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 Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

In this paper, we explore the effectiveness of dynamic analysis techniquesfor identifying malware, using Hidden Markov Models (HMMs) and Profile HiddenMarkov Models (PHMMs), both trained on sequences of API calls. We contrast ourresults to static analysis using HMMs trained on sequences of opcodes, and showthat dynamic analysis achieves significantly stronger results in many cases.Furthermore, in contrasting our two dynamic analysis techniques, we find thatusing PHMMs consistently outperforms our analysis based on HMMs.

Malware Detection Using Dynamic Birthmarks