Evading and crashing anti-malware solutions via data collection overloading during analysis serialization
Fuente:
arXiv
Guardado en:
| Autores principales: | Gkritsis, Evgenios, Patsakis, Constantinos, Stergiopoulos, George |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
QRS: A Rule-Synthesizing Neuro-Symbolic Triad for Autonomous Vulnerability Discovery
por: Tsigkourakos, George, et al.
Publicado: (2026)
por: Tsigkourakos, George, et al.
Publicado: (2026)
Just in Plain Sight: Unveiling CSAM Distribution Campaigns on the Clear Web
por: Lykousas, Nikolaos, et al.
Publicado: (2025)
por: Lykousas, Nikolaos, et al.
Publicado: (2025)
The Malware as a Service ecosystem
por: Patsakis, Constantinos, et al.
Publicado: (2024)
por: Patsakis, Constantinos, et al.
Publicado: (2024)
Assessing LLMs in Malicious Code Deobfuscation of Real-world Malware Campaigns
por: Patsakis, Constantinos, et al.
Publicado: (2024)
por: Patsakis, Constantinos, et al.
Publicado: (2024)
Hello, won't you tell me your name?: Investigating Anonymity Abuse in IPFS
por: Karapapas, Christos, et al.
Publicado: (2025)
por: Karapapas, Christos, et al.
Publicado: (2025)
Inside LockBit: Technical, Behavioral, and Financial Anatomy of a Ransomware Empire
por: Castaño, Felipe, et al.
Publicado: (2025)
por: Castaño, Felipe, et al.
Publicado: (2025)
Coding Malware in Fancy Programming Languages for Fun and Profit
por: Apostolopoulos, Theodoros, et al.
Publicado: (2025)
por: Apostolopoulos, Theodoros, et al.
Publicado: (2025)
Outside the Comfort Zone: Analysing LLM Capabilities in Software Vulnerability Detection
por: Guo, Yuejun, et al.
Publicado: (2024)
por: Guo, Yuejun, et al.
Publicado: (2024)
Assessing the Impact of Packing on Machine Learning-Based Malware Detection and Classification Systems
por: Gibert, Daniel, et al.
Publicado: (2024)
por: Gibert, Daniel, et al.
Publicado: (2024)
Addressing malware family concept drift with triplet autoencoder
por: Guldemir, Numan Halit, et al.
Publicado: (2025)
por: Guldemir, Numan Halit, et al.
Publicado: (2025)
A survey on hardware-based malware detection approaches
por: Chenet, Cristiano Pegoraro, et al.
Publicado: (2023)
por: Chenet, Cristiano Pegoraro, et al.
Publicado: (2023)
Feature graph construction with static features for malware detection
por: Zou, Binghui, et al.
Publicado: (2024)
por: Zou, Binghui, et al.
Publicado: (2024)
Certifiably robust malware detectors by design
por: Gimenez, Pierre-Francois, et al.
Publicado: (2025)
por: Gimenez, Pierre-Francois, et al.
Publicado: (2025)
secml-malware: Pentesting Windows Malware Classifiers with Adversarial EXEmples in Python
por: Demetrio, Luca, et al.
Publicado: (2021)
por: Demetrio, Luca, et al.
Publicado: (2021)
Tarallo: Evading Behavioral Malware Detectors in the Problem Space
por: Digregorio, Gabriele, et al.
Publicado: (2025)
por: Digregorio, Gabriele, et al.
Publicado: (2025)
Analysing Multidisciplinary Approaches to Fight Large-Scale Digital Influence Operations
por: Arroyo, David, et al.
Publicado: (2025)
por: Arroyo, David, et al.
Publicado: (2025)
Stealth by Conformity: Evading Robust Aggregation through Adaptive Poisoning
por: McGaughey, Ryan, et al.
Publicado: (2025)
por: McGaughey, Ryan, et al.
Publicado: (2025)
Cryptic Bytes: WebAssembly Obfuscation for Evading Cryptojacking Detection
por: Harnes, Håkon, et al.
Publicado: (2024)
por: Harnes, Håkon, et al.
Publicado: (2024)
Android App Feature Extraction: A review of approaches for malware and app similarity detection
por: Torka, Simon, et al.
Publicado: (2024)
por: Torka, Simon, et al.
Publicado: (2024)
A novel pattern recognition system for detecting Android malware by analyzing suspicious boot sequences
por: Vidal, Jorge Maestre, et al.
Publicado: (2024)
por: Vidal, Jorge Maestre, et al.
Publicado: (2024)
ActDroid: An active learning framework for Android malware detection
por: Muzaffar, Ali, et al.
Publicado: (2024)
por: Muzaffar, Ali, et al.
Publicado: (2024)
How Query Distribution Knowledge Breaks Multidimensional Encrypted Range Queries, With Guarantees
por: Blackley, Daniel, et al.
