Towards Effective Identification of Attack Techniques in Cyber Threat Intelligence Reports Using Large Language Models

This work evaluates the performance of Cyber Threat Intelligence CTI extraction methods in identifying attack techniques from threat reports available on the web using the MITRE ATT&CK framework. We analyse four configurations utilising state-of-the-art tools, including the Threat Report ATT&CK...

M-Ary Precomputation-Based Accelerated Scalar Multiplication Algorithms for Enhanced Elliptic Curve Cryptography

Whitepaper called M-Ary Precomputation-Based Accelerated Scalar Multiplication Algorithms For Enhanced Elliptic Curve Cryptography...

Rogue Cell: Adversarial Attack and Defense in Untrusted O-RAN Setup Exploiting the Traffic Steering XApp

The Open Radio Access Network O-RAN architecture is revolutionizing cellular networks with its open, multi-vendor design and AI-driven management, aiming to enhance flexibility and reduce costs. Although it has many advantages, O-RAN is not threat-free. While previous studies have mainly examined...

Capability-Based Multi-Tenant Access Management in Crowdsourced Drone Services

We propose a capability-based access control method that leverages OAuth 2.0 and Verifiable Credentials VCs to share resources in crowdsourced drone services. VCs securely encode claims about entities, offering flexibility. However, standardized protocols for VCs are lacking, limiting their...

PHSafe: Disclosure Avoidance for the 2020 Census Supplemental Demographic and Housing Characteristics File (S-DHC)

This article describes the disclosure avoidance algorithm that the U.S. Census Bureau used to protect the 2020 Census Supplemental Demographic and Housing Characteristics File S-DHC. The tabulations contain statistics of counts of U.S. persons living in certain types of households, including...

SafeTab-H: Disclosure Avoidance for the 2020 Census Detailed Demographic and Housing Characteristics File B (Detailed DHC-B)

This article describes SafeTab-H, a disclosure avoidance algorithm applied to the release of the U.S. Census Bureau's Detailed Demographic and Housing Characteristics File B Detailed DHC-B as part of the 2020 Census. The tabulations contain household statistics about household type and tenure...

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...

Attack and Defense Techniques in Large Language Models: a Survey and New Perspectives

Large Language Models LLMs have become central to numerous natural language processing tasks, but their vulnerabilities present significant security and ethical challenges. This systematic survey explores the evolving landscape of attack and defense techniques in LLMs. We classify attacks into...

RevealNet: Distributed Traffic Correlation for Attack Attribution on Programmable Networks

Network attackers have increasingly resorted to proxy chains, VPNs, and anonymity networks to conceal their activities. To tackle this issue, past research has explored the applicability of traffic correlation techniques to perform attack attribution, i.e., to identify an attacker's true network...

Can Differentially Private Fine-Tuning LLMs Protect against Privacy Attacks?

Fine-tuning large language models LLMs has become an essential strategy for adapting them to specialized tasks; however, this process introduces significant privacy challenges, as sensitive training data may be inadvertently memorized and exposed. Although differential privacy DP offers strong...

From Texts to Shields: Convergence of Large Language Models and Cybersecurity

This report explores the convergence of large language models LLMs and cybersecurity, synthesizing interdisciplinary insights from network security, artificial intelligence, formal methods, and human-centered design. It examines emerging applications of LLMs in software and network security, 5G...

Security-By-Design at the Telco Edge with OSS: Challenges and Lessons Learned

This paper presents our experience, in the context of an industrial R&D project, on securing GENIO, a platform for edge computing on Passive Optical Network PON infrastructures, and based on Open-Source Software OSS. We identify threats and related mitigations through hardening, vulnerability...

Mutual Information Minimization for Side-Channel Attack Resistance Via Optimal Noise Injection

Side-channel attacks SCAs pose a serious threat to system security by extracting secret keys through physical leakages such as power consumption, timing variations, and electromagnetic emissions. Among existing countermeasures, artificial noise injection is recognized as one of the most effective...

AI-Based Crypto Tokens: the Illusion of Decentralized AI?

The convergence of blockchain and artificial intelligence AI has led to the emergence of AI-based tokens, which are cryptographic assets designed to power decentralized AI platforms and services. This paper provides a comprehensive review of leading AI-token projects, examining their technical...

VApps: Verifiable Applications at Internet Scale

Blockchain technology promises a decentralized, trustless, and interoperable infrastructure. However, widespread adoption remains hindered by issues such as limited scalability, high transaction costs, and the complexity of maintaining coherent verification logic across different blockchain layer...

Data Encryption Battlefield: a Deep Dive into the Dynamic Confrontations in Ransomware Attacks

In the rapidly evolving landscape of cybersecurity threats, ransomware represents a significant challenge. Attackers increasingly employ sophisticated encryption methods, such as entropy reduction through Base64 encoding, and partial or intermittent encryption to evade traditional detection...

