Denial of service attacks - Strategic Insights Report

Cyberterrorism

Global Polynomial Pinning Synchronization of Coupled Reaction-diffusion Inertial Neural Networks via Dual Event Triggered Markov-switched Control

Researchers at Nazarbayev University have made a significant breakthrough in the field of information and data encoding and encryption. The team, led by Dr. Ardak Kashkynbayev, has developed a novel method for achieving global polynomial pinning synchronization (GPPS) in coupled reaction-diffusion inertial neural networks (CRDINNs) with proportional delays. This method,

Denial of service attacks

Federated Learning with Adaptive Client Selection Improves DDoS Attack Detection in IoT Environments

Researchers from the University of Milan have developed a new approach to detecting distributed denial-of-service (DDoS) attacks in Internet of Things (IoT) environments using federated learning with adaptive client selection. This method addresses the challenges of traditional centralized machine learning methods, which raise privacy and security concerns due to data

Cyberterrorism

Philippine National Police Enhances Cybersecurity Measures Amid Potential DDoS Attacks

The Philippine National Police (PNP) is taking proactive measures to secure its online platforms from Distributed Denial of Service (DDoS) attacks. According to PNP acting chief Lt. Gen. Jose Melencio Nartatez Jr., various units are working with the Department of Information and Communications Technology (DICT) to strengthen firewalls and integrity

Cyberterrorism

Enhancing Security for Upcoming 6G-Ready Smart Grids through Federated Learning and Cloud Solutions

The modern power grid's dependence on constant communication between smart meters, gateways, and control centers makes it vulnerable to distributed denial-of-service (DDoS) attacks. As 6G networks approach, researchers at the Singapore University of Technology and Design (SUTD) have explored a solution to detect DDoS attacks early and at

Cyberterrorism

Enhancing SDN Security with Deep Learning and F-Balanced Cross-Entropy for DDoS Detection

Research has shown that Software-Defined Networking (SDN) offers centralized control and programmability, but also introduces vulnerabilities, particularly to Distributed Denial of Service (DDoS) attacks. Traditional DDoS detection methods often fall short in SDN due to high false-positive rates and limited adaptability to evolving network traffic. A novel Deep Neural Network

Elsevier Science Inc.

Finite-Time Consensus of Nonlinear Multi-Agent Systems with Intermittent DoS Attacks

Researchers from the Nanjing University of Science and Technology have made significant progress in addressing the finite-time consensus problem of nonlinear multi-agent systems (MASs) with intermittent denial-of-service (DoS) attacks. The study presents a novel finite-time stability standard for intermittent control systems, utilizing the piecewise Lyapunov function approach to derive sufficient

Cyberterrorism

Novel Approach to Integral Sliding Mode Leader-Following Consensus Tracking Control for Nonlinear Multi-Agent Systems

A team of researchers at Qiqihar University has proposed a novel approach to integral sliding mode leader-following consensus tracking control for nonlinear multi-agent systems with homogeneous dynamics under hybrid cyber attacks. The significance of this work lies in its ability to enhance system resilience in adversarial environments while optimizing resource

Cyberterrorism

Secure Intermittent Impulsive Synchronization Control for Multi-Agent Systems

Researchers from Chongqing University of Posts and Telecommunications have published a new study on the secure intermittent impulsive synchronization control protocol for leader-following multi-agent systems (LF-MASs) in the presence of sensor delays and cyber attacks. This novel protocol is designed to tackle the challenging problem of mean-square bounded synchronization in

Denial of service attacks

Record-Scale DDoS Attack Detected by FastNetMon

FastNetMon, a leading solution for network security, has detected a record-scale distributed denial-of-service (DDoS) attack targeting the website of a major DDoS scrubbing vendor in Western Europe. The attack reached a staggering 1.5 billion packets per second (1.5 Gbps), making it one of the largest packet-rate floods publicly

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Global Polynomial Pinning Synchronization of Coupled Reaction-diffusion Inertial Neural Networks via Dual Event Triggered Markov-switched Control

Cloud Computing Security Threats: New Research on Deep Reinforcement Learning for DDoS Detection

Federated Learning with Adaptive Client Selection Improves DDoS Attack Detection in IoT Environments

Cloud Computing Security Threats: New Research on Deep Reinforcement Learning for DDoS Detection

Cloud Computing Security Threats: New Research on Deep Reinforcement Learning for DDoS Detection

Philippine National Police Enhances Cybersecurity Measures Amid Potential DDoS Attacks

Enhancing Security for Upcoming 6G-Ready Smart Grids through Federated Learning and Cloud Solutions

Enhancing SDN Security with Deep Learning and F-Balanced Cross-Entropy for DDoS Detection

Finite-Time Consensus of Nonlinear Multi-Agent Systems with Intermittent DoS Attacks

Novel Approach to Integral Sliding Mode Leader-Following Consensus Tracking Control for Nonlinear Multi-Agent Systems

Secure Intermittent Impulsive Synchronization Control for Multi-Agent Systems

Record-Scale DDoS Attack Detected by FastNetMon