5 research outputs found
Studying Ransomware Attacks Using Web Search Logs
Cyber attacks are increasingly becoming prevalent and causing significant
damage to individuals, businesses and even countries. In particular, ransomware
attacks have grown significantly over the last decade. We do the first study on
mining insights about ransomware attacks by analyzing query logs from Bing web
search engine. We first extract ransomware related queries and then build a
machine learning model to identify queries where users are seeking support for
ransomware attacks. We show that user search behavior and characteristics are
correlated with ransomware attacks. We also analyse trends in the temporal and
geographical space and validate our findings against publicly available
information. Lastly, we do a case study on 'Nemty', a popular ransomware, to
show that it is possible to derive accurate insights about cyber attacks by
query log analysis.Comment: To appear in the proceedings of SIGIR 202
Nudge: Accelerating Overdue Pull Requests Towards Completion
Pull requests are a key part of the collaborative software development and
code review process today. However, pull requests can also slow down the
software development process when the reviewer(s) or the author do not actively
engage with the pull request. In this work, we design an end-to-end service,
Nudge, for accelerating overdue pull requests towards completion by reminding
the author or the reviewer(s) to engage with their overdue pull requests.
First, we use models based on effort estimation and machine learning to predict
the completion time for a given pull request. Second, we use activity detection
to reduce false positives. Lastly, we use dependency determination to
understand the blocker of the pull request and nudge the appropriate
actor(author or reviewer(s)). We also do a correlation analysis to understand
the statistical relationship between the pull request completion times and
various pull request and developer related attributes. Nudge has been deployed
on 147 repositories at Microsoft since 2019. We do a large scale evaluation
based on the implicit and explicit feedback we received from sending the Nudge
notifications on 8,500 pull requests. We observe significant reduction in
completion time, by over 60%, for pull requests which were nudged thus
increasing the efficiency of the code review process and accelerating the pull
request progression