A Collaborative Intrusion Detection System Using Snort IDS Nodes

Intrusion Detection Systems IDSs are integral to safeguarding networks by detecting and responding to threats from malicious traffic or compromised devices. However, standalone IDS deployments often fall short when addressing the increasing complexity and scale of modern cyberattacks. This paper...

Snorkeling in Dark Waters: a Longitudinal Surface Exploration of Unique Tor Hidden Services (Extended Version)

The Onion Router Tor is a controversial network whose utility is constantly under scrutiny. On the one hand, it allows for anonymous interaction and cooperation of users seeking untraceable navigation on the Internet. This freedom also attracts criminals who aim to thwart law enforcement...

Private Federated Learning Using Preference-Optimized Synthetic Data

In practical settings, differentially private Federated learning DP-FL is the dominant method for training models from private, on-device client data. Recent work has suggested that DP-FL may be enhanced or outperformed by methods that use DP synthetic data Wu et al., 2024; Hou et al., 2024. The...

CVE-2025-31328

SAP Learning Solution is vulnerable to Cross-Site Request Forgery CSRF, allowing an attacker to trick authenticated user into sending unintended requests to the server. GET-based OData function is named in a way that it violates the expected behaviour. This issue could impact both the...

CVE-2025-31328 Cross-Site Request Forgery (CSRF) vulnerability in SAP S/4 HANA (Learning Solution)

SAP Learning Solution is vulnerable to Cross-Site Request Forgery CSRF, allowing an attacker to trick authenticated user into sending unintended requests to the server. GET-based OData function is named in a way that it violates the expected behaviour. This issue could impact both the...

PT-2025-17589 · Sap · Sap Learning Solution

Name of the Vulnerable Software and Affected Versions: SAP Learning Solution affected versions not specified Description: The issue allows an attacker to trick an authenticated user into sending unintended requests to the server through Cross-Site Request Forgery CSRF. A GET-based OData function ...

How Private Is Your Attention? Bridging Privacy with In-Context Learning

In-context learning ICL-the ability of transformer-based models to perform new tasks from examples provided at inference time-has emerged as a hallmark of modern language models. While recent works have investigated the mechanisms underlying ICL, its feasibility under formal privacy constraints...

SAP Learning Solution Cross-site Request Forgery Vulnerability

SAP Learning Solution is an enterprise-wide learning management system from SAP. SAP Learning Solution suffers from a cross-site request forgery vulnerability that arises from a web application that does not adequately validate that a request is coming from a trusted user. An attacker could explo...

TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification Utilizing OOD Data

Federated learning FL systems allow decentralized data-owning clients to jointly train a global model through uploading their locally trained updates to a centralized server. The property of decentralization enables adversaries to craft carefully designed backdoor updates to make the global model...

CLPSTNet: a Progressive Multi-Scale Convolutional Steganography Model Integrating Curriculum Learning

In recent years, a large number of works have introduced Convolutional Neural Networks CNNs into image steganography, which transform traditional steganography methods such as hand-crafted features and prior knowledge design into steganography methods that neural networks autonomically learn...

Intelligent Detection of Non-Essential IoT Traffic on the Home Gateway

The rapid expansion of Internet of Things IoT devices, particularly in smart home environments, has introduced considerable security and privacy concerns due to their persistent connectivity and interaction with cloud services. Despite advancements in IoT security, effective privacy measures rema...

CVE-2025-31328: Cross-Site Request Forgery (CSRF)

SAP Learning Solution is vulnerable to Cross-Site Request Forgery CSRF, allowing an attacker to trick authenticated user into sending unintended requests to the server. GET-based OData function is named in a way that it violates the expected behaviour. This issue could impact both the...

Feature Selection Via GANs (GANFS): Enhancing Machine Learning Models for DDoS Mitigation

Distributed Denial of Service DDoS attacks represent a persistent and evolving threat to modern networked systems, capable of causing large-scale service disruptions. The complexity of such attacks, often hidden within high-dimensional and redundant network traffic data, necessitates robust and...

FLARE: Feature-Based Lightweight Aggregation for Robust Evaluation of IoT Intrusion Detection

The proliferation of Internet of Things IoT devices has expanded the attack surface, necessitating efficient intrusion detection systems IDSs for network protection. This paper presents FLARE, a feature-based lightweight aggregation for robust evaluation of IoT intrusion detection to address the...

The Hardness of Learning Quantum Circuits and Its Cryptographic Applications

We show that concrete hardness assumptions about learning or cloning the output state of a random quantum circuit can be used as the foundation for secure quantum cryptography. In particular, under these assumptions we construct secure one-way state generators OWSGs, digital signature schemes,...

GIFDL: Generated Image Fluctuation Distortion Learning for Enhancing Steganographic Security

Minimum distortion steganography is currently the mainstream method for modification-based steganography. A key issue in this method is how to define steganographic distortion. With the rapid development of deep learning technology, the definition of distortion has evolved from manual design to...

Mining Characteristics of Vulnerable Smart Contracts across Lifecycle Stages

Smart contracts are the cornerstone of decentralized applications and financial protocols, which extend the application of digital currency transactions. The applications and financial protocols introduce significant security challenges, resulting in substantial economic losses. Existing solution...

SUSE CVE-2017-2644

In Moodle 3.x, XSS can occur via evidence of prior learning...

SUSE CVE-2017-2645

In Moodle 3.x, XSS can occur via attachments to evidence of prior learning...

IoT-AMLHP: Aligned Multimodal Learning of Header-Payload Representations for Resource-Efficient Malicious IoT Traffic Classification

Traffic classification is crucial for securing Internet of Things IoT networks. Deep learning-based methods can autonomously extract latent patterns from massive network traffic, demonstrating significant potential for IoT traffic classification tasks. However, the limited computational and spati...