No abstract

The Alternating Step Generator (ASG) was proposed by Gunther in 1988 and consists of three LFSRs. After several serious attacks to ASG were proposed in recent years, the security of ASG has been carefully reexamined. A new structure of LFSR/FCSR based ASG and a new combination function are proposed in this research. Here, the structures of LFSR/FCSR based ASG are found to have lower probability of finding the corresponding pairs of two base sequences from an output sequence. In other words, it can resist edit distance correlation attacks efficiently. From the overall evaluation in this research, the structures of LFSR/FCSR based ASG are regarded to be more secure than ASG. publicly accessible during wireless communication. Therefore, the attacker can easily obtain a segment of the key stream. Correlation attacks exploit the correlation probability between input LFSRs and the output key stream. The edit distance correlation attack was proposed by Golic and Menocci [ 1,2]. The success of this attack depends on whether a conditional zero distance probability decreases to zero exponentially or not. This research proposes structures of LFSR/FCSR based ASG with full addition operation as a combination function. The objective of this research is to investigate the structures of LFSR/FCSR based ASG which can resist edit distance correlation attacks efficiently. II. Notations

No abstract

Abstract-Wireless sensor network (WSN) technology is widely used in environment monitoring, health care, surveillance systems and unmanned space or planet exploration. To collect the exploration data, controllable mobility such as mobile robot called data mules can be used to help complete data gathering missions using the same sensors. This study focuses on data gathering by a mobile robot in a WSN, also referred to as a robot routing problem. It is formulated as a Traveling Salesman Problem with Neighborhoods (TSPN). Basing on the need of practical applications, a two-phase method, a clustering-based parallel genetic algorithm with migration (CBPGA), is proposed as a TSPN route computing and optimizing scheme that allows simultaneously searching of the order and locations of waypoints of clusters. The first phase of the method consists of a Euclidean-distance based clustering algorithm that assigns the nodes to clusters, and the second phase routes these clusters by planning the data collection points in the common intersection area of each cluster and the order to visit them using a genetic algorithm (GA). A travel cost reduction scheme by finding the closest waypoint in a cluster according to the visiting order is used to further shorten the path length. Simulation studies are conducted to evaluate the performance of CBPGA, by comparing it with other solutions to TSPN in WSN with identical or random sensing radii. To reveal the relative performance of each solution scheme, the effect of clustering, the role of GA and parallelism, and the integration of CBPGA in data-gathering route design are highlighted.

Localization is an important process in deploying adhoc wireless sensor networks. Several localization algorithms have been developed. However, they do not achieve satisfactory performance on irregular networks. In this paper, we present a localization algorithm based on an idea of growing local maps. This paper presents an ongoing work on a localization mechanism applied to wireless sensor networks. This mechanism can cooperate with hexagon method and trilateration and dynamic robot node to estimate the coordinates of some unknown nodes. It can estimate the sensor nodes that have no GPS with some other nodes that have GPS devices. Thereafter, we can obtain more unknown nodes with some estimated nodes. It decreases the cost that localization tracking of wireless sensor devices.