Zobrazeno 1 - 10
of 105
pro vyhledávání: '"PENG Guojun"'
Publikováno v:
网络与信息安全学报, Vol 10, Pp 66-80 (2024)
In recent years, a surge has been witnessed in cyber-attacks that leverage malicious Excel 4.0 macros (XLM) within documents. Malicious XLM codes often undergo complex obfuscation, posing a substantial challenge for conventional analysis methods and
Externí odkaz:
https://doaj.org/article/02eff001d853410d86eb85940d6f6b25
In this paper, we present PXoM, a practical technique to seamlessly retrofit XoM into stripped binaries on the x86-64 platform. As handling the mixture of code and data is a well-known challenge for XoM, most existing methods require the strict separ
Externí odkaz:
http://arxiv.org/abs/2412.02110
Different classes of safe reinforcement learning algorithms have shown satisfactory performance in various types of safety requirement scenarios. However, the existing methods mainly address one or several classes of specific safety requirement scena
Externí odkaz:
http://arxiv.org/abs/2407.05580
Autor:
Ma, Zeyuan, Guo, Hongshu, Chen, Jiacheng, Peng, Guojun, Cao, Zhiguang, Ma, Yining, Gong, Yue-Jiao
Recent research explores optimization using large language models (LLMs) by either iteratively seeking next-step solutions from LLMs or directly prompting LLMs for an optimizer. However, these approaches exhibit inherent limitations, including low op
Externí odkaz:
http://arxiv.org/abs/2403.01131
Autor:
Ma, Zeyuan, Guo, Hongshu, Chen, Jiacheng, Li, Zhenrui, Peng, Guojun, Gong, Yue-Jiao, Ma, Yining, Cao, Zhiguang
Recently, Meta-Black-Box Optimization with Reinforcement Learning (MetaBBO-RL) has showcased the power of leveraging RL at the meta-level to mitigate manual fine-tuning of low-level black-box optimizers. However, this field is hindered by the lack of
Externí odkaz:
http://arxiv.org/abs/2310.08252
Autor:
Song, Wenna, Ming, Jiang, Jiang, Lin, Yan, Han, Xiang, Yi, Chen, Yuan, Fu, Jianming, Peng, Guojun
Limited by the small keyboard, most mobile apps support the automatic login feature for better user experience. Therefore, users avoid the inconvenience of retyping their ID and password when an app runs in the foreground again. However, this auto-lo
Externí odkaz:
http://arxiv.org/abs/2103.03511
Publikováno v:
In Computers & Security February 2024 137
Anomaly detection is crucial to ensure the security of cyber-physical systems (CPS). However, due to the increasing complexity of CPSs and more sophisticated attacks, conventional anomaly detection methods, which face the growing volume of data and n
Externí odkaz:
http://arxiv.org/abs/2003.13213
Cryptocurrency malware detection in real-world environment: Based on multi-results stacking learning
Publikováno v:
In Applied Soft Computing Journal July 2022 124
Publikováno v:
In Journal of Transport Geography June 2020 86