No abstract

Abstract-In large-scale wireless sensor networks, it proves very difficult to dynamically monitor system degradation and detect bad links. Faulty link detection plays a critical role in network diagnosis. Indeed, a destructive node impacts its links' performances including transmitting and receiving. Similarly, other potential network bottlenecks such as network partition and routing errors can be detected by link scan. Since sequentially checking all potential links incurs high transmission and storage cost, existing approaches often focus on links currently in use, while overlook those unused yet ones, thus fail to offer more insights to guide following operations. We propose a novel scheme Link Scanner (LS) for monitoring wireless links at real time. LS issues one probe message in the network and collects hop counts of the received probe messages at sensor nodes. Based on the observation that faulty links can result in mismatch between the received hop counts and the network topology, we are able to deduce all links' status with a probabilistic model. We evaluate our scheme by carrying out experiments on a testbed with 60 TelosB motes and conducting extensive simulation tests. A real outdoor system is also deployed to verify that LS can be reliably applied to surveillance networks.

No abstract

No abstract

An effective detection algorithm based on the randomness is devised in this paper for stegowebpages with different steganographies. The parts where secret information embedded in a webpage can generally be represented as two states, which can be described in binary code string. The randomness of the states varies a great deal depending on the webpage part carrying secret information or not. This paper presents a procedure to transform the binary code string into octal string to capture the randomness, from which some statistical features have been discovered. The theoretical description and proof are given that these features can be employed as a criterion to test whether a webpage contains secret information or not. Experiments show that this algorithm can effectively detect the stego-webpages based on letter changing in tags and invisible characters embedding.