Sec5GLoc

Sec5GLoc: 적대적 공격에 강인한 딥러닝 아키텍처를 통한 5G 실내 측위 보안 본 연구는 적대적 공격에 강인한 딥러닝 아키텍처를 제안하여 5G 실내 측위의 보안 및 프라이버시 문제를 해결합니다. Sec5GLoc은 채널 임펄스 응답CIR 핑거프린팅과 도착 시간 차TDoA 피처 및 알려진 앵커 위치를 결합하며, 하이브리드 CNN과 멀티-헤드 어텐션 네트워크가 이를 처리합니다. 이 설계는 위치 스푸핑 및 적대적 신호 변조와 같은 위협에 대한 견고성을 향상시킵니다. 그림 1. 적대적 신호 교란 및 물리 계층 위협 하에서 안전하고...

DeepTraffic

네트워크 트래픽 분류를 위한 딥러닝 모델 자세한 내용은 논문을 참조하세요. 🎓Wei Wang의 Google Scholar 홈페이지 Wei Wang, Xuewen Zeng, Xiaozhou Ye, Yiqiang Sheng 및 Ming Zhu, "표현 학습을 위한 합성곱 신경망을 사용한 악성 트래픽 분류", 제31회 International Conference on Information Networking ICOIN 2017, pp. 712-717, 2017. Wei Wang, Jinlin Wang, Xuewen Zeng,...

Octopii

Octopii ⠀⠀⠀⠀⠀⠀⠀⣤⣤⣄⣀⡀⠀⠀⠀⢀⣠⣤⣤⣄⡀⠀⠀⠀⢀⣀⣠⣤⣤⠀⠀⠀⠀⠀⠀⠀⠀⠀ ⠀⠀⠀⠀⠀⠀⠸⣿⣿⡿⠿⢿⣷⡄⢠⣿⣿⣿⣿⣿⣿⡄⢀⣾⡿⠿⢿⣿⣿⠇⠀⠀⠀⠀⠀⠀⠀⠀ ⠀⠀⠀⠀⠀⠀⠀⠈⠉⠀⠀⢸⣿⡇⢸⣿⣿⣿⣿⣿⣿⡇⢸⣿⡇⠀⠀⠉⠁⠀⠀⠀⠀⠀⠀⠀⠀⠀ ⠀⣠⣤⡀⠀⠀⠀⠀⠀⠀⠀⢸⣿⡇⢸⣿⣿⣿⣿⣿⣿⡇⢸⣿⡇⠀⠀⠀⠀⠀⠀⠀⢀⣤⣄⠀⠀⠀ ⠸⣿⣿⣿⣿⣿⣿⣿⣿⣦⠀⢸⣿⡇⢸⣿⣿⣿⣿⣿⣿⡇⢸⣿⡇⠀⣴⣿⣿⣿⣿⣿⣿⣿⣿⠇⠀⠀ ⠀⠉⠉⠁⠀⠀⠀⠀⣿⣿⠀⢸⣿⡇⠀⠉⣿⣿⣿⣿⠉⠀⢸⣿⡇⠀⣿⣿⠀⠀⠀⠀⠈⠉⠉⠀⠀ ⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣀⣈⣻⣿⣿⣿⣿⣿⣿⣿⣿⣿⣿⣟⣁⣀⣿⣿⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀...

machine_learning_security

머신러닝과 보안 머신러닝과 보안에 관한 소스 코드입니다. 목록 사이버 보안 및 머신러닝 과정 보안 엔지니어를 위한 머신러닝 기초 교육 과정입니다. 머신러닝의 취약점 머신러닝 취약점 요약. 분석 k-means를 사용한 패킷 캡처 데이터 분석. CNNtest CNN에 대한 적대적 예제 생성. Deep Exploit 머신러닝을 이용한 완전 자동 침투 테스트 도구. Deep Exploit은 Black Hat USA 2018 Arsenal , Black Hat EURO 2018 Arsenal 및 DEF CON 26! AI Village...

eyeballer

Eyeballer Give those screenshots of yours a quick eyeballing. Eyeballer is meant for large-scope network penetration tests where you need to find "interesting" targets from a huge set of web-based hosts. Go ahead and use your favorite screenshotting tool like normal EyeWitness or GoWitness and th...

SEVulDet

SEVulDet SEVulDet는 더 많은 시맨틱을 추출, 보존 및 학습하여 취약점 패턴을 정확하게 찾아내는 시맨틱 강화 딥러닝 기반 프레임워크입니다. 이메일 문의: [email protected] SEVulDet 상세 정보 최근 몇 년간 신경망을 활용하여 취약점 패턴을 식별하는 딥러닝 기반 취약점 탐지 프레임워크에 대한 관심이 증가했습니다. 많은 노력이 있었지만, 기존 접근 방식은 실제로 정확도가 낮습니다. 이전 연구들은 소스 코드에서 시맨틱을 포괄적으로 캡처하지 못하거나 신경망의 적절한 설계를 채택하지 못합니다. ...

