English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Open

Presents the pdf analysis as premium feature

PDF Analysis

Insights

Presents the summarisation as premium feature

Summarisation

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

IP blacklists are a spam filtering tool employed by a large number of email providers. Centrally maintained and well regarded, blacklists can filter 80+% of spam without having to perform computationally expensive content-based filtering. However, spammers can vary which hosts send spam (often in intelligent ways), and as a result, some percentage of spamming IPs are not actively listed on any blacklist. Blacklists also provide a previously untapped resource of rich historical information. Leveraging this history in combination with spatial reasoning, this paper presents a novel reputation model (PreSTA), designed to aid in spam classification. In simulation on arriving email at a large university mail system, PreSTA is capable of classifying up to 50% of spam not identified by blacklists alone, and 93% of spam on average (when used in combination with blacklists). Further, the system is consistent in maintaining this blockage-rate even during periods of decreased blacklist performance. PreSTA is scalable and can classify over 500,000 emails an hour. Such a system can be implemented as a complementary blacklist service or used as a first-level filter or prioritization mechanism on an email server.

Spam mitigation using spatio-temporal reputations from blacklist history