GenAI Security: Outsmarting the Bots with a Proactive Testing Framework

The increasing sophistication and integration of Generative AI GenAI models into diverse applications introduce new security challenges that traditional methods struggle to address. This research explores the critical need for proactive security measures to mitigate the risks associated with...

Adversarial Suffix Filtering: a Defense Pipeline for LLMs

Large Language Models LLMs are increasingly embedded in autonomous systems and public-facing environments, yet they remain susceptible to jailbreak vulnerabilities that may undermine their security and trustworthiness. Adversarial suffixes are considered to be the current state-of-the-art...

Optimizing DDoS Detection in SDNs through Machine Learning Models

The emergence of Software-Defined Networking SDN has changed the network structure by separating the control plane from the data plane. However, this innovation has also increased susceptibility to DDoS attacks. Existing detection techniques are often ineffective due to data imbalance and accurac...

Security and Privacy Measurement on Chinese Consumer IoT Traffic Based on Device Lifecycle

In recent years, consumer Internet of Things IoT devices have become widely used in daily life. With the popularity of devices, related security and privacy risks arise at the same time as they collect user-related data and transmit it to various service providers. Although China accounts for a...

CANTXSec: a Deterministic Intrusion Detection and Prevention System for CAN Bus Monitoring ECU Activations

Despite being a legacy protocol with various known security issues, Controller Area Network CAN still represents the de-facto standard for communications within vehicles, ships, and industrial control systems. Many research works have designed Intrusion Detection Systems IDSs to identify attacks ...

Scaling Up: Revisiting Mining Android Sandboxes at Scale for Malware Classification

The widespread use of smartphones in daily life has raised concerns about privacy and security among researchers and practitioners. Privacy issues are generally highly prevalent in mobile applications, particularly targeting the Android platform, the most popular mobile operating system. For this...

WhatsAI: Transforming Meta Ray-Bans into an Extensible Generative AI Platform for Accessibility

Multi-modal generative AI models integrated into wearable devices have shown significant promise in enhancing the accessibility of visual information for blind or visually impaired BVI individuals, as evidenced by the rapid uptake of Meta Ray-Bans among BVI users. However, the proprietary nature ...

DNS Query Forgery: a Client-Side Defense against Mobile App Traffic Profiling

Mobile applications continuously generate DNS queries that can reveal sensitive user behavioral patterns even when communications are encrypted. This paper presents a privacy enhancement framework based on query forgery to protect users against profiling attempts that leverage these background...

Gaussian Shading++: Rethinking the Realistic Deployment Challenge of Performance-Lossless Image Watermark for Diffusion Models

Ethical concerns surrounding copyright protection and inappropriate content generation pose challenges for the practical implementation of diffusion models. One effective solution involves watermarking the generated images. Existing methods primarily focus on ensuring that watermark embedding doe...

Cryptologic Techniques and Associated Risks in Public and Private Security. an Italian and European Union Perspective with an Overview of the Current Legal Framework

This article examines the evolution of cryptologic techniques and their implications for public and private security, focusing on the Italian and EU legal frameworks. It explores the roles of cryptography, steganography, and quantum technologies in countering cybersecurity threats, emphasising th...

Multiparty Selective Disclosure Using Attribute-Based Encryption

This study proposes a mechanism for encrypting SD-JWT Selective Disclosure JSON Web Token Disclosures using Attribute-Based Encryption ABE to enable flexible access control on the basis of the Verifier's attributes. By integrating Ciphertext-Policy ABE CP-ABE into the existing SD-JWT framework, t...

ROSA: Finding Backdoors with Fuzzing

A code-level backdoor is a hidden access, programmed and concealed within the code of a program. For instance, hard-coded credentials planted in the code of a file server application would enable maliciously logging into all deployed instances of this application. Confirmed software supply chain...