Phishing URL Detection Using Bi-LSTM

Phishing attacks threaten online users, often leading to data breaches, financial losses, and identity theft. Traditional phishing detection systems struggle with high false positive rates and are usually limited by the types of attacks they can identify. This paper proposes a deep learning-based...

Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report

As transformer-based large language models LLMs increasingly permeate society, they have revolutionized domains such as software engineering, creative writing, and digital arts. However, their adoption in cybersecurity remains limited due to challenges like scarcity of specialized training data a...

Security Vulnerabilities in Quantum Cloud Systems: a Survey on Emerging Threats

Quantum computing is becoming increasingly widespread due to the potential and capabilities to solve complex problems beyond the scope of classical computers. As Quantum Cloud services are adopted by businesses and research groups, they allow for greater progress and application in many fields...

Performance of Machine Learning Classifiers for Anomaly Detection in Cyber Security Applications

This work empirically evaluates machine learning models on two imbalanced public datasets KDDCUP99 and Credit Card Fraud 2013. The method includes data preparation, model training, and evaluation, using an 80/20 train/test split. Models tested include eXtreme Gradient Boosting XGB, Multi Layer...

LLMpatronous: Harnessing the Power of LLMs for Vulnerability Detection

Despite the transformative impact of Artificial Intelligence AI across various sectors, cyber security continues to rely on traditional static and dynamic analysis tools, hampered by high false positive rates and superficial code comprehension. While generative AI offers promising automation...

TSCL:Multi-Party Loss Balancing Scheme for Deep Learning Image Steganography Based on Curriculum Learning

For deep learning-based image steganography frameworks, in order to ensure the invisibility and recoverability of the information embedding, the loss function usually contains several losses such as embedding loss, recovery loss and steganalysis loss. In previous research works, fixed loss weight...

STCL: Curriculum Learning Strategies for Deep Learning Image Steganography Models

Whitepaper called STCL: Curriculum Learning Strategies For Deep Learning Image Steganography Models...

Evaluating the Vulnerability of ML-Based Ethereum Phishing Detectors to Single-Feature Adversarial Perturbations

This paper explores the vulnerability of machine learning models to simple single-feature adversarial attacks in the context of Ethereum fraudulent transaction detection. Through comprehensive experimentation, we investigate the impact of various adversarial attack strategies on model performance...

Security Science (SecSci), Basic Concepts and Mathematical Foundations

This textbook compiles the lecture notes from security courses taught at Oxford in the 2000s, at Royal Holloway in the 2010s, and currently in Hawaii. The early chapters are suitable for a first course in security. The middle chapters have been used in advanced courses. Towards the end there are...

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...

Evaluating Argon2 Adoption and Effectiveness in Real-World Software

Modern password hashing remains a critical defense against credential cracking, yet the transition from theoretically secure algorithms to robust real-world implementations remains fraught with challenges. This paper presents a dual analysis of Argon2, the Password Hashing Competition winner,...

Resource Reduction in Multiparty Quantum Secret Sharing of Both Classical and Quantum Information under Noisy Scenario

Quantum secret sharing QSS enables secure distribution of information among multiple parties but remains vulnerable to noise. We analyze the effects of bit-flip, phase-flip, and amplitude damping noise on the multiparty QSS for classical message QSSCM and secret sharing of quantum information SSQ...

Quantum Technologies for beyond 5G and 6G Networks: Applications, Opportunities, and Challenges

As the world prepares for the advent of 6G networks, quantum technologies are becoming critical enablers of the next generation of communication systems. This survey paper investigates the convergence of quantum technologies and 6G networks, focusing on their applications, opportunities and...

On the Consistency of GNN Explanations for Malware Detection

Control Flow Graphs CFGs are critical for analyzing program execution and characterizing malware behavior. With the growing adoption of Graph Neural Networks GNNs, CFG-based representations have proven highly effective for malware detection. This study proposes a novel framework that dynamically...

Anamorphic Cryptography with Elliptic Curve Methods

In 2022, Persianom, Phan and Yung outlined the creation of Anamorphic Cryptography. With this, we can create a public key to encrypt data, and then have two secret keys. These secret keys are used to decrypt the cipher into different messages. So, one secret key is given to the Dictator who must ...

Scalable APT Malware Classification Via Parallel Feature Extraction and GPU-Accelerated Learning

This paper presents an underlying framework for both automating and accelerating malware classification, more specifically, mapping malicious executables to known Advanced Persistent Threat APT groups. The main feature of this analysis is the assembly-level instructions present in executables whi...

A Data-Centric Approach for Safe and Secure Large Language Models against Threatening and Toxic Content

Large Language Models LLM have made remarkable progress, but concerns about potential biases and harmful content persist. To address these apprehensions, we introduce a practical solution for ensuring LLM's safe and ethical use. Our novel approach focuses on a post-generation correction mechanism...

