on Computer Communication and Informatics Iccci 2022, 2022 Present Research tells about the intensity of information and communication technology by analytical hierarchy process utilized in a major big data study to convey data abouthow to make framework which will allow expanding and testing a lot of registering gadgets and a centerSoftware. The explanation of this task is to build the investigation framework for the rapid huge information preparing methodology and to get the center Software and standard ability. The explanation of this investigation is to execute the probability examination on this task. This examinationis utilizing the Analytic Hierarchy Process technique. It is built up the exact investigation process andcan quick demonstrate the intensity of the undertaking by manipulative the loads of the appraisalmethod. The result of this investigation, the total score by Analytic Hierarchy Process examination is 0.869. It demonstrates the execution if task is Possible.
Secure exchange and effectual verification of educational academic records using hyperledger fabric block chain system E. Suresh Babu, M. Srinivasa Rao, Satuluri Naganjaneyulu, M. Srinivasa Sesha Sai, Rajendra Kumar Ganiya International Journal of Ad Hoc and Ubiquitous Computing, 2022 This paper provides a solution to the educational certification issue by employing the blockchain network. The proposed permissioned blockchain network is implemented in hyperledger fabric. The proposed system provides various services to issuing institutions: verifying organisation; identification and authentication of the issuer; verify and securely share academic records to the recipients; and stores the academic records in the blockchain in a distributed manner, ensuring the privacy of stored records of the recipient. When compared to Ethereum, hyperledger fabric provides additional functionalities like efficient parallelism, concurrency, multiple transaction executions, and efficient commitments of the transaction into the ledger. The experimental analysis of the proposed system has been executed to test the performance of invoking and query transactions using Hyperledger Caliper. We analyse the throughput and transaction latency of the proposed work as well. The experimental results exhibit the proposed system achieves better transaction processing power and security compared to existing systems.
Texture classification based on statistical properties of local units Journal of Theoretical and Applied Information Technology, 2016
RECENT SCHOLAR PUBLICATIONS
SCS: A Secure Cloud Storage Framework with Enhanced Integrity and Auditability Using Consortium Blockchain System AA Devi, ES Babu, MS Rao, R Kaluri, TR Gadekallu 2024 IEEE International Conference on Smart Internet of Things (SmartIoT), 79-86 , 2024 2024 Citations: 3
Anomaly based intrusion detection using ensemble machine learning and block-chain TA Mekala SrinivasaRao, ShaikNazma, KumbhagiriNavaChaitanya IAES International Journal of Artificial Intelligence (IJ-AI) 13 (3), 2754~2762 , 2024 2024
Fog‐Sec: Secure end‐to‐end communication in fog‐enabled IoT network using permissioned blockchain system ES Babu, MS Rao, G Swain, AK Nikhath, R Kaluri International Journal of Network Management 33 (5), e2248 , 2023 2023 Citations: 24
Cross-Site Request Forgery as an Example of Machine Learning for Web Vulnerability Detection MS Rao, B Kalyani, B Vathsalya, K Dhanunjay, AL Narayana 2023 3rd International Conference on Smart Data Intelligence (ICSMDI), 422-426 , 2023 2023
Ant cat swarm optimization-enabled deep recurrent neural network for big data classification based on map reduce framework S Narayana, SB Chandanapalli, MS Rao, K Srinivas The Computer Journal 65 (12), 3167-3180 , 2022 2022 Citations: 15
Secure exchange and effectual verification of educational academic records using hyperledger fabric block chain system ES Babu, MS Rao, S Naganjaneyulu, MSS Sai, RK Ganiya International Journal of Ad Hoc and Ubiquitous Computing 40 (1/2/3), 194-213 , 2022 2022 Citations: 2
