Image data experiences geometric distortions and spatial-temporal varying blur due to the strong effects of random spatial and temporal variations in the optical refractive index of the communication path. Simultaneously removing these effects from an image is a challenging task. An efficient approach is proposed in this paper to address this problem. The approach consists of four steps. First, a frame selection strategy is employed by proposing an unsupervised k-means clustering technique. Second, a B-spline-based nonrigid image registration is carried out to suppress geometric distortions. Third, a spatiotemporal kernel regression is proposed by introducing the local sharp patch concept to fuse the registered frame sequences into an image. Finally, a blind deconvolution technique is employed to deblur the fused image. Experiments are carried out with synthetic and real-world turbulence-degraded data by implementing the proposed method and two recently reported methods. The proposed method demonstrates significant improvement over the two reported methods in terms of alleviating blur and distortions, as well as improving visual quality.
<p><span>Almost every web-based application is managed and operated through a number of websites, each of which is vulnerable to cyber-attacks that are mounted across the same networks used by the applications, with much less risk to the attacker than physical attacks. Such web-based attacks make use of a range of modern techniques-such as structured query language injection (SQLi), cross-site scripting, and data tampering-to achieve their aims. Among them, SQLi is the most popular and vulnerable attack, which can be performed in one of two ways; either by an outsider of an organization (known as the outside attacker) or by an insider with a good knowledge of the system with proper administrative rights (known as the inside attacker). An inside attacker, in contrast to an outsider, can take down the system easily and pose a significant challenge to any organization, and therefore needs to be identified in advance to mitigate the possible consequences. Blockchain-based technique is an efficient approach to detect and mitigate SQLi attacks and is widely used these days. Thus, in this study, a hybrid method is proposed that combines a SQL query matching technique (SQLMT) and a standard blockchain framework to detect SQLi attacks created by insiders. The results obtained by the proposed hybrid method through computational experiments are further validated using standard web validation tools.</span></p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.