Fast and Effective Clustering of Spam Emails Based on Structural Similarity. - Mina Sheikhalishahi; Andrea Saracino; Mohamed Mejri; Nadia Tawbi; Fabio Martinelli (FPS, 2015)

Clustering Spam Emails into Campaigns. - Mina Sheikh Alishahi; Mohamed Mejri; Nadia Tawbi (ICISSP, 2015)

Digital Waste Sorting: A Goal-Based, Self-Learning Approach to Label Spam Email Campaigns. - Mina Sheikhalishahi; Andrea Saracino; Mohamed Mejri; Nadia Tawbi; Fabio Martinelli (STM, 2015)

Collaborative Attribute Retrieval in Environment with Faulty Attribute Managers. - Mario Faiella; Fabio Martinelli; Paolo Mori; Andrea Saracino; Mina Sheikhalishahi (ARES, 2016)

MalProfiler: Automatic and Effective Classification of Android Malicious Apps in Behavioral Classes. - Antonio La Marra; Fabio Martinelli; Andrea Saracino; Mina Sheikhalishahi (FPS, 2016)

Privacy-Aware Data Sharing in a Tree-Based Categorical Clustering Algorithm. - Mina Sheikhalishahi; Mohamed Mejri; Nadia Tawbi; Fabio Martinelli (FPS, 2016)

On the Abstraction of a Categorical Clustering Algorithm. - Mina Sheikhalishahi; Mohamed Mejri; Nadia Tawbi (MLDM, 2016)

Modeling Privacy Aware Information Sharing Systems: A Formal and General Approach. - Fabio Martinelli; Andrea Saracino; Mina Sheikhalishahi (Trustcom/BigDataSE/ISPA, 2016)

Privacy-Utility Feature Selection as a tool in Private Data Classification. - Mina Sheikhalishahi; Fabio Martinelli (DCAI, 2017)

Privacy-preserving text mining as a service. - Gianpiero Costantino; Antonio La Marra; Fabio Martinelli; Andrea Saracino; Mina Sheikhalishahi (ISCC, 2017)

Privacy preserving clustering over horizontal and vertical partitioned data. - Mina Sheikhalishahi; Fabio Martinelli (ISCC, 2017)

A Distributed Framework for Collaborative and Dynamic Analysis of Android Malware. - Mario Faiella; Antonio La Marra; Fabio Martinelli; Francesco Mercaldo; Andrea Saracino; Mina Sheikhalishahi (PDP, 2017)

Try Walking in My Shoes, if You Can: Accurate Gait Recognition Through Deep Learning. - Giacomo Giorgi; Fabio Martinelli; Andrea Saracino; Mina Sheikhalishahi (SAFECOMP Workshops, 2017)

Privacy Preserving Hierarchical Clustering over Multi-party Data Distribution. - Mina Sheikhalishahi; Fabio Martinelli (SpaCCS, 2017)

Privacy-Utility Feature Selection as a Privacy Mechanism in Collaborative Data Classification. - Mina Sheikhalishahi; Fabio Martinelli (WETICE, 2017)

Privacy Preserving Random Decision Tree Classification Over Horizontally and Vertically Partitioned Data. - Fatemeh Khodaparast 002; Mina Sheikhalishahi; Hassan Haghighi; Fabio Martinelli (DASC/PiCom/DataCom/CyberSciTech, 2018)

Privacy Preserving Expectation Maximization (EM) Clustering Construction. - Mona Hamidi; Mina Sheikhalishahi; Fabio Martinelli (DCAI, 2018)

Secure Two-party Agglomerative Hierarchical Clustering Construction. - Mona Hamidi; Mina Sheikhalishahi; Fabio Martinelli (ICISSP, 2018)

Privacy Preserving Collaborative Agglomerative Hierarchical Clustering Construction. - Mina Sheikhalishahi; Mona Hamidi; Fabio Martinelli (ICISSP (Revised Selected Papers), 2018)

A Secure Distributed Framework for Agglomerative Hierarchical Clustering Construction. - Mona Hamidi; Mina Sheikhalishahi; Fabio Martinelli (PDP, 2018)

Walking Through the Deep: Gait Analysis for User Authentication Through Deep Learning. - Giacomo Giorgi; Fabio Martinelli; Andrea Saracino; Mina Sheikhalishahi (SEC, 2018)

Distributed Data Anonymization. - Fabio Martinelli; Mina Sheikh Alishahi (DASC/PiCom/DataCom/CyberSciTech, 2019)

Privacy-Preserving LDA Classification over Horizontally Distributed Data. - Fatemeh Khodaparast 002; Mina Sheikhalishahi; Hassan Haghighi; Fabio Martinelli (IDC, 2019)

On the Statistical Detection of Adversarial Instances over Encrypted Data. - Mina Sheikhalishahi; Majid Nateghizad; Fabio Martinelli; Zekeriya Erkin; Marco Loog (STM, 2019)

Privacy-Preserving Multi-Party Access Control. - Mina Sheikhalishahi; Gamze Tillem; Zekeriya Erkin; Nicola Zannone (WPES@CCS, 2019)

On the Comparison of Classifiers' Construction over Private Inputs. - Mina Sheikhalishahi; Nicola Zannone (TrustCom, 2020)

Privacy Preserving Statistical Detection of Adversarial Instances. - Mina Sheikhalishahi; Nicola Zannone (WETICE, 2020)

