AI-Powered Hybrid Intrusion Detection Framework for Cloud Security Using Novel Metaheuristic Optimization

Cybersecurity poses considerable problems to Cloud Computing CC, especially regarding Intrusion Detection Systems IDSs, facing difficulties with skewed datasets and suboptimal classification model performance. This study presents the Hybrid Intrusion Detection System HyIDS, an innovative IDS that...

GNU Privacy Guard 2.4.9

GnuPG the GNU Privacy Guard or GPG is GNU's tool for secure communication and data storage. It can be used to encrypt data and to create digital signatures. It includes an advanced key management facility and is compliant with the proposed OpenPGP Internet standard as described in RFC2440. As suc...

SQLMAP - Automatic SQL Injection Tool 1.10

sqlmap is an open source command-line automatic SQL injection tool. Its goal is to detect and take advantage of SQL injection vulnerabilities in web applications. Once it detects one or more SQL injections on the target host, the user can choose among a variety of options to perform an extensive...

Emoji-Based Jailbreaking of Large Language Models

Large Language Models LLMs are integral to modern AI applications, but their safety alignment mechanisms can be bypassed through adversarial prompt engineering. This study investigates emoji-based jailbreaking, where emoji sequences are embedded in textual prompts to trigger harmful and unethical...

Evil-M5Project WiFi Exploration Tool

This is the latest archive as of 2025/01/02 of the Evil-M5Project, an innovative tool developed for ethical testing and exploration of WiFi networks. It harnesses the power of the M5Core2 device to scan, monitor, and interact with WiFi networks in a controlled environment. This project is designe...

Towards Understanding and Characterizing Vulnerabilities in Intelligent Connected Vehicles through Real-World Exploits

Intelligent Connected Vehicles ICVs are a core component of modern transportation systems, and their security is crucial as it directly relates to user safety. Despite prior research, most existing studies focus only on specific sub-components of ICVs due to their inherent complexity. As a result...

Threat Intelligence Driven IP Protection for Entrepreneurial SMEs

Entrepreneurial small to medium enterprises face significant cybersecurity challenges when developing valuable intellectual property IP. This paper addresses the critical gap in research on how E-SMEs can protect their IP assets from cybersecurity threats through effective threat intelligence and...

TP-Link TL-WR820N 2.80 Weak Cryptography

TP-Link TL-WR820N version 2.80 uses weak cryptographic algorithms for SSH...

Impersonating Quantum Secrets over Classical Channels

We show that a simple eavesdropper listening in on classical communication between potentially entangled quantum parties will eventually be able to impersonate any of the parties. Furthermore, the attack is efficient if one-way puzzles do not exist. As a direct consequence, one-way puzzles are...

Revotech I6032W-FHW Authentication Bypass

The Revotech I6032W-FHW IP camera firmware contains an authentication bypass vulnerability in the /cgi-bin/jvsweb.cgi endpoint. The device does not validate the user.name and user.digest fields included in JSON-based API requests, allowing unauthenticated attackers to invoke administrative method...

Nuclei 3.6.2

Nuclei is a modern, high-performance vulnerability scanner that leverages simple YAML-based templates. It empowers you to design custom vulnerability detection scenarios that mimic real-world conditions, leading to zero false positives...

tcpdump 4.99.6

tcpdump allows you to dump the traffic on a network. It can be used to print out the headers and/or contents of packets on a network interface that matches a given expression. You can use this tool to track down network problems, to detect many attacks, or to monitor the network activities...

Scapy Packet Manipulation Tool 2.7.0

Scapy is a powerful interactive packet manipulation tool, packet generator, network scanner, network discovery tool, and packet sniffer. It provides classes to interactively create packets or sets of packets, manipulate them, send them over the wire, sniff other packets from the wire, match answe...

Improving Router Security Using BERT

Previous work on home router security has shown that using system calls to train a transformer-based language model built on a BERT-style encoder using contrastive learning is effective in detecting several types of malware, but the performance remains limited at low false positive rates. In this...

GNU Privacy Guard 2.5.16

GnuPG the GNU Privacy Guard or GPG is GNU's tool for secure communication and data storage. It can be used to encrypt data and to create digital signatures. It includes an advanced key management facility and is compliant with the proposed OpenPGP Internet standard as described in RFC2440. As suc...

CuFuzz: Hardening CUDA Programs through Transformation and Fuzzing

GPUs have gained significant popularity over the past decade, extending beyond their original role in graphics rendering. This evolution has brought GPU security and reliability to the forefront of concerns. Prior research has shown that CUDA's lack of memory safety can lead to serious...

PDPL Metric: Validating a Scale to Measure Personal Data Privacy Literacy among University Students

Personal data privacy literacy PDPL refers to a collection of digital literacy skills related to an individuals ability to understand, evaluate, and manage the collection, use, and protection of personal data in online and digital environments. This study introduces and validates a new psychometr...

libpcap 1.10.6

Libpcap is a portable packet capture library which is used in many packet sniffers, including tcpdump...

