Directed paths between vulnerable nodes and potential sensor nodes are used to construct a bipartite graph, and the sensor network design problem is formulated as a minimum set cover problem.
Soft-decision combining not only benefits from using more descriptive data but also becomes more vulnerable to outliers in sensor reports, e.g., extremely high or low RSS values.
Node replication attacks leave wireless sensor networks vulnerable to various insidious attacks, e.g., the adversary can pour false data into the network to prevent the success of the data aggregation protocol or the node replication attack can revoke legitimate nodes and disconnect the network by triggering a correct execution of the node revocation protocols [1].
In ref. [33], Zhou applies Voronoi graph and Dijkstra algorithm to search vulnerable path in the sensors network.
For instance, CMOS sensors may suffer from skew on moving objects or scenes if its shutter speed is too slow, while CCD sensors are vulnerable to smearing artifacts when bright light sources overload a column or row of pixels.
In this paper we use sensor-annotated abstraction hierarchies (Reising & Sanderson, 1996, 2002a, b) to show that unless appropriately instrumented, configural displays designed according to the principles of ecological interface design (EID) might be vulnerable to misinterpretation when sensors become unreliable or are unavailable.
Wireless sensor networks are vulnerable to a wide variety of physical attacks.
However, such over-provisioned sensor networks remain vulnerable to unpredictable scope and gravity of failures, raising questions on the very viability of this approach.
The sensor network is vulnerable to jamming attacks since the sensor nodes operate at a very low radio power [4] and use limited communication range between source and sink.
Wireless network is itself vulnerable and when combined with sensors the other errors that add upon to it are sensor failures, localization errors, prediction, and detection errors.
