{"product_id":"computer-security-esorics-2025-9783032078834","title":"Computer Security  ESORICS 2025","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e.- Time-Distributed Backdoor Attacks on Federated Spiking Learning.\u003cbr\u003e.- TATA: Benchmark NIDS Test Sets Assessment and Targeted Augmentation.\u003cbr\u003e.- Abuse-Resistant Evaluation of AI-as-a-Service via Function-Hiding Homomorphic Signatures.\u003cbr\u003e.- PriSM: A Privacy-friendly Support vector Machine.\u003cbr\u003e.- Towards Context-Aware Log Anomaly Detection Using Fine-Tuned Large Language Models.\u003cbr\u003e.- PROTEAN: Federated Intrusion Detection in Non-IID Environments through Prototype-Based Knowledge Sharing.\u003cbr\u003e.- KeTS: Kernel-based Trust Segmentation against Model Poisoning Attacks.\u003cbr\u003e.- Machine Learning Vulnerabilities in 6G: Adversarial Attacks and Their Impact on Channel Gain Prediction and Resource Allocation in UC-CF-mMIMO.\u003cbr\u003e.- FuncVul: An Effective Function Level Vulnerability Detection Model using LLM and Code Chunk.\u003cbr\u003e.- LUMIA: Linear probing for Unimodal and MultiModal Membership Inference Attacks leveraging internal LLM states.\u003cbr\u003e.- Membership Privacy Evaluation in Deep Spiking Neural Networks.\u003cbr\u003e.- DUMB and DUMBer: Is Adversarial Training Worth It in the Real World?.\u003cbr\u003e.- Countering Jailbreak Attacks with Two-Axis Pre-Detection and Conditional Warning Wrappers.\u003cbr\u003e.- How Dataset Diversity Affects Generalization in ML-based NIDS.\u003cbr\u003e.- Llama-based source code vulnerability detection: Prompt engineering vs Finetuning. \u003cbr\u003e.- DBBA: Diffusion-based Backdoor Attacks on Open-set Face Recognition Models.\u003cbr\u003e.- Evaluation of Autonomous Intrusion Response Agents In Adversarial and Normal Scenarios.\u003cbr\u003e.- Trigger-Based Fragile Model Watermarking for Image Transformation Networks.\u003cbr\u003e.- Let the Noise Speak: Harnessing Noise for a Unified Defense Against Adversarial and Backdoor Attacks.\u003cbr\u003e.- On the Adversarial Robustness of Graph Neural Networks with Graph Reduction.\u003cbr\u003e.- SecureT2I: No More Unauthorized Manipulation on AI Generated Images from Prompts.\u003cbr\u003e.- GANSec: Enhancing Supervised Wireless Anomaly Detection Robustness through Tailored Conditional GAN Augmentation.\u003cbr\u003e.- Fine-Grained Data Poisoning Attack to Local Differential Privacy Protocols for Key-Value Data.\u003cbr\u003e.- The DCR Delusion: Measuring the Privacy Risk of Synthetic Data.\u003cbr\u003e.- StructTransform: A Scalable Attack Surface for Safety-Aligned Large Language Models.\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Default Title","offer_id":52151401775447,"sku":"9783032078834","price":64.99,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/computer-security-esorics-2025-9783032078834","provider":"Book Curl","version":"1.0","type":"link"}