Slips: Behavioral Evidence Aggregation for Network Security

Computer Science > Cryptography and Security [Submitted on 12 Aug 2026] Slips: Behavioral Evidence Aggregation for Network Security Sebastian Garcia, Veronica Valeros, Alya Gomaa, Ondřej Lukáš, Martin Řepa, Lukáš Forst, David Otta, František Střasák, Jan Svoboda, Dita Hollmannová Network intrusion detection systems often analyze individual packets or flows, although malicious behavior may develop across many connections and over time. This may limit their ability to combine isolated detections into a coherent assessment of host behavior. Packet-level features may also be too low-level for complex AI-based detection, requiring additional processing to improve accuracy while maintaining a low false-positive rate. We present Slips, a network intrusion detection system that builds host-centered behavioral profiles and organizes activity into time windows. It uses a modular architecture in which independent modules report evidence rather than generating final alerts directly. Slips then accumulates this evidence into host-level decisions. We evaluate Slips against Suricata on an expert-labeled PCAP dataset. At the profile-time-window level, Slips achieved 83% higher recall and a 70% higher F1 score than Suricata, while neither system produced false positives. These results indicate that time-window-based evidence accumulation can produce context-aware decisions that better align with expert judgment. Subjects: Cryptography and Security (cs.CR) Cite as: arXiv:2608.11979 [cs.CR]   (or arXiv:2608.11979v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2608.11979 Focus to learn more Submission history From: Veronica Valeros [view email] [v1] Wed, 12 Aug 2026 12:12:55 UTC (1,462 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-08 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)