Abstract
Network Security Systems are heavily anchored in the digital plane of “cyber space” and hence cannot be used effectively to derive the physical identity of an intruder in order to prevent further malicious wireless broadcasts (i.e., escorting an intruder off the premises based on physical evidence). Embedded Sensor Networks (SNs) can be used to bridge the gap between digital and physical security planes, and thus can provide reciprocal benefit to security tasks on both planes. Toward that end, we present our experience integrating wireless networking security services into snBench (the Sensor Network workBench). snBench provides an extensible framework that enables the rapid development and automated deployment of SN applications on a shared, embedded sensing and actuation infrastructure. snBench’s extensible architecture allows an engineer to quickly integrate new sensing and response capabilities into the snBench framework, while high-level languages, compilers and execution environments allow novice SN programmers to compose SN service logic, unaware of the lower-level components on which their services rely. Concrete examples are provided to illustrate the power and potential of Wireless Security Services that span both the physical and digital plane.
This research was supported in part by a number of NSF awards, including CISE/CSR Award #0720604, ENG/EFRI Award #0735974, CISE/CNS Awards #0524477, #0952145, CNS/NeTS Award #0520166, CNS/ITR Award #0205294, CISE/EIA RI Award #0202067, and CISE/CCF Award #0820138.
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Notes
- 1.
SXEs can retrieve Opcode implementations at runtime; however, support for loading new sensing devices at runtime is not currently supported. Such functionality is not difficult to support, and it is analogous to dynamically loading device drivers to support new hardware.
- 2.
Readers may readily note that this Opcode is a loaded weapon and may gasp or recoil in horror. In fact, this is not the first Opcode that requires special user privileges to ensure correct use.
- 3.
We refer the reader to [9] for a more thorough treatment of the SNAFU language and its evaluation.
- 4.
A MAC address is far from the best way to uniquely identify an attacker, as the attacker will likely use a fictitious MAC address or worse, clone a legitimate user’s MAC during an attack.
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Bestavros, A., Ocean, M.J. (2011). Virtualization and Programming Support for Video Sensor Networks with Application to Wireless and Physical Security. In: Bhanu, B., Ravishankar, C., Roy-Chowdhury, A., Aghajan, H., Terzopoulos, D. (eds) Distributed Video Sensor Networks. Springer, London. https://doi.org/10.1007/978-0-85729-127-1_12
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