Abstract
The concept of security for tiny artifacts has been studied in a wide range of aspects, from authentication through data integrity to intrusion detection. This chapter provides a broad overview of some of the techniques developed for constrained devices where computational power, memory capacity, and energy limitations enforce slightly different approaches to these problems, when compared to standard high-end devices. In the following, we present ideas that leverage unique properties of sensor networks (also wireless sensor networks) to provide consistent and secure systems for information gathering and sensing.
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Notes
- 1.
A Bloom filter [7] is a bit-vector of length n, originally set to all-zeroes. To insert a value into the filter one calculates a hash function \(H: \{0,1\}^{*} \rightarrow \{1,\ldots \, n\}\) and sets the corresponding bit in the filter to one. At later time it is possible to effectively check if a given value does not belong to the filter by calculating the \(H(\cdot)\) on the value; on the other hand, due to possible collisions in the hash function, the Bloom filter is liable to false positives.
- 2.
In fact this is a two-step process: first, a polynomial \(a \equiv f \circledast e (\textrm{mod}\,q)\) is calculated such that its coefficients are in the range \(<-q/2, q/2>\), which cancels out \((\textrm{mod}\,q)\) operation. Then, the blinding polynomial \(p\cdot\phi\) is reduced \((\textrm{mod}\,p)\) and by inverse \(p^{-1}\) the message \((\textrm{mod}\,p)\) is recovered. For detailed discussion, see [25].
- 3.
see footnote in Sect. 22.2.1.3
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Błaśkiewicz, P., Kutyłowski, M. (2011). Security and Trust in Sensor Networks. In: Nikoletseas, S., Rolim, J. (eds) Theoretical Aspects of Distributed Computing in Sensor Networks. Monographs in Theoretical Computer Science. An EATCS Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14849-1_22
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