Computer Security. ESORICS 2024 International Workshops SECAI, DisA, CPS4CIP, and SecAssure, Bydgoszcz, Poland, September 16–20, 2024, Revised Selected Papers, Part II /
This two-volume set LNCS 15263 and LNCS 15264 constitutes the refereed proceedings of eleven International Workshops which were held in conjunction with the 29th European Symposium on Research in Computer Security, ESORICS 2024, held in Bydgoszcz, Poland, during September 16–20, 2024. The papers inc...
I tiakina i:
| Kaituhi rangatōpū: | |
|---|---|
| Ētahi atu kaituhi: | , , , , , , , , , , , , , , , , |
| Hōputu: | Tāhiko īPukapuka |
| Reo: | Ingarihi |
| I whakaputaina: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
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| Putanga: | 1st ed. 2025. |
| Rangatū: | Lecture Notes in Computer Science,
15264 |
| Ngā marau: | |
| Urunga tuihono: | https://doi.org/10.1007/978-3-031-82362-6 |
| Ngā Tūtohu: |
Tāpirihia he Tūtohu
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
|
Rārangi ihirangi:
- SECAI PAPERS: Feasibility Study for Supporting Static Malware Analysis Using LLM
- PSY: Posterior Sampling Based Privacy Enhancer in Large Language Models
- Systematic Bug Reproduction with Large Language Model
- BOTracle: A framework for Discriminating Bots and Humans
- Deep Learning for Network Anomaly Detection under Data Contamination: Evaluating Robustness and Mitigating Performance Degradation
- On Intrinsic Cause and Defense of Adversarial Examples in Deep Neural Networks
- Effects of Poisoning Attacks on Causal Deep Reinforcement Learning
- Generating Traffic-Level Adversarial Examples from Feature-Level Specifications
- PhishCoder: Efficient Extraction of Contextual Information from Phishing Emails
- .On the Robustness of Malware Detectors to Adversarial Samples
- Towards AI-Based Identification of Publicly Known Vulnerabilities
- Machine Learning-Based Secure Malware Detection using Features from Binary Executable Headers
- Improving Adversarial Robustness in Android Malware Detection by Reducing the Impact of Spurious Correlations
- Multi-Objective Evolutionary Algorithm for Automatic Generation of Adversarial Metamorphic Malware
- A RAG-Based Question-Answering Solution for Cyber-Attack Investigation and Attribution. DisA PAPERS: Recognition of Remakes and Fake Facial Images
- A Novel Method of Improving Intrusion Detection Systems Robustness Against Adversarial Attacks, through Feature Omission and a Committee of Classifiers
- Proposition of a Novel Type of Attacks Targeting Explainable AI Algorithms in Cybersecurity
- Data structures towards the recognition of fake news and disinformation written in Polish. CPS4CIP PAPERS: Characterizing Prediction Model Responses to Attack Inputs: A Study with Time-Series Power Consumption Data
- Best Practices - based Training for Improving Cybersecurity in Power Grids
- Proactive Cyber Security Strategies for Securing Critical National Infrastructure
- Weaponizing Disinformation Against Critical Infrastructures. SecAssure PAPERS: Compliance-driven CWE Assessment by Semantic Similarity
- Enabling Android Application Monitoring by Characterizing Security-Critical Code Fragments
- MITRE-Based APT Attack Generation and Prediction
- Assuring Privacy of AI-Powered Community Driven Android Code Vulnerability Detection
- Formalizing Federated Learning and Differential Privacy for GIS systems in IIIf
- AI-Assisted Assurance Profile Creation for System Security Assurance
- Attack to Defend: Gamifying the MITRE ATT&CK for Cyber Security Training using the COFELET Framework
- Canary in the Coal Mine: Identifying Cyber Threat Trends through Topic Mining
- Stack Overflow Case Study.