Self-Supervised Transformer-Based Contrastive Learning for Intrusion Detection Systems

As the digital landscape becomes more interconnected, the frequency and severity of zero-day attacks, have significantly increased, leading to an urgent need for innovative Intrusion Detection Systems IDS. Machine Learning-based IDS that learn from the network traffic characteristics and can...

Self-Supervised Federated GNSS Spoofing Detection with Opportunistic Data

Global navigation satellite systems GNSS are vulnerable to spoofing attacks, with adversarial signals manipulating the location or time information of receivers, potentially causing severe disruptions. The task of discerning the spoofing signals from benign ones is naturally relevant for machine...

Engineering Risk-Aware, Security-By-Design Frameworks for Assurance of Large-Scale Autonomous AI Models

As AI models scale to billions of parameters and operate with increasing autonomy, ensuring their safe, reliable operation demands engineering-grade security and assurance frameworks. This paper presents an enterprise-level, risk-aware, security-by-design approach for large-scale autonomous AI...

QUIC-Exfil: Exploiting QUIC'S Server Preferred Address Feature to Perform Data Exfiltration Attacks

The QUIC protocol is now widely adopted by major tech companies and accounts for a significant fraction of today's Internet traffic. QUIC's multiplexing capabilities, encrypted headers, dynamic IP address changes, and encrypted parameter negotiations make the protocol not only more efficient,...

Device Presence Anomaly Detected (High)

It is important to know what assets exist in your network. New assets can indicate unexpected network connections, third-party connectivity, or potential threats to the network. This plugin only works with Tenable.ot. Please visit https://www.tenable.com/products/tenable-ot for more information...

Secure Cluster-Based Hierarchical Federated Learning in Vehicular Networks

Hierarchical Federated Learning HFL has recently emerged as a promising solution for intelligent decision-making in vehicular networks, helping to address challenges such as limited communication resources, high vehicle mobility, and data heterogeneity. However, HFL remains vulnerable to...

Analysis of the Vulnerability of Machine Learning Regression Models to Adversarial Attacks Using Data from 5G Wireless Networks

This article describes the process of creating a script and conducting an analytical study of a dataset using the DeepMIMO emulator. An advertorial attack was carried out using the FGSM method to maximize the gradient. A comparison is made of the effectiveness of binary classifiers in the task of...

AI-Driven IRM: Transforming Insider Risk Management with Adaptive Scoring and LLM-Based Threat Detection

Insider threats pose a significant challenge to organizational security, often evading traditional rule-based detection systems due to their subtlety and contextual nature. This paper presents an AI-powered Insider Risk Management IRM system that integrates behavioral analytics, dynamic risk...

GiBy: a Giant-Step Baby-Step Classifier for Anomaly Detection in Industrial Control Systems

The continuous monitoring of the interactions between cyber-physical components of any industrial control system ICS is required to secure automation of the system controls, and to guarantee plant processes are fail-safe and remain in an acceptably safe state. Safety is achieved by managing...

Cybersecurity for Autonomous Vehicles

The increasing adoption of autonomous vehicles is bringing a major shift in the automotive industry. However, as these vehicles become more connected, cybersecurity threats have emerged as a serious concern. Protecting the security and integrity of autonomous systems is essential to prevent...

The Dark Side of Digital Twins: Adversarial Attacks on AI-Driven Water Forecasting

Digital twins DTs are improving water distribution systems by using real-time data, analytics, and prediction models to optimize operations. This paper presents a DT platform designed for a Spanish water supply network, utilizing Long Short-Term Memory LSTM networks to predict water consumption...

Quantum Autoencoder for Multivariate Time Series Anomaly Detection

Anomaly Detection AD defines the task of identifying observations or events that deviate from typical - or normal - patterns, a critical capability in IT security for recognizing incidents such as system misconfigurations, malware infections, or cyberattacks. In enterprise environments like SAP...

Blockchain Meets Adaptive Honeypots: a Trust-Aware Approach to Next-Gen IoT Security

Edge computing-based Next-Generation Wireless Networks NGWN-IoT offer enhanced bandwidth capacity for large-scale service provisioning but remain vulnerable to evolving cyber threats. Existing intrusion detection and prevention methods provide limited security as adversaries continually adapt the...

Detecting Zero-Day Web Attacks with an Ensemble of LSTM, GRU, and Stacked Autoencoders

The rapid growth in web-based services has significantly increased security risks related to user information, as web-based attacks become increasingly sophisticated and prevalent. Traditional security methods frequently struggle to detect previously unknown zero-day web attacks, putting sensitiv...

The vulnerability of the biometric authentication function in Windows Hello on Windows operating systems allows attackers to perform spoofing attacks.

The vulnerability of the biometric authentication function in Windows Hello on Windows operating systems is related to insufficient detection or processing of adversarial input anomalies. Exploiting this vulnerability can allow attackers to perform spoofing attacks...

The vulnerability of the Citrix NetScaler Application Delivery Controller (previously Citrix ADC) and the Citrix NetScaler Gateway (previously Citrix Gateway) access control systems, related to behavior anomaly detection, allows attackers to gain unauthorized access to limited functions.

The vulnerability of the Citrix NetScaler Application Delivery Controller previously Citrix ADC and the Citrix NetScaler Gateway previously Citrix Gateway access control system is related to the violation of expected behavior. Exploiting this vulnerability can allow an attacker, operating remotel...

NHIs Are the Future of Cybersecurity: Meet NHIDR

The frequency and sophistication of modern cyberattacks are surging, making it increasingly challenging for organizations to protect sensitive data and critical infrastructure. When attackers compromise a non-human identity NHI, they can swiftly exploit it to move laterally across systems,...

How AI Is Transforming IAM and Identity Security

In recent years, artificial intelligence AI has begun revolutionizing Identity Access Management IAM, reshaping how cybersecurity is approached in this crucial field. Leveraging AI in IAM is about tapping into its analytical capabilities to monitor access patterns and identify anomalies that coul...

Context is King: Using API Sessions for Security Context

There’s no doubt that API security is a hot topic these days. The continued growth in API-related breaches and increase in publicized API vulnerabilities has pushed API security to the top of CISO’s lists. The tools in the market for API security still have room for improvement, of course. One of...

Understanding the Initial Stages of Web Shell and VPN Threats: An MXDR Analysis

While cyberattacks that employ web shells and VPN compromise are not particularly novel, they are still prevalent. The recent incidents that Trend Micro MXDR analyzed highlight the importance of behavioral analysis and anomaly detection in security measures...