Publicado: (2025)
por: Blackley, Daniel, et al.
Publicado: (2025)
Algorithmic Complexity Attacks on Dynamic Learned Indexes
por: Yang, Rui, et al.
Publicado: (2024)
por: Yang, Rui, et al.
Publicado: (2024)
When AIOps Become "AI Oops": Subverting LLM-driven IT Operations via Telemetry Manipulation
por: Pasquini, Dario, et al.
Publicado: (2025)
por: Pasquini, Dario, et al.
Publicado: (2025)
Reassessing feature-based Android malware detection in a contemporary context
por: Muzaffar, Ali, et al.
Publicado: (2023)
por: Muzaffar, Ali, et al.
Publicado: (2023)
Evading Black-box Classifiers Without Breaking Eggs
por: Debenedetti, Edoardo, et al.
Publicado: (2023)
por: Debenedetti, Edoardo, et al.
Publicado: (2023)
TENNOR: Trustworthy Execution for Neural Networks through Obliviousness and Retrievals
por: Qu, Zifan, et al.
Publicado: (2026)
por: Qu, Zifan, et al.
Publicado: (2026)
AppPoet: Large Language Model based Android malware detection via multi-view prompt engineering
por: Zhao, Wenxiang, et al.
Publicado: (2024)
por: Zhao, Wenxiang, et al.
Publicado: (2024)
Global BGP Attacks that Evade Route Monitoring
por: Birge-Lee, Henry, et al.
Publicado: (2024)
por: Birge-Lee, Henry, et al.
Publicado: (2024)
Exposing Privacy Risks in Anonymizing Clinical Data: Combinatorial Refinement Attacks on k-Anonymity Without Auxiliary Information
por: Chhillar, Somiya, et al.
Publicado: (2025)
por: Chhillar, Somiya, et al.
Publicado: (2025)
LLMmap: Fingerprinting For Large Language Models
por: Pasquini, Dario, et al.
Publicado: (2024)
por: Pasquini, Dario, et al.
Publicado: (2024)
Hacking Back the AI-Hacker: Prompt Injection as a Defense Against LLM-driven Cyberattacks
por: Pasquini, Dario, et al.
Publicado: (2024)
por: Pasquini, Dario, et al.
Publicado: (2024)
TH-Bench: Evaluating Evading Attacks via Humanizing AI Text on Machine-Generated Text Detectors
por: Zheng, Jingyi, et al.
Publicado: (2025)
por: Zheng, Jingyi, et al.
Publicado: (2025)
A Wolf in Sheep's Clothing: Practical Black-box Adversarial Attacks for Evading Learning-based Windows Malware Detection in the Wild
por: Ling, Xiang, et al.
Publicado: (2024)
por: Ling, Xiang, et al.
Publicado: (2024)
Watch Out! Simple Horizontal Class Backdoor Can Trivially Evade Defense
por: Ma, Hua, et al.
Publicado: (2023)
por: Ma, Hua, et al.
Publicado: (2023)
Evading Data Provenance in Deep Neural Networks
por: Zhu, Hongyu, et al.
Publicado: (2025)
por: Zhu, Hongyu, et al.
Publicado: (2025)
Securing the Digital World: Protecting smart infrastructures and digital industries with Artificial Intelligence (AI)-enabled malware and intrusion detection
por: Schmitt, Marc
Publicado: (2023)
por: Schmitt, Marc
Publicado: (2023)
Comprehensive evaluation of Mal-API-2019 dataset by machine learning in malware detection
por: Li, Zhenglin, et al.
Publicado: (2024)
por: Li, Zhenglin, et al.
Publicado: (2024)
AuthorMist: Evading AI Text Detectors with Reinforcement Learning
por: David, Isaac, et al.
Publicado: (2025)
por: David, Isaac, et al.
Publicado: (2025)
EvadeDroid: A Practical Evasion Attack on Machine Learning for Black-box Android Malware Detection
por: Bostani, Hamid, et al.
Publicado: (2021)
por: Bostani, Hamid, et al.
Publicado: (2021)
Ejemplares similares
-
QRS: A Rule-Synthesizing Neuro-Symbolic Triad for Autonomous Vulnerability Discovery
por: Tsigkourakos, George, et al.
Publicado: (2026) -
Just in Plain Sight: Unveiling CSAM Distribution Campaigns on the Clear Web
por: Lykousas, Nikolaos, et al.
Publicado: (2025) -
The Malware as a Service ecosystem
por: Patsakis, Constantinos, et al.
Publicado: (2024) -
Assessing LLMs in Malicious Code Deobfuscation of Real-world Malware Campaigns
por: Patsakis, Constantinos, et al.
Publicado: (2024) -
Hello, won't you tell me your name?: Investigating Anonymity Abuse in IPFS
por: Karapapas, Christos, et al.
Publicado: (2025)