Network intrusion detection and classification using machine learning predictions fusion,  Indonesian Journal of Electrical Engineering and Computer Science Vol. 31

AN OVERVIEW OF VARIOUS TECHNIQUES INVOLVED IN DETECTION OF ANOMALIES FROM SURVEILLANCE CAMERAS Vasanth Kumar N.T and Geetha Kiran .A Department of Computer Science & Engineering, Malnad College of Engineering, Hassan, Visvesvaraya Technological University, Belagavi - 590018, Karnataka, India vasanthkumarnt@gmail.com, geethaamk@gmail.com ABSTRACT In recent years, the use of surveillance cameras is rapidly increasing in both public and private areas to enhance the security measures. Many companies are recruiting people to monitor the activities captured by surveillance cameras and due to human error they may failed to monitor the abnormal events. So, an automated system to detect the anomalous events acts as a significant approach in surveillance applications. Due to sparse occurrence of anomalous activities, the detection of anomalies is remaining as a challenging task. To overcome these drawbacks, many researchers have worked to develop an effective anomaly detection methods using different approaches. This study prioritized some existing approaches to detect anomalies takes place in surveillance videos. The existing researches utilized University of Central Florida (UCF) Crime video dataset to collect the data about the anomalous activities, UCF crime video dataset consist of 13 categories of anomalies which consist of 1900 surveillance videos. The key parameters such as accuracy, recall, F1 score and Area Under Curve (AUC) are evaluated to analyse the efficiency of the existing anomaly detection methods. This survey acts as a tool for future researchers to overcome the drawbacks in the existing methods and create a novel anomaly detection approach. KEYWORDS Abnormal Events, Anomaly Detection, Automated System, Security, Surveillance Cameras.

N. Sushma, H. N. Suresh, J. M. Lakshmi, P. N. Srinivasu, A. K. Bhoi and P. Barsocchi, "A Unified Metering System Deployed for Water and Energy Monitoring in Smart City," in IEEE Access, vol. 11, pp. 80429-80447, 2023, doi: 10.1109/ACCESS.2023.3299825. 

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE) , Vol 10, Issue 4,  April 2023, pp- 45-48

Sunitha P a, Uma B a, Channakeshava S b, Suresh Babu C S , A fully labelled image dataset of banana leaves deficient in nutrients, Data in Brief, Volume 48, June 2023, 109155, Elsevier.

Intensity Based Headlight Management System

Kavyasri M N, Ramesh B, “Key- cipher Policy based ABE with efficient encryption of multimedia data at data centers of cloud”, International journal of Engineering Trends and Technology volume 11 issue 1 May 2022.

Malicious URL Detection Using Logistic Regression

IOT Based Food Spoilage Detector

Janardhana D R, A P Manu, Shivanna K and Suhas K C “A lightweight Blockchain to Secure Data Communication in IoT Network on Healthcare systems”, International journal of critical computer based systems. Publisher: Inderscience (Under Review).