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This book constitutes the refereed proceedings of the 14th International Conference on Security, Privacy, and Applied Cryptography Engineering, SPACE 2024, held in Kottayam, India, during December 14-17, 2024.
The 8 full papers, 10 short papers and 1 invited paper included in this book were carefully reviewed and selected from 43 submissions. They were organized in topical sections as follows: security, privacy, applied cryptographic engineering, integration of machine learning techniques, reflecting the growing prominence of this approach in contemporary research on security and cryptography, hardware security, the exploration of post-quantum cryptography, and the development of efficient implementations for emerging cryptographic primitives.
List of contents
.- Attacks and Countermeasures for Digital Microfluidic Biochips.
.- SideLink: Exposing NVLink to Covert- and Side-Channel Attacks.
.- Faster and more Energy-Efficient Equation Solvers over GF(2).
.- Transferability of Evasion Attacks Against FHE Encrypted Inference.
.- Security Analysis of ASCON Cipher under Persistent Faults.
.- Privacy-Preserving Graph-Based Machine Learning with Fully Homomorphic Encryption for Collaborative Anti-Money Laundering.
.- CoPrIME: Complete Process Isolation using Memory Encryption.
.- Online Testing Entropy and Entropy Tests with a Two State Markov Model.
.- DLShield: A Defense Approach against Dirty Label Attacks in Heterogeneous Federated Learning.
.- Benchmarking Backdoor Attacks on Graph Convolution Neural Networks: A Comprehensive Analysis of Poisoning Techniques.
.- Spatiotemporal Intrusion Detection Systems for IoT Networks.
.- High Speed High Assurance implementations of Mutivariate Quadratic based Signatures.
.- "There's always another counter": Detecting Micro-architectural Attacks in a Probabilistically Interleaved Malicious/Benign Setting.
.- FPGA-Based Acceleration of Homomorphic Convolution with Plaintext Kernels.
.- Post-Quantum Multi-Client Conjunctive Searchable Symmetric Encryption from Isogenies.
.- BlockDoor: Blocking Backdoor Based Watermarks in Deep Neural Networks.
.- Adversarial Malware Detection.
.- ML based Improved Differential Distinguisher with High Accuracy: Application to GIFT-128 and ASCON.
