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huge irrelevant search hits. In this paper, we propose an improved method for ranking of search results to reduce human efforts on locating interesting hits. The search results are re-ranked using adaptive user interest hierarchies (AUIH), which considers both investigator-defined keywords and user interest learnt from
the device to strengthen the defense. To enhance the security of the back-end application servers, we use keyword filtering and re-treatment to rule out the blacklist, and to adjust the system settings so that it can effectively block the assaults or reduce the possibility of successful attacks. In addition, we also
expansion of the keyword lexicon used to discover IED related web pages, which identified new relevant terms for inclusion. Additionally, we present an improved web page feature representation designed to better capture the structural and stylistic cues revealing of genres of communication, and a series of experiments
To discover information endangering network security, an exploration method of network security information based on immunology is proposed. Antibody and antigen in biological immune system are used to denote keywords hid in HTML pages. Proposed method generates new antibodies to recognize unknown keywords through
distinctive keywords used in Web pages or URLs in order to detect new phishing sites that are not yet listed in blacklists. However, these kinds of heuristics can be easily circumvented by phishers once their mechanism is revealed. In order to overcome this weakness, visual similarity-based detection techniques have been
the tokens or between the checksums indicates a same origin violation. To reduce the scheme's performance ovrhead, this matching is performed only when a request originated from a page with no submission form has suspicious keywords. We analyze the protection potential, security, and performance overhead of our scheme.
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