siva krishnaiah chintha

@aitsrajampetpgcs.ac.in

Assistant Professor, MCA department
Annamacharya PG College of Computer Studies,Rajampet

siva krishnaiah chintha


               Download Compact PDF  
https://researchid.co/sivacmca

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Networks and Communications, Computer Science Applications, Computer Science
6

Scopus Publications

15

Scholar Citations

2

Scholar h-index

Scopus Publications

  • Feature-Optimised Gradient Boosting for Accurate and Efficient Network Intrusion Detection
    M Hari Haranadha Sastry, M Sharwani, Ch Ram Mohan, C Siva Krishnaiah, Venkata Ramana N, R Kiran Kumar
    Proceedings of 3rd International Conference on Machine Learning and Autonomous Systems Icmlas 2026, 2026
  • Design and Implementation of an IoT-based Emergency Alert and GPS Tracking System using MQTT and GSM/GPS Module
    P. Chinnasamy, Pranavdev P. S, Chintha Sivakrishnaiah, T. Sathiya, Irfan Alam, Divya Priya Degala
    Proceedings of 5th International Conference on Trends in Material Science and Inventive Materials Ictmim 2025, 2025
    An optimally optimized emergency response system can prove to be lifesaving by reducing response time during the state of emergency. This paper proposes an IoT-based emergency alert and GPS tracking system implemented on an ESP32 microcontroller and an A9G GSM/GPS module. The system has a continuous log of user position and device battery level and pushes data in intervals through MQTT to the Adafruit IO platform for remote monitoring. To achieve best battery life, the A9G module goes into low power mode in idle mode but keeps GPS monitoring running. One more feature highlighted is the SOS button, which makes an emergency call by sending the user's location as an SMS and calling a pre-configured contact number. The system also maintains data integrity with automatic reconnect of MQTT broker when it loses connection. Low power and battery portable, the system is applicable in personal protection, home health care for elderly, outdoor adventure, and remote area surveillance. The article explains hardware design, software process, MQTT-based data communication, and testing of the performance of the system based on precision, network, and response to emergencies. The results verify reliability and cost saving of the system in real-time monitoring and reporting of emergencies. With its energy-saving and usability design, it helps in the development of IoT-backed safety solutions for real-time tracking and emergency response in case of a need.
  • Advanced Video Anomaly Detection with Enhanced Feature Learning using Deep Convolutional Neural Nets and Context Mining Approach
    A Ranjith Kumar, V S N Murthy, V D S Krishna, Chintha Sivakrishnaiah, Bendalam Vijaya, U Ganesh Naidu
    Proceedings of 8th International Conference on Inventive Computation Technologies Icict 2025, 2025
    The increasing deployment of CCTV surveillance systems necessitates intelligent anomaly detection for identifying unauthorized actions such as shoplifting, sudden sprints, and unusual object appearances. Traditional techniques rely on extensive labelled datasets, leading to high computational costs and impractical real-time applications. This research introduces a novel method integrating three pretrained Convolutional Neural Network (CNN) models for tracking, object detection, and anomaly detection, ensuring highly efficient feature extraction while minimizing manual labelling and computational overhead. A Denoising Autoencoder (DAE) reconstructs expected behaviour from usual activity patterns, highlighting anomalies through red bounding boxes for enhanced interpretability. The UCSD Pedestrian Dataset (Ped1 and Ped2) serves as the evaluation benchmark, where normal pedestrian movement is distinguished from anomalies such as bicycle intrusions or abrupt object appearances. Additionally, context mining techniques extract spatial and temporal behaviour features, improving discrimination between normal and anomalous events. The proposed approach significantly reduces computational complexity while enhancing real-time detection, achieving an accuracy of 96.4 %, an F1-score of 92.9 %, and an AUC-ROC of 97.1 %, with a processing rate of 32 FPS, ensuring scalability in large-scale surveillance environments. Future work will explore action recognition and key point detection to refine human behaviour characterization and extend applicability across diverse video datasets to further strengthen robustness and real-world implementation.
  • Managing Network Security in IT Sector using the Suricata
    P. Chinnasamy, Chintha SivaKrishnaiah, Thuvva Anjali, Anuradha Kambalapelly, P. Varaprasada Rao, Divya Priya Degala
    Proceedings 3rd International Conference on Self Sustainable Artificial Intelligence Systems Icssas 2025, 2025
    In the current era of digitalization, network security is a top priority for organizations, especially in the IT industry, where cyber-attacks are ever-changing. Intrusion Detection and Prevention Systems (IDPS) are a key component in protecting networks from malicious behavior. Suricata, a sophisticated open-source IDPS, has become an effective solution because of its high-performance feature, deep packet inspection, and real-time traffic analysis. This essay discusses Suricata's role in maintaining network security in the IT industry, highlighting its efficiency in the detection, prevention, and mitigation of cyber threats. The article starts by mentioning the basic challenges for IT businesses in protecting their networks, including zero-day exploits, advanced persistent threats (APTs), and distributed denial-of-service (DDoS) attacks. Conventional security solutions usually are not effective in managing a large amount of network traffic at once, causing the detection of threats to be delayed and respond to them late. Suricata overcomes such challenges through multi-threading, deep packet inspection, and protocol parsing for anomaly detection with high accuracy. One of the most important features of this research is the deployment of Suricata in an enterprise network environment. The research offers a detailed explanation of Suricata's rule-based detection engine, signature- based threat detection, and integration with security information and event management (SIEM) systems. It also discusses the effectiveness of Suricata compared to other IDPS solutions, including Snort and Zeek, and its strengths in scalability and performance.
  • Dynamic queue management for optimized QoS in manets
    International Journal of Scientific and Technology Research, 2019
  • On control aspects of quality of service in mobile ad hoc networks
    C. Siva Krishnaiah, A. Subramanyam
    Lecture Notes in Electrical Engineering, 2019