Digital Waste Disposal: an automated framework for analysis of spam emails. - Mina Sheikhalishahi; Andrea Saracino; Fabio Martinelli; Antonio La Marra; Mohammed Mejri; Nadia Tawbi (Int. J. Inf. Sec., 2020)

D-BRIDEMAID: A Distributed Framework for Collaborative and Dynamic Analysis of Android Malware. - Antonio La Marra; Fabio Martinelli; Francesco Mercaldo; Andrea Saracino; Mina Sheikhalishahi (J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl., 2020)

Not a Free Lunch, But a Cheap One: On Classifiers Performance on Anonymized Datasets. - Mina Alishahi; Nicola Zannone (DBSec, 2021)

Multi-Party Private Set Intersection Protocols for Practical Applications. - Aslí Bay; Zeki Erkin; Mina Alishahi; Jelle Vos (SECRYPT, 2021)

Comparing Classifiers' Performance under Differential Privacy. - Milan Lopuhaä-Zwakenberg; Mina Alishahi; Jeroen Kivits; Jordi Klarenbeek; Gert-Jan van der Velde; Nicola Zannone (SECRYPT, 2021)

Privacy-preserving policy evaluation in multi-party access control. - Mina Sheikhalishahi; Ischa Stork; Nicola Zannone (J. Comput. Secur., 2021)

Hide me Behind the Noise: Local Differential Privacy for Indoor Location Privacy. - Hojjat Navidan; Vahideh Moghtadaiee; Niki Nazaran; Mina Alishahi (EuroS&P Workshops, 2022)

Local Differential Privacy for Private Construction of Classification Algorithms. - Mina Alishahi; Daan Gast; Sam Vermeiren (NordSec, 2022)

Add noise to remove noise: Local differential privacy for feature selection. - Mina Alishahi; Vahideh Moghtadaiee; Hojjat Navidan (Comput. Secur., 2022)

On the privacy protection of indoor location dataset using anonymization. - Amir Fathalizadeh; Vahideh Moghtadaiee; Mina Alishahi (Comput. Secur., 2022)

Privacy preserving data sharing and analysis for edge-based architectures. - Mina Sheikhalishahi; Andrea Saracino; Fabio Martinelli; Antonio La Marra (Int. J. Inf. Sec., 2022)

Feature Selection on Anonymized Datasets. - Mina Alishahi; Vahideh Moghtadaiee (DASC/PiCom/CBDCom/CyberSciTech, 2023)

Pixels Who Violate Our Privacy! Deep Learning for Identifying Images' Key Pixels. - Carmen Veenker; Danny Opdam; Mina Alishahi (ESORICS Workshops (2), 2023)

BC-FL k-means: A Blockchain-based Framework for Federated Clustering. - Mina Alishahi; Wouter Leeuw; Nicola Zannone (TrustCom, 2023)

Autoencoder for Detecting Malicious Updates in Differentially Private Federated Learning. - Lucía Alonso; Mina Alishahi (SECRYPT, 2024)

Local Differential Privacy for Data Clustering. - Lisa Bruder; Mina Alishahi (SECRYPT, 2024)

Membership Inference Attacks Against Indoor Location Models. - Vahideh Moghtadaiee; Amir Fathalizadeh; Mina Alishahi (SECRYPT, 2024)

Indoor Location Fingerprinting Privacy: A Comprehensive Survey. - Amir Fathalizadeh; Vahideh Moghtadaiee; Mina Alishahi (CoRR, 2024)

Anonify: Decentralized Dual-level Anonymity for Medical Data Donation. - Sarah Abdelwahab Gaballah; Lamya Abdullah; Mina Alishahi; Thanh Hoang Long Nguyen; Ephraim Zimmer; Max Mühlhäuser; Karola Marky (Proc. Priv. Enhancing Technol., 2024)

Indoor Geo-Indistinguishability: Adopting Differential Privacy for Indoor Location Data Protection. - Amir Fathalizadeh; Vahideh Moghtadaiee; Mina Alishahi (IEEE Trans. Emerg. Top. Comput., 2024)

Federated Few-Shot Zone Learning for Indoor Localization. - Amir Fathalizadeh; Vahideh Moghtadaiee; Mina Alishahi (ICL-GNSS, 2025)

Learning Without Sharing: A Comparative Study of Federated Learning Models for Healthcare. - Anja Campmans; Mina Alishahi; Vahideh Moghtadaiee (SECRYPT, 2025)

From Real to Synthetic: GAN and DPGAN for Privacy Preserving Classifications. - Mohammad Emadi; Vahideh Moghtadaiee; Mina Alishahi (SECRYPT, 2025)

A survey and future outlook on indoor location fingerprinting privacy preservation. - Amir Fathalizadeh; Vahideh Moghtadaiee; Mina Alishahi (Comput. Networks, 2025)

Fed-GWAS: Privacy-preserving individualized incentive-based cross-device federated GWAS learning. - Omid Torki; Maede Ashouri-Talouki; Mina Alishahi (J. Inf. Secur. Appl., 2025)

Fair Play for Individuals, Foul Play for Groups? Auditing Anonymization's Impact on ML Fairness. - Héber Hwang Arcolezi; Mina Alishahi; Adda-Akram Bendoukha; Nesrine Kaaniche (CoRR, 2025)

Differentially private GANs for generating synthetic indoor location data. - Vahideh Moghtadaiee; Mina Alishahi; Milad Rabiei (Int. J. Inf. Sec., 2025)