LibVulnWatch: a Deep Assessment Agent System and Leaderboard for Uncovering Hidden Vulnerabilities in Open-Source AI Libraries

Open-source AI libraries are foundational to modern AI systems but pose significant, underexamined risks across security, licensing, maintenance, supply chain integrity, and regulatory compliance. We present LibVulnWatch, a graph-based agentic assessment framework that performs deep,...

Comparative Analysis of Blockchain Systems

Blockchain is a type of decentralized distributed database. Unlike traditional relational database management systems, it does not require management or maintenance by a third party. All data management and update processes are open and transparent, solving the trust issues of centralized databas...

Inference Attacks for X-Vector Speaker Anonymization

We revisit the privacy-utility tradeoff of x-vector speaker anonymization. Existing approaches quantify privacy through training complex speaker verification or identification models that are later used as attacks. Instead, we propose a novel inference attack for de-anonymization. Our attack is...

Information Leakage in Data Linkage

The process of linking databases that contain sensitive information about individuals across organisations is an increasingly common requirement in the health and social science research domains, as well as with governments and businesses. To protect personal data, protocols have been developed t...

Modeling Interdependent Cybersecurity Threats Using Bayesian Networks: a Case Study on In-Vehicle Infotainment Systems

Cybersecurity threats are increasingly marked by interdependence, uncertainty, and evolving complexity challenges that traditional assessment methods such as CVSS, STRIDE, and attack trees fail to adequately capture. This paper reviews the application of Bayesian Networks BNs in cybersecurity ris...

On the Interplay of Explainability, Privacy and Predictive Performance with Explanation-Assisted Model Extraction

Machine Learning as a Service MLaaS has gained important attraction as a means for deploying powerful predictive models, offering ease of use that enables organizations to leverage advanced analytics without substantial investments in specialized infrastructure or expertise. However, MLaaS...

Removing Watermarks with Partial Regeneration Using Semantic Information

As AI-generated imagery becomes ubiquitous, invisible watermarks have emerged as a primary line of defense for copyright and provenance. The newest watermarking schemes embed semantic signals - content-aware patterns that are designed to survive common image manipulations - yet their true...

On the Account Security Risks Posed by Password Strength Meters

Password strength meters PSMs have been widely used by websites to gauge password strength, encouraging users to create stronger passwords. Popular data-driven PSMs, e.g., based on Markov, Probabilistic Context-free Grammar PCFG and neural networks, alarm strength based on a model learned from re...

The Sponge Is Quantum Indifferentiable

The sponge is a cryptographic construction that turns a public permutation into a hash function. When instantiated with the Keccak permutation, the sponge forms the NIST SHA-3 standard. SHA-3 is a core component of most post-quantum public-key cryptography schemes slated for worldwide adoption...

Quantum Support Vector Regression for Robust Anomaly Detection

Anomaly Detection AD is critical in data analysis, particularly within the domain of IT security. In recent years, Machine Learning ML algorithms have emerged as a powerful tool for AD in large-scale data. In this study, we explore the potential of quantum ML approaches, specifically quantum kern...

Area Comparison of CHERIoT and PMP in Ibex

Memory safety is a critical concern for modern embedded systems, particularly in security-sensitive applications. This paper explores the area impact of adding memory safety extensions to the Ibex RISC-V core, focusing on physical memory protection PMP and Capability Hardware Extension to RISC-V...

Red Teaming the Mind of the Machine: a Systematic Evaluation of Prompt Injection and Jailbreak Vulnerabilities in LLMs

Large Language Models LLMs are increasingly integrated into consumer and enterprise applications. Despite their capabilities, they remain susceptible to adversarial attacks such as prompt injection and jailbreaks that override alignment safeguards. This paper provides a systematic investigation o...

