Faqian Guan - RankMe

16 papers B 1Journal 11Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	T-MIA: A membership inference attack via timing side-channel and possible defense scheme. Inf. Sci. Kai Sheng, Faqian Guan, Wei Ren, Tianqing Zhu
2025	J	`jnl`	Attention-Based Membership Inference Attacks on Graph Neural Network Through Topological Features. IEEE Trans. Dependable Secur. Comput. Faqian Guan, Tianqing Zhu, Hanjin Tong, Wanlei Zhou
2025	J	`jnl`	Graph Unlearning: Efficient Node Removal in Graph Neural Networks. CoRR Faqian Guan, Tianqing Zhu, Zhoutian Wang, Wei Ren, Wanlei Zhou
2025	J	`jnl`	Large Language Models Merging for Enhancing the Link Stealing Attack on Graph Neural Networks. IEEE Trans. Dependable Secur. Comput. Faqian Guan, Tianqing Zhu, Wenhan Chang, Wei Ren, Wanlei Zhou
2025	J	`jnl`	Large Language Models for Link Stealing Attacks Against Graph Neural Networks. IEEE Trans. Big Data Faqian Guan, Tianqing Zhu, Hui Sun, Wanlei Zhou, Philip S. Yu
2025	—	`conf`	Neighbor Information Fusion with a Real-Time Update Strategy for Unsupervised Person Re-Identification. BIBM Yongyi Xiao, Faqian Guan, Jiayan Huang, Antoni Grau
2025	J	`jnl`	Topology-Based Node-Level Membership Inference Attacks on Graph Neural Networks. IEEE Trans. Big Data Faqian Guan, Tianqing Zhu, Wanlei Zhou, Philip S. Yu
2024	J	`jnl`	A realistic model extraction attack against graph neural networks. Knowl. Based Syst. Faqian Guan, Tianqing Zhu, Hanjin Tong, Wanlei Zhou
2024	—	`conf`	Defense Against Graph Injection Attack in Graph Neural Networks. DSC Hanjin Tong, Tianqing Zhu, Faqian Guan, Wanlei Zhou
2024	J	`jnl`	Graph neural networks: a survey on the links between privacy and security. Artif. Intell. Rev. Faqian Guan, Tianqing Zhu, Wanlei Zhou, Kim-Kwang Raymond Choo
2024	J	`jnl`	Large Language Models Merging for Enhancing the Link Stealing Attack on Graph Neural Networks. CoRR Faqian Guan, Tianqing Zhu, Wenhan Chang, Wei Ren, Wanlei Zhou
2024	J	`jnl`	Large Language Models for Link Stealing Attacks Against Graph Neural Networks. CoRR Faqian Guan, Tianqing Zhu, Hui Sun, Wanlei Zhou, Philip S. Yu
2024	J	`jnl`	Topology modification against membership inference attack in Graph Neural Networks. Knowl. Based Syst. Faqian Guan, Tianqing Zhu, Hanjin Tong, Wanlei Zhou
2019	B	`conf`	A GAN Model With Self-attention Mechanism To Generate Multi-instruments Symbolic Music. IJCNN Faqian Guan, Chunyan Yu, Suqiong Yang
2019	—	`conf`	Non-parallel Many-to-many Singing Voice Conversion by Adversarial Learning. APSIPA Jinsen Hu, Chunyan Yu, Faqian Guan
2018	—	`conf`	Convolutional Neural Networks with Multi-task Loss for Polyphonic Sound Event Detection. CSAE Huang Liu, Xiu Wang, Faqian Guan, Jinsen Hu

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.