RECENT SCHOLAR PUBLICATIONS

  • Feature-Optimised Gradient Boosting for Accurate and Efficient Network Intrusion Detection
    MHH Sastry, M Sharwani, CR Mohan, CS Krishnaiah, RK Kumar
    2026 International Conference on Machine Learning and Autonomous Systems … , 2026
    2026.0
  • Managing network security in IT sector using the suricata
    P Chinnasamy, C SivaKrishnaiah, T Anjali, A Kambalapelly, PV Rao, ...
    2025 3rd International Conference on Self Sustainable Artificial … , 2025
    2025.0
    Citations: 6
  • Advanced Video Anomaly Detection with Enhanced Feature Learning Using Deep Convolutional Neural Nets and Context Mining Approach
    AR Kumar, VSN Murthy, VDS Krishna, C Sivakrishnaiah, B Vijaya, ...
    2025 International Conference on Inventive Computation Technologies (ICICT … , 2025
    2025.0
  • Design and Implementation of an IoT-based Emergency Alert and GPS Tracking System using MQTT and GSM/GPS Module
    P Chinnasamy, C Sivakrishnaiah, T Sathiya, I Alam, DP Degala
    2025 5th International Conference on Trends in Material Science and … , 2025
    2025.0
    Citations: 7
  • REVOCATION AUTHORITY BASED SECURE CLOUD SERVICES
    P ChittiBabu, C SivaKrishnaiah, V Akhila
    DOI:18.0002.IJAEMA.2020.V12I3.200001.0156360 12 (4), 540-543 , 2020
    2020.0
  • Dynamic Queue Management For Optimized Qos In Manets
    DTH C.Siva Krishnaiah,Dr. N.Geethanjali
    International Journal of Scientific & Technology Research(issn 2277-8616) 8 … , 2019
    2019.0
  • AN ENHANCED AD HOC ON-DEMAND DISTANCE VECTOR ROUTING PROTOCOL FOR MANET’S
    DTH C.Siva Krishnaiah, Prof.N.Geethanjali
    Journal of Emerging Technologies and Innovative Research 6 (5), 352-357 , 2019
    2019.0
  • On Control Aspects of Quality of Service
    S Krishnaiah C, A Subramanyam
    Proceedings of the International Conference on Communications and Cyber … , 2018
    2018.0
  • Subramanyam (2017) Framework on quality of service in mobile ad hoc networks
    C Siva Krishnaiah
    International Journal of Advanced Scientific Technologies in Engineering and … , 2017
    2017.0
    Citations: 2
  • FDM SORT: An External and Distributed Sorting
    PCB Chintha Siva Krishnaiah
    International Journal of Emerging Trends & Technology in Computer Science … , 2016
    2016.0
  • Cluster-Based Routing Protocol for Delay-Tolerant Mobile Networks
    CSK T.Harikrishna, Dr.A.Subramanyam
    National Conference on Recent Trends in Information Technology (NCRTIT'13), 7-11 , 2013
    2013.0
  • EFFICIENT DATA TRACKING FOR SECURE CLOUD STORAGE
    P ChittiBabu, C SivaKrishnaiah, K Supraja
  • Profit Optimization for Cloud Service Provider through Service Mechanism
    PC Babu, VV Kumar, CS Krishnaiah