Where the Devil Hides: Deepfake Detectors Can No Longer Be Trusted

With the advancement of AI generative techniques, Deepfake faces have become incredibly realistic and nearly indistinguishable to the human eye. To counter this, Deepfake detectors have been developed as reliable tools for assessing face authenticity. These detectors are typically developed on De...

iOS SwiftZero CVE-2025-24203 Proof of Concept

SwiftZero is a proof of concept exploit for iOS versions 16.0 through 18.3.2 that performs a protected file overwrite...

SAFE-SiP: Secure Authentication Framework for System-In-Package Using Multi-Party Computation

The emergence of chiplet-based heterogeneous integration is transforming the semiconductor, AI, and high-performance computing industries by enabling modular designs and improved scalability. However, assembling chiplets from multiple vendors after fabrication introduces a complex supply chain th...

Unencrypted Flying Objects: Security Lessons from University Small Satellite Developers and Their Code

Satellites face a multitude of security risks that set them apart from hardware on Earth. Small satellites may face additional challenges, as they are often developed on a budget and by amateur organizations or universities that do not consider security. We explore the security practices and...

Lightweight Hybrid Block-Stream Cryptographic Algorithm for the Internet of Things

In this thesis, a novel lightweight hybrid encryption algorithm named SEPAR is proposed, featuring a 16-bit block length and a 128-bit initialization vector. The algorithm is designed specifically for application in Internet of Things IoT technology devices. The design concept of this algorithm i...

Key Exchange Protocol Based on Circulant Matrix Action over Congruence-Simple Semiring

We present a new key exchange protocol based on circulant matrices acting on matrices over a congruence-simple semiring. We describe how to compute matrices with the necessary properties for the implementation of the protocol. Additionally, we provide an analysis of its computational cost and its...

Cryptography without Long-Term Quantum Memory and Global Entanglement: Classical Setups for One-Time Programs, Copy Protection, and Stateful Obfuscation

We show how oracles which only allow for classical query access can be used to construct a variety of quantum cryptographic primitives which do not require long-term quantum memory or global entanglement. Specifically, if a quantum party can execute a semi-quantum token scheme Shmueli 2022 with...

Kudzu: Fast and Simple High-Throughput BFT

We present Kudzu, a high-throughput atomic broadcast protocol with an integrated fast path. Our contribution is based on the combination of two lines of work. Firstly, our protocol achieves finality in just two rounds of communication if all but $p$ out of $n = 3f + 2p + 1$ participating replicas...

MUBox: a Critical Evaluation Framework of Deep Machine Unlearning

Recent legal frameworks have mandated the right to be forgotten, obligating the removal of specific data upon user requests. Machine Unlearning has emerged as a promising solution by selectively removing learned information from machine learning models. This paper presents MUBox, a comprehensive...

GPML: Graph Processing for Machine Learning

The dramatic increase of complex, multi-step, and rapidly evolving attacks in dynamic networks involves advanced cyber-threat detectors. The GPML Graph Processing for Machine Learning library addresses this need by transforming raw network traffic traces into graph representations, enabling...

Robustness Analysis against Adversarial Patch Attacks in Fully Unmanned Stores

The advent of convenient and efficient fully unmanned stores equipped with artificial intelligence-based automated checkout systems marks a new era in retail. However, these systems have inherent artificial intelligence security vulnerabilities, which are exploited via adversarial patch attacks,...

Blockchain Technology: Core Mechanisms, Evolution, and Future Implementation Challenges

Blockchain technology has emerged as one of the most transformative digital innovations of the 21st century. This paper presents a comprehensive review of blockchain's fundamental architecture, tracing its development from Bitcoin's initial implementation to current enterprise applications. We...

Improved Algorithms for Differentially Private Language Model Alignment

Language model alignment is crucial for ensuring that large language models LLMs align with human preferences, yet it often involves sensitive user data, raising significant privacy concerns. While prior work has integrated differential privacy DP with alignment techniques, their performance...

Measuring the Accuracy and Effectiveness of PII Removal Services

This paper presents the first large-scale empirical study of commercial personally identifiable information PII removal systems -- commercial services that claim to improve privacy by automating the removal of PII from data broker's databases. Popular examples of such services include DeleteMe,...

