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Edge computing that leverages cloud resources to the proximity of user devices is seen as the future infrastructure for distributed applications. However, developing and deploying edge applications, that rely on cellular networks, is burdensome. Such network infrastructures are often based on proprietary components, each with unique programming abstractions and interfaces. To facilitate straightforward deployment of edge applications, we introduce open-source software (OSS) based radio access network (RAN) on over-the-air (OTA) commercial spectrum with Development Operations (DevOps) capabilities. OSS allows software modifications and integrations of the system components, e.g., Evolved Packet Core (EPC) and edge hosts running applications, required for new data pipelines and optimizations not addressed in standardization. Such an OSS infrastructure enables further research and prototyping of novel end-user applications in an environment familiar to software engineers without telecommunications background. We evaluated the presented infrastructure with end-to-end (E2E) OTA testing, resulting in 7.5MB/s throughput and latency of 21ms, which shows that the presented infrastructure provides low latency for edge applications.

Description Logics (DLs) are knowledge representation and reasoning formalisms used in many settings. Among them, the EL family of DLs stands out due to the availability of polynomial-time inference algorithms and its ability to represent knowledge from domains such as medical informatics. However, the construction of an ontology is an errorprone process which often leads to unintended inferences. This paper presents the BEACON tool for debugging EL + ontologies. BEACON builds on earlier work relating minimal justifications (MinAs) of EL + ontologies and MUSes of a Horn formula, and integrates state-of-the-art algorithms for solving different function problems in the SAT domain.

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End-user-devices in the current cellular ecosystem are prone to many different vulnerabilities across different generations and protocol layers. Fixing these vulnerabilities retrospectively can be expensive, challenging, or just infeasible. A pragmatic approach for dealing with such a diverse set of vulnerabilities would be to identify attack attempts at runtime on the device side, and thwart them with mitigating and corrective actions. Towards this goal, in the paper we propose a general and extendable approach called PHOENIX for identifying nday cellular network control-plane vulnerabilities as well as dangerous practices of network operators from the device vantage point. PHOENIX monitors the device-side cellular network traffic for performing signature-based unexpected behavior detection through lightweight runtime verification techniques. Signatures in PHOENIX can be manually-crafted by a cellular network security expert or can be automatically synthesized using an optional component of PHOENIX, which reduces the signature synthesis problem to the language learning from the informant problem. Based on the corrective actions that are available to PHOENIX when an undesired behavior is detected, different instantiations of PHOENIX are possible: a full-fledged defense when deployed inside a baseband processor; a user warning system when deployed as a mobile application; a probe for identifying attacks in the wild. One such instantiation of PHOENIX was able to identify all 15 representative n-day vulnerabilities and unsafe practices of 4G LTE networks considered in our evaluation with a high packet processing speed (∼68000 packets/second) while inducing only a moderate amount of energy overhead (∼4mW).