Machine Learning Approaches -- PAC: Privacy-preserving Arrhythmia Classi cation with neural networks -- Ransomware Network Traffic Analysis for Pre-Encryption Alert -- Using Machine Learning to Detect Anomalies in Embedded Networks in Heavy Vehicles -- Selection and performance analysis of CICIDS2017 features importance -- Semantic Representation Based on Deep Learning for Spam Detection -- Interpreting Machine Learning Malware Detectors Which Leverage N-gram Analysis -- Labelled Network Capture Generation For Anomaly Detection -- Attack Prevention and Trustworthiness -- Lempel-Ziv Compression with Randomized Input-Output for Anti-Compression Side-Channel Attacks under HTTPS/TLS -- Secure Logging with Security against Adaptive Crash Attack -- Enroll, and Authentication will Follow: eID-based Enrollment for a Customized, Secure, and Frictionless Authentication Experience -- TATIS: Trustworthy APIs for Threat Intelligence Sharing with UMA and CP-ABE -- Protecting Android Apps from Repackaging Using Native Code -- Access Control Models and Cryptography -- Command Dependencies in Heuristic Safety Analysis of Access Control Models -- On Attribute Retrieval in ABAC -- Incorporating O -Line Attribute Delegation into Hierarchical Group and Attribute-Based Access Control -- U-EPS: An Ultra-small and Efficient Post-quantum Signature Scheme -- An Efficient Identification Scheme Based on Rank Metric -- Security Analysis of Auctionity: a blockchain based e-auction -- Dynamic Searchable Encryption with Access Control -- Short Papers -- Get-your-ID: Decentralized Proof of Identity -- Towards secure TMIS protocols -- Detecting Ransomware in Encrypted Web Traffic -- Digital forensics in vessel transportation systems -- A Privacy Protection Layer for Wearable Devices -- Validating the DFA Attack Resistance of AES -- A rejection-based approach for detecting SQL injection vulnerabilities in Web applications -- Lightweight IoT Mutual Authentication Scheme based on Transient Identities and Transactions History -- Towards Privacy-Aware Smart Surveillance.

This book constitutes the revised selected papers of the 12th International Symposium on Foundations and Practice of Security, FPS 2019, held in Toulouse, France, in November 2019. The 19 full papers and 9 short papers presented in this book were carefully reviewed and selected from 50 submissions. They cover a range of topics such as machine learning approaches; attack prevention and trustworthiness; and access control models and cryptography.