Adaptive Security Policy Management in Cloud Environments Using Reinforcement Learning

The security of cloud environments, such as Amazon Web Services AWS, is complex and dynamic. Static security policies have become inadequate as threats evolve and cloud resources exhibit elasticity 1. This paper addresses the limitations of static policies by proposing a security policy managemen...

Privacy-Preserving Analytics for Smart Meter (AMI) Data: a Hybrid Approach to Comply with CPUC Privacy Regulations

Advanced Metering Infrastructure AMI data from smart electric and gas meters enables valuable insights for utilities and consumers, but also raises significant privacy concerns. In California, regulatory decisions CPUC D.11-07-056 and D.11-08-045 mandate strict privacy protections for customer...

Optimized Couplings for Watermarking Large Language Models

Large-language models LLMs are now able to produce text that is, in many cases, seemingly indistinguishable from human-generated content. This has fueled the development of watermarks that imprint a signal'' in LLM-generated text with minimal perturbation of an LLM's output. This paper provides a...

Nmap Port Scanner 7.97

Nmap is a utility for port scanning large networks, although it works fine for single hosts. Sometimes you need speed, other times you may need stealth. In some cases, bypassing firewalls may be required. Not to mention the fact that you may want to scan different protocols UDP, TCP, ICMP, etc...

A Large-Scale Empirical Analysis of Custom GPTs' Vulnerabilities in the OpenAI Ecosystem

Millions of users leverage generative pretrained transformer GPT-based language models developed by leading model providers for a wide range of tasks. To support enhanced user interaction and customization, many platforms-such as OpenAI-now enable developers to create and publish tailored model...

Securing WiFi Fingerprint-Based Indoor Localization Systems from Malicious Access Points

WiFi fingerprint-based indoor localization schemes deliver highly accurate location data by matching the received signal strength indicator RSSI with an offline database using machine learning ML or deep learning DL models. However, over time, RSSI values degrade due to the malicious behavior of...

Federated Large Language Models: Feasibility, Robustness, Security and Future Directions

The integration of Large Language Models LLMs and Federated Learning FL presents a promising solution for joint training on distributed data while preserving privacy and addressing data silo issues. However, this emerging field, known as Federated Large Language Models FLLM, faces significant...

Fair Play for Individuals, Foul Play for Groups? Auditing Anonymization'S Impact on ML Fairness

Machine learning ML algorithms are heavily based on the availability of training data, which, depending on the domain, often includes sensitive information about data providers. This raises critical privacy concerns. Anonymization techniques have emerged as a practical solution to address these...

Mirror Mirror on the Wall, Have I Forgotten It All? A New Framework for Evaluating Machine Unlearning

Machine unlearning methods take a model trained on a dataset and a forget set, then attempt to produce a model as if it had only been trained on the examples not in the forget set. We empirically show that an adversary is able to distinguish between a mirror model a control model produced by...

Zeek 7.0.7

Zeek is a powerful network analysis framework that is much different from the typical IDS you may know. While focusing on network security monitoring, Zeek provides a comprehensive platform for more general network traffic analysis as well. Well grounded in more than 15 years of research, Zeek ha...

Post-Quantum Secure Decentralized Random Number Generation Protocol with Two Rounds of Communication in the Standard Model

Randomness plays a vital role in numerous applications, including simulation, cryptography, distributed systems, and gaming. Consequently, extensive research has been conducted to generate randomness. One such method is to design a decentralized random number generator DRNG, a protocol that enabl...

Assessing the Latency of Network Layer Security in 5G Networks

In contrast to its predecessors, 5G supports a wide range of commercial, industrial, and critical infrastructure scenarios. One key feature of 5G, ultra-reliable low latency communication, is particularly appealing to such scenarios for its real-time capabilities. However, 5G's enhanced security,...