Systematically Optimized CNN-Transformer with Focal Loss for Imbalanced Intrusion Detection on NSL-KDD

Intrusion Detection Systems IDS struggle with imbalanced datasets like NSL-KDD, especially in detecting rare R2L and U2R attacks. This work describes a systematically optimized and explainable framework using a CNN-Transformer architecture to improve performance on highly imbalanced data. We...

Cybersecurity in Edge Computing: A Trust-Aware Federated Hybrid Intrusion Detection Framework

Edge computing has emerged as a critical computing paradigm in modern distributed systems by migrating data processing closer to end users and Internet of Things IoT devices. While this paradigm decentralizes processes, minimizes latency, and reduces backhaul bandwidth congestion, it exponentiall...

TP-CRIV: A Framework for Third-Party Challenge-Response Identity Verification of AI Models

Artificial intelligence AI models are increasingly deployed through remote services, making model misappropriation a growing concern. Existing approaches, including watermarking, fingerprinting, and model similarity analysis, primarily rely on predefined evidence or direct behavioral comparison a...

Topological Signatures of Cyber-Attack Classes in Natural Visibility Graph Representations of Network Traffic

Natural Visibility Graph NVG-based representations provide a promising approach for capturing structural patterns in sequential network traffic. However, whether different cyber-attack classes exhibit distinctive topological signatures in such representations remains insufficiently understood. Th...

Delphi Scanner: Efficient and Interpretable Static Malware Detection Via API Sequence Modeling

Static malware detection for Windows Portable Executable files demands a careful balance between detection effectiveness, computational efficiency, and analytical interpretability. This paper introduces Delphi Scanner, a static malware detection system for Windows PE files that balances efficienc...

Categorical Robustness Assessment for Machine Learning Based Network Intrusion Detection Systems

Network Intrusion Detection Systems NIDS heavily utlize Machine Learning ML but ML models can be manipulated via adversarial attacks. These attacks add carefully crafted perturbations to network traffic data that leads to misclassifications. While prior work has demonstrated adversarial...

Separating Secrets from Placeholders: A Hybrid CNN-CodeBERT Framework for Three-Class Credential Leakage Detection

Credential leakage in public source code repositories poses a critical security threat, with over 23.8 million secrets exposed in 2024 alone. Existing detection tools suffer from high false-positive rates because rigid pattern matching and binary classification schemes fail to distinguish genuine...

Deepfake Geography: Detecting AI-Generated Satellite Images

The rapid advancement of generative models such as StyleGAN2 and Stable Diffusion poses a growing threat to the authenticity of satellite imagery, which is increasingly vital for reliable analysis and decision-making across scientific and security domains. While deepfake detection has been...

Blockchain Powered Edge Intelligence for U-Healthcare in Privacy Critical and Time Sensitive Environment

Edge Intelligence EI serves as a critical enabler for privacy-preserving systems by providing AI-empowered computation and distributed caching services at the edge, thereby minimizing latency and enhancing data privacy. The integration of blockchain technology further augments EI frameworks by...

A week in security (September 23 – September 29)

Last week on Malwarebytes Labs: Millions of Kia vehicles were vulnerable to remote attacks with just a license plate number Privacy watchdog files complaint over Firefox quietly enabling its Privacy Preserving Attribution Telegram will hand over user details to law enforcement Don’t share the vir...

SpaceX, CNN, and The White House internal data allegedly published online. Is it real?

A cybercriminal has released internal data online that they say has come from leaks at several high-profile sources, including SpaceX, CNN, and the White House. However, there are some questions around the reliability and usefulness of the released data, so we took a closer look. When it comes to...

cnn.gr Cross Site Scripting vulnerability OBB-3949437

Following the coordinated and responsible vulnerability disclosure guidelines of the ISO 29147 standard, Open Bug Bounty has: a. verified the vulnerability and confirmed its existence; b. notified the website operator about its existence. Technical details of the vulnerability are currently hidde...

Big name TikTok accounts hijacked after opening DM

High profile TikTok accounts, including CNN, Sony, and—er­—Paris Hilton have been targeted in a recent attack. CNN was the first account takeover that made the news, with Semafor reporting that the account was down for several days after the incident. According to Forbes, the attack happens witho...

TikTok Hack Targets ‘High-Profile’ Users via DMs

TikTok has confirmed a “potential exploit” that is being used to go after accounts belonging to media organizations and celebrities, including CNN and Paris Hilton, through direct messages...