A Hybrid Intrusion Detection System against Botnet Attack in IoT using Light Weight Signature and Ensemble Learning Technique ES Babu, MS Rao, R Pemula, SR Nayak, A Shankar 2022 Citations: 6
An Optimized Fuzzy-Based Resource Allocation for Cloud Using Secured Tabu Search Technique C Srinivasa Kumar, RS Sirisati, M Srinivasa Rao, MV Narayana, ... Innovations in Computer Science and Engineering: Proceedings of the Ninth … , 2022 2022 Citations: 3
An Optimized Fuzzy-Based Resource Allocation for Cloud Using Secured Tabu CS Kumar, RS Sirisati, MS Rao, MV Narayana, J Rajeshwar Innovations in Computer Science and Engineering: Proceedings of the Ninth … , 2022 2022
An Analytical Hierarchy Process Investigation on High Speed Data Implementations Using Big Data Y Garapati, GC Babu, KVM Mohan, MS Rao, J Kavitha 2022 International Conference on Computer Communication and Informatics … , 2022 2022 Citations: 1
Change detection of pulmonary embolism using isomeric cluster and computer vision AK Rao, M.S., Kumar, S.V., Pemula, R., Prathipati IAES International Journal of Artificial Intelligence 11 (2), 787-798 , 2022 2022 Citations: 2
Verifiable Authentication and Issuance of Academic Certificates Using Permissioned Blockchain Network ES Babu, BKN Srinivasarao, I Kavati, MS Rao International Journal of Information Security and Privacy (IJISP) 16 (1), 1-24 , 2022 2022 Citations: 24
A Hybrid Clinical Data Predication Approach Using Modified PSO PSVS Rao, MS Rao, RS Sirisati Smart Computing Techniques and Applications: Proceedings of the Fourth … , 2021 2021
Permissioned Blockchain-based Collaborative Intrusion Detection System to Secure Internet of Things Against DDoS Attacks RC Erukala Suresh Babu, BKN Srinivasa Rao, M. Srinivasa Rao, Ilaiah Kavati Journal of Information Assurance and Security 16 (5), 178-191 , 2021 2021
A Hybrid Clinical Data Predication Approach Using Modified PSO PSV Srinivasa Rao, MS Rao, RS Sirisati Smart Computing Techniques and Applications: Proceedings of the Fourth … , 2021 2021 Citations: 3
A heuristic methodology for ECG heartbeat categorization using Convolutional Neural Networks PMYKAK P. S. V. Srinivasa Rao, M. Srinivasa Rao, P. Gopala Krishna 2nd International Conference on Smart Electronics and Communication (ICOSEC … , 2021 2021
Automatic Music Genre Classification Based on Linguistic Frequencies Using Machine Learning MS Rao, OP Kalyan, NN Kumar, MT Tabassum, B Srihari International Conference on Recent Advances in Mathematics and Informatics … , 2021 2021 Citations: 11
Auto-Adaptive Learning for Machine Perception of Native Accent Using Deep Learning SRS Mekala Srinivasa Rao, P.S.V. Srinivasa Rao Proceedings of First International Conference on Mathematical Modeling and … , 2021 2021 Citations: 1
Secure and Lightweight User Authentication Technique for IoT Devices MS Rao, YS Kumari, HP Chandika Algorithms for Intelligent Systems, 497-510 , 2021 2021 Citations: 1
Machine Learning based diagnosis of Diabetic Retinopathy using digital Fundus images with CLAHE along FPGA Methodology RSS Yallanti Sowjanya Kumari, Mekala Srinivasa Rao International Journal of Advanced Science and Technology 29 (5), 12748-12759 , 2020 2020
MOST CITED SCHOLAR PUBLICATIONS
Fog‐Sec: Secure end‐to‐end communication in fog‐enabled IoT network using permissioned blockchain system ES Babu, MS Rao, G Swain, AK Nikhath, R Kaluri International Journal of Network Management 33 (5), e2248 , 2023 2023 Citations: 24
Verifiable Authentication and Issuance of Academic Certificates Using Permissioned Blockchain Network ES Babu, BKN Srinivasarao, I Kavati, MS Rao International Journal of Information Security and Privacy (IJISP) 16 (1), 1-24 , 2022 2022 Citations: 24