Towards Stateless Clients in Ethereum: Benchmarking Verkle Trees and Binary Merkle Trees with SNARKs

Ethereum, the leading platform for decentralized applications, faces challenges in maintaining decentralization due to the significant hardware requirements for validators to store Ethereum's entire state. To address this, the concept of stateless clients is under exploration, enabling validators...

Post Quantum Cryptography (PQC) Signatures without Trapdoors

Some of our current public key methods use a trap door to implement digital signature methods. This includes the RSA method, which uses Fermat's little theorem to support the creation and verification of a digital signature. The problem with a back-door is that the actual trap-door method could, ...

Set You Straight: Auto-Steering Denoising Trajectories to Sidestep Unwanted Concepts

Ensuring the ethical deployment of text-to-image models requires effective techniques to prevent the generation of harmful or inappropriate content. While concept erasure methods offer a promising solution, existing finetuning-based approaches suffer from notable limitations. Anchor-free methods...

Trusted Identities for AI Agents: Leveraging Telco-Hosted ESIM Infrastructure

The rise of autonomous AI agents in enterprise and industrial environments introduces a critical challenge: how to securely assign, verify, and manage their identities across distributed systems. Existing identity frameworks based on API keys, certificates, or application-layer credentials lack t...

Wireshark Analyzer 4.4.6

Wireshark is a GTK+-based network protocol analyzer that lets you capture and interactively browse the contents of network frames. The goal of the project is to create a commercial-quality analyzer for Unix and Win32 and to give Wireshark features that are missing from closed-source sniffers. Thi...

Omnissa Unified Access Gateway (UAG) CORS Bypass

A cross-origin resource sharing bypass vulnerability was privately reported in Omnissa Unified Access Gateway UAG. An update is available to remediate this vulnerability in impacted versions of the product. The fixed version is 2503...

Security-First AI: Foundations for Robust and Trustworthy Systems

The conversation around artificial intelligence AI often focuses on safety, transparency, accountability, alignment, and responsibility. However, AI security i.e., the safeguarding of data, models, and pipelines from adversarial manipulation underpins all of these efforts. This manuscript posits...

ZkVC: Fast Zero-Knowledge Proof for Private and Verifiable Computing

Whitepaper called ZkVC: Fast Zero-Knowledge Proof For Private And Verifiable Computing...

Secure Transfer Learning: Training Clean Models against Backdoor in (Both) Pre-Trained Encoders and Downstream Datasets

Transfer learning from pre-trained encoders has become essential in modern machine learning, enabling efficient model adaptation across diverse tasks. However, this combination of pre-training and downstream adaptation creates an expanded attack surface, exposing models to sophisticated backdoor...

A Scalable Framework for Post-Quantum Authentication in Public Key Infrastructures

This work explores the performance and scalability of a hierarchical certificate authority framework with automated certificate issuance employing post-quantum cryptographic PQC signature algorithms. The system is designed for compatibility with both classical and PQC algorithms, promoting...

MULTI-LF: a Unified Continuous Learning Framework for Real-Time DDoS Detection in Multi-Environment Networks

Detecting Distributed Denial of Service DDoS attacks in Multi-Environment M-En networks presents significant challenges due to diverse malicious traffic patterns and the evolving nature of cyber threats. Existing AI-based detection systems struggle to adapt to new attack strategies and lack...

OpenSSH 10.0p1

OpenSSH is the premier connectivity tool for remote login with the SSH protocol. It encrypts all traffic to eliminate eavesdropping, connection hijacking, and other attacks. In addition, OpenSSH provides a large suite of secure tunneling capabilities, several authentication methods, and...

WordPress Motors 1.4.64 Arbitrary Plugin Installation

WordPress Motors plugin versions 1.4.64 and below suffer from an arbitrary plugin installation vulnerability...

OpenSCAP Libraries 1.3.12

The openscap project is a set of open source libraries that support the SCAP Security Content Automation Protocol set of standards from NIST. It supports CPE, CCE, CVE, CVSS, OVAL, and XCCDF...

Next.js Middleware Authorization Bypass

Proof of concept exploit that demonstrates an authorization bypass being exploited in Next.js middleware...

Linux ax88179_rx_fixup() Out-Of-Bounds Access

drivers/net/usb/ax88179178a.c contains multiple out-of-bounds accesses in ax88179rxfixup, the function responsible for taking a buffer received over USB and splitting it up into ethernet packets...

How to Create a Scan to Identify Remote Command Execution

This whitepaper covers how to create a scan in Perl to identify remote command execution in web applications. Depending on the context of the environment and architecture, the content of the paper can be applied to APIs in addition to presenting how to correct or avoid RCE problems at the code...