Vatilon-based IP Cameras Authentication Bypass / Credential Exposure

Vatilon-based IP camera firmware contains an authentication bypass and plaintext credential exposure vulnerability in the /cgi-bin/web.cgi API. The web interface processes requests containing username and password parameters in plaintext without validating authentication state or session context,...

Engineering Attack Vectors and Detecting Anomalies in Additive Manufacturing

Additive manufacturing AM is rapidly integrating into critical sectors such as aerospace, automotive, and healthcare. However, this cyber-physical convergence introduces new attack surfaces, especially at the interface between computer-aided design CAD and machine execution layers. In this work, ...

Post-Quantum Cryptography Key Expansion Method and Anonymous Certificate Scheme Based on NTRU

NTRU is one of the important lattice-based post-quantum cryptography methods, offering resistance against quantum computing attacks. However, a drawback of NTRU lies in its relatively low efficiency in generating key pairs. Therefore, this study proposes an NTRU-based key expansion method that...

Advanced Vulnerability Scanning for Open Source Software: Detection and Mitigation of Log4j Vulnerabilities

Automated detection of software vulnerabilities remains a critical challenge in software security. Log4j is an industrial-grade Java logging framework listed as one of the top 100 critical open source projects. On Dec. 10, 2021 a severe vulnerability Log4Shell was disclosed before being fully...

Cyberscurity Threats and Defense Mechanisms in IoT Network

The rapid proliferation of Internet of Things IoT technologies, projected to exceed 30 billion interconnected devices by 2030, has significantly escalated the complexity of cybersecurity challenges. This survey aims to provide a comprehensive analysis of vulnerabilities, threats, and defense...

An Empirical Evaluation of LLM-Based Approaches for Code Vulnerability Detection: RAG, SFT, and Dual-Agent Systems

The rapid advancement of Large Language Models LLMs presents new opportunities for automated software vulnerability detection, a crucial task in securing modern codebases. This paper presents a comparative study on the effectiveness of LLM-based techniques for detecting software vulnerabilities...

Cracking IoT Security: Can LLMs Outsmart Static Analysis Tools?

Smart home IoT platforms such as openHAB rely on Trigger Action Condition TAC rules to automate device behavior, but the interplay among these rules can give rise to interaction threats, unintended or unsafe behaviors emerging from implicit dependencies, conflicting triggers, or overlapping...

Low Rank Comes with Low Security: Gradient Assembly Poisoning Attacks against Distributed LoRA-Based LLM Systems

Low-Rank Adaptation LoRA has become a popular solution for fine-tuning large language models LLMs in federated settings, dramatically reducing update costs by introducing trainable low-rank matrices. However, when integrated with frameworks like FedIT, LoRA introduces a critical vulnerability:...

From Consensus to Chaos: A Vulnerability Assessment of the RAFT Algorithm

In recent decades, the RAFT distributed consensus algorithm has become a main pillar of the distributed systems ecosystem, ensuring data consistency and fault tolerance across multiple nodes. Although the fact that RAFT is well known for its simplicity, reliability, and efficiency, its security...

Rectifying Adversarial Examples Using Their Vulnerabilities

Deep neural network-based classifiers are prone to errors when processing adversarial examples AEs. AEs are minimally perturbed input data undetectable to humans posing significant risks to security-dependent applications. Hence, extensive research has been undertaken to develop defense mechanism...

Exploring the Integration of Differential Privacy in Cybersecurity Analytics: Balancing Data Utility and Privacy in Threat Intelligence

To resolve the acute problem of privacy protection and guarantee that data can be used in the context of threat intelligence, this paper considers the implementation of Differential Privacy DP in cybersecurity analytics. DP, which is a sound mathematical framework, ensures privacy by adding a...

Scalable Ultrafast Random Bit Generation Using Wideband Chaos-Based Entropy Sources

The exponential growth of data transmission and processing speeds in modern digital infrastructure requires entropy sources capable of producing large volumes of true randomness for information security. Chaotic emissions from semiconductor lasers are attractive in this context because of their...

Towards Eco Friendly Cybersecurity: Machine Learning Based Anomaly Detection with Carbon and Energy Metrics

The rising energy footprint of artificial intelligence has become a measurable component of US data center emissions, yet cybersecurity research seldom considers its environmental cost. This study introduces an eco aware anomaly detection framework that unifies machine learning based network...

CellSecInspector: Safeguarding Cellular Networks Via Automated Security Analysis on Specifications

The complexity, interdependence, and rapid evolution of 3GPP specifications present fundamental challenges for ensuring the security of modern cellular networks. Manual reviews and existing automated approaches, which often depend on rule-based parsing or small sets of manually crafted security...

Understanding Security Risks of AI Agents' Dependency Updates

Package dependencies are a critical control point in modern software supply chains. Dependency changes can substantially alter a project's security posture. As AI coding agents increasingly modify software via pull requests, it is unclear whether their dependency decisions introduce distinct...

SourceBroken: A Large-Scale Analysis on the (Un)Reliability of SourceRank in the PyPI Ecosystem

SourceRank is a scoring system made of 18 metrics that assess the popularity and quality of open-source packages. Despite being used in several recent studies, none has thoroughly analyzed its reliability against evasion attacks aimed at inflating the score of malicious packages, thereby...

