Lately, there has been a growing trend in the Internet space particularly among the Online Social Media (OSMs) platforms like Twitter, Facebook etc which are becoming huge repositories of information. This information, by design, is posted by users of these websites and consequently, this information is vast, un-organized, unreliable and dynamic. It is commonly observed that along with genuine users, a lot of activity is seen from spammers or users with the intent of spreading malicious or irrelevant content. In our work, we focus on spamming activity on Twitter. Spamming activity in Twitter is can typically be reported by its users, who we refer as reporters and those who indulge in spamming activities are referred as reportees. We collected data of suspected spammers, i.e. reportees as well as of the users who reported them, i.e. reporters. Thereafter, we classified them into various categories and tried to study the ecosystem of these reportees and reporters. We used three data mining techniques i.e., decision tree , K-nearest neighbors and random forest classifier for the classification tasks. Finally, we have compared these three algorithms on the basis of their accuracy.
With the widespread use of Internet, transfer of digital data online is enormous. This leads to easy accessibility and vulnerability to attacks of copyrighted content on large scale. Digital data in form of videos, audios, text, images can easily be manipulated, forged and redistributed for profits. To overcome this problem and protect copyrighted content, Digital Watermarking emerged as a useful solution. This paper talks about the literature survey of different watermarking techniques and showcase the comparative description of superiority of one technique over the other.
Intellectual and copyright protection is one of the major issues faced by copyright owners. Easy access to Internet and all the digital media such as audios, images, digital documents and videos, poses great threat to copyright owners as their work gets manipulated, forged, redistributed conveniently through illegal means. As an effective solution to this problem, concept of Digital Watermarking has been used. Watermarks can be of the form images, text, binary logos, signatures, and numbers. They are used for storing information about the copyright owner, source of data, and authentic users. In the proposed work, video watermarking technique has been shown highlighting comparative analysis of db wavelets based on different quality parameters. Each of the db wavelets is applied on the randomly selected frames from the input coloured video using random number that works as a key for the proposed extraction algorithm. It is shown that not all db wavelets support watermarking scheme. Out of 45 wavelets, 12 db wavelets were applicable for watermarking. The original watermark image and the extracted watermark image are then used as the basis against various quality parameters to check if the imperceptibility of the watermark is retained after watermark extraction. The proposed watermarking scheme is imperceptible against various quality parameters such as Peak-signal-to-noise ratio, Mean-square error, maximum difference, and normalized absolute error.
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