MOST CITED SCHOLAR PUBLICATIONS

  • Design and Implementation of an IoT-based Emergency Alert and GPS Tracking System using MQTT and GSM/GPS Module
    P Chinnasamy, C Sivakrishnaiah, T Sathiya, I Alam, DP Degala
    2025 5th International Conference on Trends in Material Science and … , 2025
    2025.0
    Citations: 7
  • Managing network security in IT sector using the suricata
    P Chinnasamy, C SivaKrishnaiah, T Anjali, A Kambalapelly, PV Rao, ...
    2025 3rd International Conference on Self Sustainable Artificial … , 2025
    2025.0
    Citations: 6
  • Subramanyam (2017) Framework on quality of service in mobile ad hoc networks
    C Siva Krishnaiah
    International Journal of Advanced Scientific Technologies in Engineering and … , 2017
    2017.0
    Citations: 2
  • Feature-Optimised Gradient Boosting for Accurate and Efficient Network Intrusion Detection
    MHH Sastry, M Sharwani, CR Mohan, CS Krishnaiah, RK Kumar
    2026 International Conference on Machine Learning and Autonomous Systems … , 2026
    2026.0
  • Advanced Video Anomaly Detection with Enhanced Feature Learning Using Deep Convolutional Neural Nets and Context Mining Approach
    AR Kumar, VSN Murthy, VDS Krishna, C Sivakrishnaiah, B Vijaya, ...
    2025 International Conference on Inventive Computation Technologies (ICICT … , 2025
    2025.0
  • REVOCATION AUTHORITY BASED SECURE CLOUD SERVICES
    P ChittiBabu, C SivaKrishnaiah, V Akhila
    DOI:18.0002.IJAEMA.2020.V12I3.200001.0156360 12 (4), 540-543 , 2020
    2020.0
  • Dynamic Queue Management For Optimized Qos In Manets
    DTH C.Siva Krishnaiah,Dr. N.Geethanjali
    International Journal of Scientific & Technology Research(issn 2277-8616) 8 … , 2019
    2019.0
  • AN ENHANCED AD HOC ON-DEMAND DISTANCE VECTOR ROUTING PROTOCOL FOR MANET’S
    DTH C.Siva Krishnaiah, Prof.N.Geethanjali
    Journal of Emerging Technologies and Innovative Research 6 (5), 352-357 , 2019
    2019.0
  • On Control Aspects of Quality of Service
    S Krishnaiah C, A Subramanyam
    Proceedings of the International Conference on Communications and Cyber … , 2018
    2018.0
  • FDM SORT: An External and Distributed Sorting
    PCB Chintha Siva Krishnaiah
    International Journal of Emerging Trends & Technology in Computer Science … , 2016
    2016.0
  • Cluster-Based Routing Protocol for Delay-Tolerant Mobile Networks
    CSK T.Harikrishna, Dr.A.Subramanyam
    National Conference on Recent Trends in Information Technology (NCRTIT'13), 7-11 , 2013
    2013.0
  • EFFICIENT DATA TRACKING FOR SECURE CLOUD STORAGE
    P ChittiBabu, C SivaKrishnaiah, K Supraja
  • Profit Optimization for Cloud Service Provider through Service Mechanism
    PC Babu, VV Kumar, CS Krishnaiah