Zobrazeno 1 - 10
of 1 453 797
pro vyhledávání: '"A. Apt"'
Publikováno v:
APT Satellite Holdings Limited MarketLine Company Profile. 7/17/2023, p1-16. 16p.
Autor:
Xuan, Cho Do1 (AUTHOR) chodx@ptit.edu.vn, Nguyen, Tung Thanh2 (AUTHOR)
Publikováno v:
Scientific Reports. 9/30/2024, Vol. 14 Issue 1, p1-19. 19p.
Autor:
Borges de Almeida, Gonçalo1 (AUTHOR), Pascuzzo, Riccardo2 (AUTHOR) riccardo.pascuzzo@istituto-besta.it, Mambrin, Francesca3 (AUTHOR), Aquino, Domenico2 (AUTHOR), Verri, Mattia2 (AUTHOR), Moscatelli, Marco2 (AUTHOR), Del Bene, Massimiliano4 (AUTHOR), DiMeco, Francesco4,5,6 (AUTHOR), Silvani, Antonio7 (AUTHOR), Pollo, Bianca8 (AUTHOR), Grisoli, Marina2 (AUTHOR), Doniselli, Fabio Martino2 (AUTHOR)
Publikováno v:
Cancers. Sep2024, Vol. 16 Issue 17, p3014. 15p.
Autor:
Huang, Yi-Ting, Guo, Ying-Ren, Yang, Yu-Sheng, Wong, Guo-Wei, Jheng, Yu-Zih, Sun, Yeali, Modini, Jessemyn, Lynar, Timothy, Chen, Meng Chang
With the increasing sophistication of Advanced Persistent Threats (APTs), the demand for effective detection and mitigation strategies and methods has escalated. Program execution leaves traces in the system audit log, which can be analyzed to detect
Externí odkaz:
http://arxiv.org/abs/2411.13138
As Advanced Persistent Threats (APTs) grow increasingly sophisticated, the demand for effective detection methods has intensified. This study addresses the challenge of identifying APT campaign attacks through system event logs. A cascading approach,
Externí odkaz:
http://arxiv.org/abs/2410.22602
Autor:
Qiao, Wei, Feng, Yebo, Li, Teng, Zhang, Zijian, Xu, Zhengzi, Ma, Zhuo, Shen, Yulong, Ma, JianFeng, Liu, Yang
Advanced Persistent Threats (APTs) represent sophisticated cyberattacks characterized by their ability to remain undetected within the victim system for extended periods, aiming to exfiltrate sensitive data or disrupt operations. Existing detection a
Externí odkaz:
http://arxiv.org/abs/2410.17910
This paper investigates the application of Deep Reinforcement Learning (DRL) for attributing malware to specific Advanced Persistent Threat (APT) groups through detailed behavioural analysis. By analysing over 3500 malware samples from 12 distinct AP
Externí odkaz:
http://arxiv.org/abs/2410.11463
Autor:
Chen, Jun Yu, Gao, Tao
We present APT, an advanced Large Language Model (LLM)-driven framework that enables autonomous agents to construct complex and creative structures within the Minecraft environment. Unlike previous approaches that primarily concentrate on skill-based
Externí odkaz:
http://arxiv.org/abs/2411.17255
Publikováno v:
APT Bulletin: The Journal of Preservation Technology, 2024 Jan 01. 54(1/2), 79-80.
Externí odkaz:
https://www.jstor.org/stable/48796445