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dimva 2025 : Conference on Detection of Intrusions and Malware & Vulnerability Assessment | |||||||||||||
Link: https://www.dimva.org/dimva2025/ | |||||||||||||
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Call For Papers | |||||||||||||
General Information
The annual DIMVA conference serves as a premier forum for advancing the state of the art in the broader areas of intrusion detection, malware analysis, and vulnerability assessment. Each year, DIMVA brings together international experts from academia, industry, and government to present and discuss novel research in these areas. DIMVA is organized by the special interest group Security - Intrusion Detection and Response (SIDAR) of the German Informatics Society (GI). The conference proceedings will appear in the Springer Lecture Notes in Computer Science (LNCS) series. Topics of Interest DIMVA solicits submissions of high-quality, original scientific papers presenting novel research on malware analysis, intrusion detection, vulnerability assessment, and related systems security topics. Topics of interest include, but are not limited to: Intrusions Novel approaches and domains Insider detection Prevention and response Data leakage, exfiltration, and poisoning Result correlation and cooperation Evasion and other attacks Potentials and limitation Operational experiences Privacy, legal, and social aspects Targeted attacks Analysis or detection of cryptocurrency heists Malware Automated analyses Behavioral models Prevention and containment Classification Lineage Forensics and recovery Underground economy Vulnerabilities in malware Financially targeted malware (e.g., ransomware, DeFi) Vulnerability detection Vulnerability prevention Vulnerability analysis Exploitation and defenses Hardware vulnerabilities Situational awareness Active probing Vulnerabilities in decentralized systems Papers will be judged on novelty, significance, correctness, and clarity. We expect all papers to provide enough details to enable reproducibility of the experimental results. We encourage papers that bridge research in different communities. We also welcome experience papers that clearly articulate lessons learnt. |
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