Correctness of Extended RSA Public Key Cryptosystem

This paper proposes an alternative approach to formally establishing the correctness of the RSA public key cryptosystem. The methodology presented herein deviates slightly from conventional proofs found in existing literature. Specifically, this study explores the conditions under which the choic...

FedLiTeCAN : A Federated Lightweight Transformer for Fast and Robust CAN Bus Intrusion Detection

This work implements a lightweight Transformer model for IDS in the domain of Connected and Autonomous Vehicles...

Jailbreaking Attacks Vs. Content Safety Filters: How Far Are We in the LLM Safety Arms Race?

As large language models LLMs are increasingly deployed, ensuring their safe use is paramount. Jailbreaking, adversarial prompts that bypass model alignment to trigger harmful outputs, present significant risks, with existing studies reporting high success rates in evading common LLMs. However,...

SynRAG: A Large Language Model Framework for Executable Query Generation in Heterogeneous SIEM System

Security Information and Event Management SIEM systems are essential for large enterprises to monitor their IT infrastructure by ingesting and analyzing millions of logs and events daily. Security Operations Center SOC analysts are tasked with monitoring and analyzing this vast data to identify...

The Quantum State Continuity Problem and Temporal Enforcement against Fork Attacks

We introduce the Quantum State Continuity Problem QSCP, a security objective orthogonal to identity authentication that captures whether a systems current execution is a legitimate continuation of a unique past execution. We show that classical and stateless quantum authentication mechanisms fail...

Quantum Machine Learning Approaches for Coordinated Stealth Attack Detection in Distributed Generation Systems

Coordinated stealth attacks are a serious cybersecurity threat to distributed generation systems because they modify control and measurement signals while remaining close to normal behavior, making them difficult to detect using standard intrusion detection methods. This study investigates quantu...

Large Empirical Case Study: Go-Explore Adapted for AI Red Team Testing

Production LLM agents with tool-using capabilities require security testing despite their safety training. We adapt Go-Explore to evaluate GPT-4o-mini across 28 experimental runs spanning six research questions. We find that random-seed variance dominates algorithmic parameters, yielding an 8x...

Training-Free Color-Aware Adversarial Diffusion Sanitization for Diffusion Stegomalware Defense at Security Gateways

The rapid expansion of generative AI has normalized large-scale synthetic media creation, enabling new forms of covert communication. Recent generative steganography methods, particularly those based on diffusion models, can embed high-capacity payloads without fine-tuning or auxiliary decoders,...

MeLeMaD: Adaptive Malware Detection Via Chunk-Wise Feature Selection and Meta-Learning

Confronting the substantial challenges of malware detection in cybersecurity necessitates solutions that are both robust and adaptable to the ever-evolving threat environment. The paper introduces Meta Learning Malware Detection MeLeMaD, a novel framework leveraging the adaptability and...

Toward Trustworthy Agentic AI: A Multimodal Framework for Preventing Prompt Injection Attacks

Powerful autonomous systems, which reason, plan, and converse using and between numerous tools and agents, are made possible by Large Language Models LLMs, Vision-Language Models VLMs, and new agentic AI systems, like LangChain and GraphChain. Nevertheless, this agentic environment increases the...

Research Directions in Quantum Computer Cybersecurity

This document presents a concise overview of the contemporary research directions in quantum computer cybersecurity. The aim of this document is not to be a survey, but rather a succinct summary of the major research directions in quantum computer cybersecurity at the end of the first half of the...

Security without Detection: Economic Denial As a Primitive for Edge and IoT Defense

Detection-based security fails against sophisticated attackers using encryption, stealth, and low-rate techniques, particularly in IoT/edge environments where resource constraints preclude ML-based intrusion detection. We present Economic Denial Security EDS, a detection-independent framework tha...

Agentic AI for Autonomous Defense in Software Supply Chain Security: Beyond Provenance to Vulnerability Mitigation

The software supply chain attacks are becoming more and more focused on trusted development and delivery procedures, so the conventional post-build integrity mechanisms cannot be used anymore. The available frameworks like SLSA, SBOM and in toto are majorly used to offer provenance and traceabili...

Zero-Trust Agentic Federated Learning for Secure IIoT Defense Systems

Recent attacks on critical infrastructure, including the 2021 Oldsmar water treatment breach and 2023 Danish energy sector compromises, highlight urgent security gaps in Industrial IoT IIoT deployments. While Federated Learning FL enables privacy-preserving collaborative intrusion detection,...

Breaking Audio Large Language Models by Attacking Only the Encoder: A Universal Targeted Latent-Space Audio Attack

Audio-language models combine audio encoders with large language models to enable multimodal reasoning, but they also introduce new security vulnerabilities. We propose a universal targeted latent space attack, an encoder-level adversarial attack that manipulates audio latent representations to...

Application-Specific Power Side-Channel Attacks and Countermeasures: A Survey

Side-channel attacks try to extract secret information from a system by analyzing different side-channel signatures, such as power consumption, electromagnetic emanation, thermal dissipation, acoustics, time, etc. Power-based side-channel attack is one of the most prominent side-channel attacks i...