Rohith Vegensa: Cybersecurity In Fueling Systems-Protecting Transactions And Preventing Fraud

Rohith Vegesna is a software engineer specializing in secure, cloud-connected fueling systems, with a strong focus on IoT, real-time monitoring, and cybersecurity.
Devdiscourse

AI moves to the core of cyber defense as attacks grow more complex

Intrusion detection systems, long constrained by high false-positive rates and limited adaptability, are being re-engineered ...
Coordinated Science Laboratory

Researchers awarded NSF grant to improve firewalls, antivirus software while preserving personal data

Assistant Professor Yupeng Zhang and his team, along with researchers from the University of California, Irvine, received a ...
Opinion
Que.com on MSNOpinion

Enhancing AI security: Why traditional cybersecurity measures fall short

As the digital landscape evolves, the deployment of artificial intelligence (AI) systems has surged across various industries. These AI systems ...
Beebom

AI vs Machine Learning: What is the Difference?

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...
Scientific Research Publishing

Liu, H. and Lang, B. (2019) Machine Learning and Deep Learning Methods for Intrusion Detection Systems: A Survey. Applied Sciences, 9, Article 4396.

ABSTRACT: The research aim is to develop an intelligent agent for cybersecurity systems capable of detecting abnormal user behavior using deep learning methods and ensuring interpretability of ...
Scientific Research Publishing

Sharma, A., Sahay, R. and Gupta, M. (2020) Deep Learning-Based Intrusion Detection Systems: A Comparative Analysis. Computers & Security, 97, Article 101857.

ABSTRACT: The accelerating sophistication of cyberattacks poses unprecedented challenges for national security, critical infrastructures, and global digital resilience. Traditional signature-based ...
IEEE

Machine learning-based intrusion detection and prevention using cross-layer features in Internet of Things (IoT) networks

Abstract: The IoT has emerged as a significant target for cyber-attacks, particularly with a focus on the routing protocol for low-power and lossy networks (RPL) within Wireless Sensor Networks (WSNs) ...
IEEE

Intrusion Detection System for Digital Substations using Semi-Supervised Learning and Traffic Distance Similarity Clustering

Abstract: Cyber attacks on power grids are imminent and potentially have a severe impact, as evidenced by the cyber attacks in Ukraine in 2015, 2016, and 2022. In response to this challenge, machine ...