Active Digital Twin Verification for Robust Federated Learning in IoT Intrusion Detection

Despite the dominance of Transformer-based models in software vulnerability detection, the extent to which their learned security logic generalizes across different programming languages remains a critical open question. To address this, we propose a comprehensive evaluation framework organized into three phases spanning five distinct experimental scenarios, aiming to rigorously dissect...

Security testing of REST APIs remains difficult because real-world OpenAPI specifications are often incomplete, many security flaws are inherently stateful, and prevailing stateful fuzzers still optimize primarily for structural exploration rather than OWASP-aligned risk categories. Based on this gap, this paper presents APIGFUZZ, a graph-driven, OWASP-aware black-box REST API fuzzing...