2025/02/12 by François De Keersmaeker, Rémi Van Boxem, De Keersmaeker, François +5
Computer Science · Social Sciences · #68M15 #C.2.3 #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Human Mobility and Location-Based Analysis #Network Security and Intrusion Detection #Networking and Internet Architecture (cs.NI) #Privacy, Security, and Data Protection
paper · pdf · doi:10.48550/arxiv.2502.08535
openalex publication_date 2025/02/12 · openalex created_date 2025/02/15 · openalex updated_date 2026/08/01
The widespread use of Smart Home devices has attracted significant research interest in understanding their behavior within home networks. Unlike general-purpose computers, these devices exhibit relatively simple and predictable network activity patterns. However, previous studies have primarily focused on normal network conditions, overlooking potential hidden patterns that emerge under challenging conditions. Discovering these hidden flows is crucial for assessing device robustness. This paper addresses this gap by presenting a framework that systematically and automatically reveals these hidden communication patterns. By actively disturbing communication and blocking observed traffic, the framework generates comprehensive profiles structured as behavior trees, uncovering flows that are missed by more shallow methods. This approach was applied to ten real-world devices, identifying 254 unique flows, with over 27% only discovered through this new method. These insights enhance our understanding of device robustness and can be leveraged to improve the accuracy of network security measures.