Tao Wang - RankMe

24 papers A* 2Journal 22

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Make Identity Indistinguishable: Utility-Preserving Face Dataset Publication With Provable Privacy Guarantees. IEEE Trans. Pattern Anal. Mach. Intell. Yushu Zhang, Junhao Ji, Tao Wang, Ruoyu Zhao, Wenying Wen, Yong Xiang
2025	J	`jnl`	A Comprehensive Image Protection Framework Based on High-Capacity Adversarial Data Hiding. IEEE Trans. Big Data Ming Li, Wenwen Zhou, Tao Wang, Yushu Zhang, Wenying Wen
2025	J	`jnl`	Beyond Privacy: Generating Privacy-Preserving Faces Supporting Robust Image Authentication. IEEE Trans. Inf. Forensics Secur. Tao Wang, Wenying Wen, Xiangli Xiao, Zhongyun Hua, Yushu Zhang, Yuming Fang
2025	J	`jnl`	Controllable facial protection against malicious translation-based attribute editing. Knowl. Based Syst. Yiyi Xie, Yuqian Zhou, Tao Wang, Zhongyun Hua, Wenying Wen, Shuang Yi, Yushu Zhang
2025	J	`jnl`	Detecting Malicious Concepts Without Image Generation in AIGC. CoRR Kun Xu, Yushu Zhang, Shuren Qi, Tao Wang, Wenying Wen, Yuming Fang
2025	J	`jnl`	Make Identity Unextractable yet Perceptible: Synthesis-Based Privacy Protection for Subject Faces in Photos. CoRR Tao Wang, Yushu Zhang, Xiangli Xiao, Kun Xu, Lin Yuan, Wenying Wen, Yuming Fang
2025	J	`jnl`	Privacy-preserving face attribute classification via differential privacy. Neurocomputing Xiaoting Zhang, Tao Wang, Junhao Ji, Yushu Zhang, Rushi Lan
2025	J	`jnl`	Security and Privacy on Generative Data in AIGC: A Survey. ACM Comput. Surv. Tao Wang, Yushu Zhang, Shuren Qi, Ruoyu Zhao, Zhihua Xia, Jian Weng
2025	J	`jnl`	Seeing is Not Believing: An Identity Hider for Human Vision Privacy Protection. IEEE Trans. Biom. Behav. Identity Sci. Tao Wang, Yushu Zhang, Zixuan Yang, Xiangli Xiao, Hua Zhang, Zhongyun Hua
2025	J	`jnl`	Tailor-Made Face Privacy Protection via Class-Wise Targeted Universal Adversarial Perturbations. IEEE Trans. Dependable Secur. Comput. Yushu Zhang, Zixuan Yang, Tao Wang, Zhongyun Hua, Jian Weng
2025	J	`jnl`	Visual Content Privacy Protection: A Survey. ACM Comput. Surv. Ruoyu Zhao, Yushu Zhang, Tao Wang, Wenying Wen, Yong Xiang, Xiaochun Cao
2024	J	`jnl`	Dual Protection for Image Privacy and Copyright via Traceable Adversarial Examples. IEEE Trans. Circuits Syst. Video Technol. Ming Li, Zhaohui Yang, Tao Wang, Yushu Zhang, Wenying Wen
2024	J	`jnl`	Image Privacy Protection: A Survey. CoRR Wenying Wen, Ziye Yuan, Yushu Zhang, Tao Wang, Xiangli Xiao, Ruoyu Zhao, Yuming Fang
2024	A*	`conf`	Make Privacy Renewable! Generating Privacy-Preserving Faces Supporting Cancelable Biometric Recognition. ACM Multimedia Tao Wang, Yushu Zhang, Xiangli Xiao, Lin Yuan, Zhihua Xia, Jian Weng
2024	A*	`conf`	Once-for-all: Efficient Visual Face Privacy Protection via Person-specific Veils. ACM Multimedia Zixuan Yang, Yushu Zhang, Tao Wang, Zhongyun Hua, Zhihua Xia, Jian Weng
2024	J	`jnl`	Reversible gender privacy enhancement via adversarial perturbations. Neural Networks Yiyi Xie, Yuqian Zhou, Tao Wang, Wenying Wen, Shuang Yi, Yushu Zhang
2024	J	`jnl`	Utility-Enhanced Image Obfuscation With Block Differential Privacy. IEEE Signal Process. Lett. Junhao Ji, Ruoyu Zhao, Tao Wang, Youwen Zhu
2023	J	`jnl`	Face Database Protection via Beautification with Chaotic Systems. Entropy Tao Wang, Yushu Zhang, Ruoyu Zhao
2023	J	`jnl`	Identifiable Face Privacy Protection via Virtual Identity Transformation. IEEE Signal Process. Lett. Tao Wang, Yushu Zhang, Ruoyu Zhao, Wenying Wen, Rushi Lan
2023	J	`jnl`	RAPP: Reversible Privacy Preservation for Various Face Attributes. IEEE Trans. Inf. Forensics Secur. Yushu Zhang, Tao Wang, Ruoyu Zhao, Wenying Wen, Youwen Zhu
2023	J	`jnl`	Security and Privacy on Generative Data in AIGC: A Survey. CoRR Tao Wang, Yushu Zhang, Shuren Qi, Ruoyu Zhao, Zhihua Xia, Jian Weng
2023	J	`jnl`	Seeing is not Believing: An Identity Hider for Human Vision Privacy Protection. CoRR Tao Wang, Yushu Zhang, Zixuan Yang, Hua Zhang, Zhongyun Hua
2023	J	`jnl`	Visual Content Privacy Protection: A Survey. CoRR Ruoyu Zhao, Yushu Zhang, Tao Wang, Wenying Wen, Yong Xiang, Xiaochun Cao
2021	J	`jnl`	A novel deep recommend model based on rating matrix and item attributes. J. Intell. Inf. Syst. Liping Sun, Xiaoqing Liu, Yuanjun Liu, Tao Wang, Liangmin Guo, Xiaoyao Zheng, Yonglong Luo

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.