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)

The main purpose of this paper is to introduce some techniques to overcome 3D missing information visual artefacts problem, holes and blank regions between 3D integral images (holoscopic images) frames encountered with the computer generated 3D integral image, pixel-tracing styles is proposed to achieve a higher performance of generating 3D integral images in terms of execution time, Z-buffer and correct occlusion scheme is also introduced to overcome visual artefact. The methods are based on a 3D integral images ray-tracer containing 3D integral images parser, 3D integral camera model, a 3D integral images renderer and scene transformations. Consequently, fast sequences of 3D integral image frames for animations purposes are generated, experimental results show validation of the strategies to fill in the 3D missing pixels and test on different scenes, improvement in terms of execution time depends on the complexity of the scene is achieved.
Dr. Mahmoud Geat Eljadid, Prof. Amar Aggoun, Dr. Osama Hassan Youssef(1-2014)

Transliteration is the process of representing words of one language into another using corresponding equivalent phonemes. For example, “Mohammed”, “Mohammad”, or “Muhammed” are three valid transliterations to the Arabic proper noun “محمد”. Transliteration from Arabic to English usually results in several different versions for the same Arabic name causing some names to have more than 40 different versions. Finding transliterated names is a problem in most languages. In English, this problem has been studied by researchers and many techniques have been developed to find transliterated names referring to the same foreign name. Techniques such as string matching and phonetic matching have been used to find similar names. However, some of these techniques were designed to find similar names of English origin and not a specific transliterated names. In this paper we review current techniques used to find variants of the same name and introduce a new technique we specifically developed to find transliterated Arabic names in English text. We developed a data set of more than 25,000 transliterated Arabic names and tested the effectiveness of current and the new technique on finding 115 names within that list. Our results show that our technique is superior to all other techniques. We also present an online system that we developed to find transliterated Arabic names on the web using our technique. arabic 8 English 57
Abdusalam F. Ahmad Nwesri, Nabila Al-Mabrouk S. Shinbir(9-2009)