Accuracy and Efficiency Trade-Offs in LLM-Based Malware Detection and Explanation: A Comparative Study of Parameter Tuning Vs. Full Fine-Tuning

This study examines whether Low-Rank Adaptation LoRA fine-tuned Large Language Models LLMs can approximate the performance of fully fine-tuned models in generating human-interpretable decisions and explanations for malware classification. Achieving trustworthy malware detection, particularly when...

Small Language Models for Phishing Website Detection: Cost, Performance, and Privacy Trade-Offs

Phishing websites pose a major cybersecurity threat, exploiting unsuspecting users and causing significant financial and organisational harm. Traditional machine learning approaches for phishing detection often require extensive feature engineering, continuous retraining, and costly infrastructur...

Efficient Adversarial Malware Defense Via Trust-Based Raw Override and Confidence-Adaptive Bit-Depth Reduction

The deployment of robust malware detection systems in big data environments requires careful consideration of both security effectiveness and computational efficiency. While recent advances in adversarial defenses have demonstrated strong robustness improvements, they often introduce computationa...

Offensive Tool Determination Strategy R.I.D.D.L.E. + (C)

Intentional threats are a major risk factor related to vulnerabilities in critical infrastructure assets, and an accurate risk assessment is necessary to analyze threats, assess vulnerabilities, and evaluate potential impacts on assets and systems. This research proposes a methodology that can be...

Incentive Attacks in BTC: Short-Term Revenue Changes and Long-Term Efficiencies

Bitcoin's BTC Difficulty Adjustment Algorithm DAA has been a source of vulnerability for incentive attacks such as selfish mining, block withholding and coin hopping strategies. In this paper, first, we rigorously study the short-term revenue change per hashpower of the adversarial and honest...

Intel Thread Director Visualizer 安全漏洞

Intel Thread Director Visualizer is a desktop application from Intel Corporation USA. It helps end-users visualize CPU utilization and the distribution between P-cores performance cores and E-cores energy-efficient cores for Alder Lake and above platforms. A security vulnerability exists in Intel...

Quantum Semantic Communication beyond the Shannon-Wyner Channel Capacity

Quantum Secure Direct Communication QSDC, a paradigm-shifting breakthrough in quantum communication, exploits quantum states for unmediated information transmission. Rooted in the inviolable fundamental laws of quantum mechanics, QSDC enables ultrasensitive detection of even the faintest...

Secure Low-Altitude Maritime Communications Via Intelligent Jamming

Low-altitude wireless networks LAWNs have emerged as a viable solution for maritime communications. In these maritime LAWNs, unmanned aerial vehicles UAVs serve as practical low-altitude platforms for wireless communications due to their flexibility and ease of deployment. However, the open and...

MGASA-2025-0264 Updated gstreamer1.0-plugins-bad packages fix security vulnerability

GStreamer H265 Codec Parsing Stack-based Buffer Overflow Remote Code Execution Vulnerability. CVE-2025-3887...

6 Reasons Occupancy Monitoring Is Key for Energy Efficiency

Today, with the world more conscious than ever about the conservation of energy, efficiency becomes even more critical.…...

[SECURITY] Fedora 41 Update: rust-astral-tokio-tar-0.5.6-1.fc41

A Rust implementation of an async TAR file reader and writer. This library does not currently handle compression, but it is abstract over all I/O readers and writers. Additionally, great lengths are taken to ensure that the entire contents are never required to be entirely resident in memory all ...

Android Malware Detection: A Machine Learning Approach

This study examines machine learning techniques like Decision Trees, Support Vector Machines, Logistic Regression, Neural Networks, and ensemble methods to detect Android malware. The study evaluates these models on a dataset of Android applications and analyzes their accuracy, efficiency, and...

An Efficient Anomaly Detection Framework for Wireless Sensor Networks Using Markov Process

Wireless Sensor Networks forms the backbone of modern cyber physical systems used in various applications such as environmental monitoring, healthcare monitoring, industrial automation, and smart infrastructure. Ensuring the reliability of data collected through these networks is essential as the...

You asked, we delivered: Introducing new features for an improved security experience

At the Microsoft Security Response Center MSRC, your feedback drives our innovation. Every enhancement we deliver starts with listening to the security community and our customers. Based on your input, we’ve introduced three new features designed to make your experience more efficient, transparen...

[SECURITY] Fedora 43 Update: mirrorlist-server-3.0.8-1.fc43

The mirrorlist-server uses the data created by MirrorManager2 https://github.com/fedora-infra/mirrormanager2 to answer client request for the "best" mirror. This implementation of the mirrorlist-server is written in Rust. The original version of the mirrorlist-server was part of the MirrorManager...

EUVD-2008-5308

Malware in sbrugna...

EUVD-2021-2382

Malware in sbrugna...

OptiFLIDS: Optimized Federated Learning for Energy-Efficient Intrusion Detection in IoT

In critical IoT environments, such as smart homes and industrial systems, effective Intrusion Detection Systems IDS are essential for ensuring security. However, developing robust IDS solutions remains a significant challenge. Traditional machine learning-based IDS models typically require large...

EUVD-2025-15915

Malicious code in bioql PyPI...

EUVD-2025-14942

Malicious code in bioql PyPI...