The advertising ecosystem faces major threats from ad fraud caused by artificial display requests or clicks, created by malicious codes, bot-nets, and click-firms. Currently, there is a multibillion-dollar online advertisement market which generates the primary revenue for some of the internet's most successful websites. Unfortunately, the complexities of the advertisement ecosystem attract a considerable amount of cybercrime activity, which profits at the expense of advertisers. Web ad fraud has been extensively studied whereas fraud in mobile ads has received very little attention. Most of these studies have been carried out to identify fraudulent online and mobile ads clicks. However, the identification of individual fraudulent displays in mobile ads has yet to be explored. Additionally, other fraudulent activity aspects such as hacking ad-campaign accounts have rarely been addressed. The purpose of this study is to provide a comprehensive review of state-of-the-art ad fraud in web content as well as mobile apps. In this context, we will introduce a deeper understanding of vulnerabilities of online/mobile advertising ecosystems, the ad fraud’s well-known attacks, their effective detection methods and prevention mechanisms. arabic 8 English 40
Hala Shaari, Nuredin Ahmed(12-2020)

Inspection offers an opportunity to detect and remove defects at various points during software development. Early detection will reduce the effect of propagation and amplification of defects into the later phases of software development. Collaborative inspection on the web aims to eliminate the time factor needed to assemble the inspection or review team at a physical location. Through the collaborative mode, software teams can perform software inspection and review from geographically separated places asynchronously. These newly introduced practices have proven that collaborative inspection and review of artifacts on the web is feasible. This paper provides a model for collaborative inspection and review including possible features of model and tool that will support collaborative inspection and review on the web. arabic 10 English 64
Abdusalam Nwesri, Khairuddin Hashim(10-2008)

The process of conflating different Arabic word formats to their stem or root is called stemming. Indexing text collection using stems or roots has been reported to be superior to using original word formats. However, the Arabic text stemming has negative effects on words. It conflates words with different meaning under one index term. This occurs frequently in Arabic when using stems and it becomes more frequent when choosing roots to index the collection. Furthermore, search engine whose index is constructed using a particular stemmer makes it a stemmer-dependent engine. In this paper, we show how we can still use stemming to reach the same results without indexing the stemmed text. Original words have been indexed, and a stemmer used to extract word variants and add them to the user query. Apart from making our search operation stemmer-independent, we proof that our approach is as good as light stemming and is significantly better than root stemming. arabic 5 English 41
Aabdusalam F Ahmad Nwesri, Hasan A. H. Alyagoubi(9-2015)