Ant cat swarm optimization-enabled deep recurrent neural network for big data classification based on map reduce framework S Narayana, SB Chandanapalli, MS Rao, K Srinivas The Computer Journal 65 (12), 3167-3180 , 2022 2022 Citations: 15
Smart Agriculture: Automated Controlled Monitoring System using Internet of Things IK Mekala Srinivasa Rao, Erukala Suresh Babu, P. Siva Naga Raju International Journal of Recent Technology and Engineering 8 (3), 8778-8784 , 2019 2019 Citations: 14
Texture classification based on first order local ternary direction patterns MS Rao, VV Kumar, MK Prasad International Journal of Image, Graphics and Signal Processing 9 (2), 46 , 2017 2017 Citations: 14
Automatic Music Genre Classification Based on Linguistic Frequencies Using Machine Learning MS Rao, OP Kalyan, NN Kumar, MT Tabassum, B Srihari International Conference on Recent Advances in Mathematics and Informatics … , 2021 2021 Citations: 11
A Hybrid Intrusion Detection System against Botnet Attack in IoT using Light Weight Signature and Ensemble Learning Technique ES Babu, MS Rao, R Pemula, SR Nayak, A Shankar 2022 Citations: 6
Analysis of Hybrid Fusion-Neural Filter Approach to detect Brain Tumor ST R. SwamySirisati, M. S. Rao 2020 Sixth International Conference on Parallel, Distributed and Grid … , 2020 2020 Citations: 6
Implementation of Service Based Chatbot Using Deep Learning SF Mekala Srinivasa Rao, Maddineni Mounika TEST Engineering & Management 83, 2013-2019 , 2020 2020 Citations: 5
Texture Classification based on Local Features Using Dual Neighborhood Approach MS Rao, VV Kumar, MHM KrishnaPrasad International Journal of Image, Graphics and Signal Processing 9 (9), 59 , 2017 2017 Citations: 5
Texture Classification Based On Statistical Properties Of Local Units MS Rao, VV Kumar, MHMK Prasad Journal of Theoretical and Applied Information Technology 93 (2), 246 , 2016 2016 Citations: 4
SCS: A Secure Cloud Storage Framework with Enhanced Integrity and Auditability Using Consortium Blockchain System AA Devi, ES Babu, MS Rao, R Kaluri, TR Gadekallu 2024 IEEE International Conference on Smart Internet of Things (SmartIoT), 79-86 , 2024 2024 Citations: 3
An Optimized Fuzzy-Based Resource Allocation for Cloud Using Secured Tabu Search Technique C Srinivasa Kumar, RS Sirisati, M Srinivasa Rao, MV Narayana, ... Innovations in Computer Science and Engineering: Proceedings of the Ninth … , 2022 2022 Citations: 3
A Hybrid Clinical Data Predication Approach Using Modified PSO PSV Srinivasa Rao, MS Rao, RS Sirisati Smart Computing Techniques and Applications: Proceedings of the Fourth … , 2021 2021 Citations: 3
Secure exchange and effectual verification of educational academic records using hyperledger fabric block chain system ES Babu, MS Rao, S Naganjaneyulu, MSS Sai, RK Ganiya International Journal of Ad Hoc and Ubiquitous Computing 40 (1/2/3), 194-213 , 2022 2022 Citations: 2
Change detection of pulmonary embolism using isomeric cluster and computer vision AK Rao, M.S., Kumar, S.V., Pemula, R., Prathipati IAES International Journal of Artificial Intelligence 11 (2), 787-798 , 2022 2022 Citations: 2
Online Toll Gate Payment System using RFID &IoT AC Suresh, MS Rao, DV Sridhar, GS Annapurna International Journal of Recent Technology and Engineering (IJRTE) 8 (4 … , 2019 2019 Citations: 2
Implementation and Performance Evaluation of CoAP Data Protocol of Internet of Things MSR Y.Naga Malleswara Rao International Journal of Advanced Engineering and Global Technology 5 (5 … , 2017 2017 Citations: 2
Collaborative Attack Effect Against Table-Driven Routing Protocols for WANETs: A Performance Analysis E Suresh Babu, S Naganjaneyulu, PSVS Rao, MS Rao Computer Communication, Networking and Internet Security: Proceedings of … , 2017 2017 Citations: 2
An Analytical Hierarchy Process Investigation on High Speed Data Implementations Using Big Data Y Garapati, GC Babu, KVM Mohan, MS Rao, J Kavitha 2022 International Conference on Computer Communication and Informatics … , 2022 2022 Citations: 1
