Detection of Intrusions and Malware, and Vulnerability Assessment, Kartoniert / Broschiert
Detection of Intrusions and Malware, and Vulnerability Assessment
- 22nd International Conference, DIMVA 2025, Graz, Austria, July 9-11, 2025, Proceedings, Part I
(soweit verfügbar beim Lieferanten)
- Herausgeber:
- Manuel Egele, Veelasha Moonsamy, Daniel Gruss, Michele Carminati
- Verlag:
- Springer, 07/2025
- Einband:
- Kartoniert / Broschiert
- Sprache:
- Englisch
- ISBN-13:
- 9783031976193
- Artikelnummer:
- 12358982
- Umfang:
- 316 Seiten
- Gewicht:
- 482 g
- Maße:
- 235 x 155 mm
- Stärke:
- 18 mm
- Erscheinungstermin:
- 10.7.2025
- Hinweis
-
Achtung: Artikel ist nicht in deutscher Sprache!
Weitere Ausgaben von Detection of Intrusions and Malware, and Vulnerability Assessment |
Preis |
|---|---|
| Buch, Kartoniert / Broschiert, Englisch | EUR 72,27* |
Klappentext
.- Web Security.
.- ScamFerret: Detecting Scam Websites Autonomously with Large Language Models.
.- Domain Name Encryption Does Not Ensure Privacy: Website Fingerprinting Attack With Only a Few Samples Using Siamese Network.
.- Making (Only) the Right Calls: Preventing Remote Code Execution Attacks in PHP Applications with Contextual, State-Sensitive System Call Filtering.
.- Poster: Generating the WEB-IDS23 Dataset.
.- Vulnerability Detection.
.- Sourcerer: channeling the void.
.- CodeGrafter: Unifying Source and Binary Graphs for Robust Vulnerability Detection.
.- SyzFroge: An Automated System Call Specification Generation Process for Efficient Kernel Fuzzing.
.- Poster: Machine Learning for Vulnerability Detection as Target Oracle in Automated Fuzz Driver Generation.
.- Side channels.
.- Reverse-Engineering the Address Translation Caches.
.- The HMB Timing Side Channel: Exploiting the SSD's Host Memory Buffer.
.- Cohere+Reload: Re-enabling High-Resolution Cache Attacks on AMD SEV-SNP.
.- Poster: Extracting Cryptographic Keys from Windows Live Processes.
.- Obfuscation.
.- Experimental Study of Binary Diffing Resilience on Obfuscated Programs.
.- Quantifying and Mitigating the Impact of Obfuscations on Machine-Learning-Based Decompilation Improvement.
.- Exploring the Potential of LLMs for Code Deobfuscation.
.- Poster: All Right Then, (Don't) Keep Your Secrets: Exposing API Hashing in Malware.
