Recently, the emerging event camera shows great potential for robotics and AR/VR application thanks to its advantages including low latency, high dynamic range, low power consumption, etc. However, the output of event cameras usually has a large amount of noise which will affect unlocking their potentials and obtaining wider applications. In this paper, we present a two-stage local spatio-temporal event filter (LSTEF) based on adaptive thresholds. Considering the spatio-temporal constraints of generated event streams, a local sliding window is adopted for the noise candidate selection stage and noise filtering stage. An adaptive thresholding mechanism is also introduced into the filter in order to improve the generalization performance. Corresponding experimental evaluations are performed on the public datasets to prove the efficiency of the proposed filter. Results show that the presented LSTEF can successfully achieve the event denoising, and at the same time, effectively preserve useful scene information.

Abstract In this paper, in order to simultaneously resolve the transmission security and availability in Supervisory Control And Data Acquisition (SCADA) group communications, we propose a robust and efficient group key management scheme, called LiSH+, which is characterized by developing a secure self‐healing mechanism witht‐revocation and collusion resistance capability. A dual direction hash chain is utilized to guarantee the backward secrecy and forward secrecy of group key. A novel self‐healing mechanism is constructed to ensure availability of the group member in case of devices failure and prevent the collusive users from exploiting the group key in the proposed scheme. In addition, the compromised users can be revoked from the group dynamically by broadcasting message. Detailed security analysis shows that the proposed LiSH+ scheme meets the requirements of group communication and is secure in terms oftuser collusion‐free. Performance evaluation also demonstrates its efficiency in terms of low storage requirement and communication overheads. Copyright © 2014 John Wiley & Sons, Ltd.

Accurate localization is crucial for wireless ad-hoc and sensor networks. Among the localization schemes, component-based approaches specialize in localization performance. By grouping nodes into increasingly large rigid components, component-based localization algorithms can properly conquer network sparseness and anchor sparseness. However, such design is sensitive to measurement errors. Existing robust localization methods focus on eliminating the positioning error of a single node. Indeed, a single node has two dimensions of freedom in 2D space and only suffers from one type of transformation: translation. As a rigid 2D structure, a component suffers from three possible transformations: translation, rotation, and reflection. A high degree of freedom brings about complicated cases of error productions and difficulties on error controlling. This study is the first work addressing how to deal with ranging noises for component-based methods. By exploiting a set of robust patterns, we present an Error-TOlerant Component-based algorithm (ETOC) that not only inherits the high-performance characteristic of component-based methods, but also achieves robustness of the result. We evaluate ETOC through a real-world sensor network consisting of 120 TelosB motes as well as extensive large-scale simulations. Experiment results show that, comparing with the-state-of-the-art designs, ETOC can work properly in sparse networks and provide more accurate localization results.

Supevisory Control And Data Acquisition (SCADA) systems are vital for operation and control of critical infrastructures in smart grid. Availability is one of the most important security objectives in SCADA communications, unavailability of which may further undermine the power delivery, and a reliable key management is essential to address this problem. In this paper, in order to simultaneously resolve the transmission security and availability in SCADA group communications, we propose a robust and efficient group key management scheme, called LiSH, which is characterized by developing a secure self-healing mechanism with t-revocation capability using one-way function to protect current session keys from being attacked by intruders. Detailed security analysis shows that the proposed LiSH scheme is secure in terms of collusion-free, and t-wise forward and backward security. In addition, performance evaluation also demonstrates its efficiency in terms of low storage and communication overheads.

Localization is crucial for wireless ad hoc and sensor networks. As the distance-measurement ranges are often less than the communication ranges for many ranging systems, most communication-dense wireless networks are localization-sparse. Consequently, existing algorithms fail to provide accurate localization supports. In order to address this issue, by introducing the concept of component, we group nodes into components so that nodes are able to better share ranging and anchor knowledge. Operating on the granularity of components, our design, CALL, relaxes two essential restrictions in localization: the node ordering and the anchor distribution. Compared to previous designs, CALL is proven to be able to locate the same number of nodes using the least information. We evaluate the effectiveness of CALL through extensive simulations. The results show that CALL locates 90% nodes in a network with average degree 7.5 and 5% anchors, which outperforms the state-of-the-art design Sweeps by about 40%.

Accurate localization is crucial for wireless ad-hoc and sensor networks. Among the localization schemes, component-based approaches specialize in localization performance, which can properly conquer network sparseness and anchor sparseness. However, such design is sensitive to measurement errors. Existing robust localization methods focus on eliminating the positioning error of a single node. Indeed, a single node has two dimensions of freedom in 2D space and only suffers from one type of transformation: translation. As a rigid 2D structure, a component suffers from three possible transformations: translation, rotation, and reflection. A high degree of freedom brings about complicated cases of error productions and difficulties on error controlling. This study is the first work addressing how to deal with ranging noises for component- based methods. By exploiting a set of robust patterns, we present an Error-TOlerant Component-based algorithm (ETOC) that not only inherits the high-performance characteristic of component-based methods, but also achieves robustness of the result. We evaluate ETOC through a real-world sensor network consisting of 120 TelosB motes as well as extensive large-scale simulations. Experiment results show that, comparing with the-state-of-the-art designs, ETOC can work properly in sparse networks and provide more accurate localization results.

Accurate self-localization is a key enabling technique for many pervasive applications. Existing approaches, most of which are multilateration based, often suffer ambiguities, resulting in unbounded positioning errors. To address this problem, previous approaches discard those positioning results with possible flip ambiguities, trading the performance for robustness. However, the high false positive rate of flip prediction incorrectly rejects many reliable location estimates. By exploiting the characteristics of flip ambiguity, which causes either huge or zero error, we propose the concept of optimistic localization and design an algorithm, OFA, that employs a global consistency check and a location correction phase in the localization process. We evaluate this design through extensive simulations. The results show that OFA obtains robustness with extremely low performance cost, so as to reduce the requirement on average degree from 25 to 10 for robustly localizing a network.

Localization is crucial for wireless ad hoc and sensor networks. As the distance-measurement ranges are often less than that of the communication range for many ranging systems, most communication-dense wireless networks are often localization-sparse. Consequently, most existing algorithms fail to provide accurate localization supports. In order to address this issue, by introducing a concept ofcomponent, we propose to group nodes into components, so that nodes are able to better share their ranging and anchor knowledge. This design, CALL, relaxes two essential restrictions in localization: node ordering and anchor distribution. We evaluate the effectiveness of CALL through extensive simulations. The results show that CALL locates 80% nodes in a network with average degree 7.5 and 5% percent anchors, which outperforms the state of the art design Sweeps about 20%.