Description

Book Synopsis

.- Time-Distributed Backdoor Attacks on Federated Spiking Learning.
.- TATA: Benchmark NIDS Test Sets Assessment and Targeted Augmentation.
.- Abuse-Resistant Evaluation of AI-as-a-Service via Function-Hiding Homomorphic Signatures.
.- PriSM: A Privacy-friendly Support vector Machine.
.- Towards Context-Aware Log Anomaly Detection Using Fine-Tuned Large Language Models.
.- PROTEAN: Federated Intrusion Detection in Non-IID Environments through Prototype-Based Knowledge Sharing.
.- KeTS: Kernel-based Trust Segmentation against Model Poisoning Attacks.
.- Machine Learning Vulnerabilities in 6G: Adversarial Attacks and Their Impact on Channel Gain Prediction and Resource Allocation in UC-CF-mMIMO.
.- FuncVul: An Effective Function Level Vulnerability Detection Model using LLM and Code Chunk.
.- LUMIA: Linear probing for Unimodal and MultiModal Membership Inference Attacks leveraging internal LLM states.
.- Membership Privacy Evaluation in Deep Spiking Neural Networks.
.- DUMB and DUMBer: Is Adversarial Training Worth It in the Real World?.
.- Countering Jailbreak Attacks with Two-Axis Pre-Detection and Conditional Warning Wrappers.
.- How Dataset Diversity Affects Generalization in ML-based NIDS.
.- Llama-based source code vulnerability detection: Prompt engineering vs Finetuning. 
.- DBBA: Diffusion-based Backdoor Attacks on Open-set Face Recognition Models.
.- Evaluation of Autonomous Intrusion Response Agents In Adversarial and Normal Scenarios.
.- Trigger-Based Fragile Model Watermarking for Image Transformation Networks.
.- Let the Noise Speak: Harnessing Noise for a Unified Defense Against Adversarial and Backdoor Attacks.
.- On the Adversarial Robustness of Graph Neural Networks with Graph Reduction.
.- SecureT2I: No More Unauthorized Manipulation on AI Generated Images from Prompts.
.- GANSec: Enhancing Supervised Wireless Anomaly Detection Robustness through Tailored Conditional GAN Augmentation.
.- Fine-Grained Data Poisoning Attack to Local Differential Privacy Protocols for Key-Value Data.
.- The DCR Delusion: Measuring the Privacy Risk of Synthetic Data.
.- StructTransform: A Scalable Attack Surface for Safety-Aligned Large Language Models.

Computer Security ESORICS 2025

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    A Paperback by Vincent Nicomette

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      Publisher: Springer
      Publication Date: 11/12/2025
      ISBN13: 9783032078834, 978-3032078834
      ISBN10: 3032078830

      Description

      Book Synopsis

      .- Time-Distributed Backdoor Attacks on Federated Spiking Learning.
      .- TATA: Benchmark NIDS Test Sets Assessment and Targeted Augmentation.
      .- Abuse-Resistant Evaluation of AI-as-a-Service via Function-Hiding Homomorphic Signatures.
      .- PriSM: A Privacy-friendly Support vector Machine.
      .- Towards Context-Aware Log Anomaly Detection Using Fine-Tuned Large Language Models.
      .- PROTEAN: Federated Intrusion Detection in Non-IID Environments through Prototype-Based Knowledge Sharing.
      .- KeTS: Kernel-based Trust Segmentation against Model Poisoning Attacks.
      .- Machine Learning Vulnerabilities in 6G: Adversarial Attacks and Their Impact on Channel Gain Prediction and Resource Allocation in UC-CF-mMIMO.
      .- FuncVul: An Effective Function Level Vulnerability Detection Model using LLM and Code Chunk.
      .- LUMIA: Linear probing for Unimodal and MultiModal Membership Inference Attacks leveraging internal LLM states.
      .- Membership Privacy Evaluation in Deep Spiking Neural Networks.
      .- DUMB and DUMBer: Is Adversarial Training Worth It in the Real World?.
      .- Countering Jailbreak Attacks with Two-Axis Pre-Detection and Conditional Warning Wrappers.
      .- How Dataset Diversity Affects Generalization in ML-based NIDS.
      .- Llama-based source code vulnerability detection: Prompt engineering vs Finetuning. 
      .- DBBA: Diffusion-based Backdoor Attacks on Open-set Face Recognition Models.
      .- Evaluation of Autonomous Intrusion Response Agents In Adversarial and Normal Scenarios.
      .- Trigger-Based Fragile Model Watermarking for Image Transformation Networks.
      .- Let the Noise Speak: Harnessing Noise for a Unified Defense Against Adversarial and Backdoor Attacks.
      .- On the Adversarial Robustness of Graph Neural Networks with Graph Reduction.
      .- SecureT2I: No More Unauthorized Manipulation on AI Generated Images from Prompts.
      .- GANSec: Enhancing Supervised Wireless Anomaly Detection Robustness through Tailored Conditional GAN Augmentation.
      .- Fine-Grained Data Poisoning Attack to Local Differential Privacy Protocols for Key-Value Data.
      .- The DCR Delusion: Measuring the Privacy Risk of Synthetic Data.
      .- StructTransform: A Scalable Attack Surface for Safety-Aligned Large Language Models.

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