Abstract-The increasing deployment of networked mobile embedded devices leads to unique challenges communications security. This is especially true for embedded biomedical devices and robotic materials handling, in which subversion or denial of service could result in loss of human life and other catastrophic outcomes. In this paper we present the Learning Intrusion Detection System (L-IDS), a network security service for protecting embedded mobile devices within institutional boundaries, which can be deployed alongside existing security systems with no modifications to the embedded devices. L-IDS utilizes the OpenFlow SoftwareDefined Networking architecture, which allows it to both detect and respond to attacks as they happen.
Skowyra et al. in REF present L-IDS, the Learning Intrusion Detection System that secures mobile devices with constrained hardware and CPU resources.
Software-Defined IDS for securing embedded mobile devices
2013 IEEE High Performance Extreme Computing Conference (HPEC)
2013 IEEE High Performance Extreme Computing Conference (HPEC)
Computer Science