Qianyu Li - RankMe

11 papers A* 1B 1Journal 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	CryptDNN: A Fast Privacy-Preserving Deep Neural Network Inference Architecture Based on Cloud-Edge-Client Collaboration. IEEE Trans. Netw. Sci. Eng. Dong Li, Anupam Chattopadhyay, Qianyu Li, Qingguo Lü, Jiahui Wu, Tao Xiang, Xiaofeng Liao
2026	J	`jnl`	Mimi: Dynamically Secure Multi-Keyword Retrieval Scheme With Two-Factor Verification. IEEE Trans. Dependable Secur. Comput. Dong Li, Anupam Chattopadhyay, Qianyu Li, Jiahui Wu, Qingguo Lü, Bowen Xing, Tao Xiang, Xiaofeng Liao
2024	J	`jnl`	An Intelligent Penetration Testing Method Using Human Feedback. IEEE Trans. Ind. Informatics Qianyu Li, Ruipeng Wang, Min Zhang, Fan Shi, Yi Shen, Miao Hu, Bingyang Guo, Chengxi Xu
2024	J	`jnl`	DynPen: Automated Penetration Testing in Dynamic Network Scenarios Using Deep Reinforcement Learning. IEEE Trans. Inf. Forensics Secur. Qianyu Li, Ruipeng Wang, Dong Li, Fan Shi, Min Zhang, Anupam Chattopadhyay, Yi Shen, Yang Li
2023	J	`jnl`	A hierarchical deep reinforcement learning model with expert prior knowledge for intelligent penetration testing. Comput. Secur. Qianyu Li, Min Zhang, Yi Shen, Ruipeng Wang, Miao Hu, Yang Li, Hao Hao
2023	A*	`conf`	AlphaEXP: An Expert System for Identifying Security-Sensitive Kernel Objects. USENIX Security Symposium Ruipeng Wang, Kaixiang Chen, Chao Zhang, Zulie Pan, Qianyu Li, Siliang Qin, Shenglin Xu, Min Zhang, Yang Li
2023	J	`jnl`	BD-CVSA: A Broadband Direction Finding Method Based on Constructing Virtual Sparse Arrays. Signal Process. Min Zhang, Cheng Tu, Wenli Zhu, Chenxi Wu, Qianyu Li, Chenyang Wang, Hongjun Wang
2023	J	`jnl`	INNES: An intelligent network penetration testing model based on deep reinforcement learning. Appl. Intell. Qianyu Li, Miao Hu, Hao Hao, Min Zhang, Yang Li
2023	J	`jnl`	Sparse reward for reinforcement learning-based continuous integration testing. J. Softw. Evol. Process. Yang Yang, Zheng Li, Ying Shang, Qianyu Li
2023	J	`jnl`	Tunter: Assessing Exploitability of Vulnerabilities with Taint-Guided Exploitable States Exploration. Comput. Secur. Ruipeng Wang, Kaixiang Chen, Zulie Pan, Yuwei Li, Qianyu Li, Yang Li, Min Zhang, Chao Zhang
2020	B	`conf`	Occurrence Frequency and All Historical Failure Information Based Method for TCP in CI. ICSSP Ying Shang, Qianyu Li, Yang Yang, Zheng Li

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.