Co-authors: James Verbus and Beibei Wang The Anti-Abuse AI Team at LinkedIn creates, deploys, and maintains models that detect and prevent many types of abuse, including the creation of fake accounts, member profile scraping, automated spam, and account takeovers. As we prevent abuse using machine learning, there are several challenges we can face: Maximizing...
trust engineering Articles
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Co-authors: Parvez Ahammad, Kinjal Basu, Shaunak Chatterjee, Sakshi Jain, Ryan Rogers, and Guillaume Saint-Jacques At LinkedIn, our guiding principle is “Members First.” It ensures we honor our responsibility to protect our members and maintain their trust in every decision we make, and puts their interests first. A key area where we apply this value in...
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LinkedIn is committed to providing a trusted environment to keep our nearly 740 million members safe. Part of that commitment involves protecting against various types of abuse on the platform. Fighting abuse presents many challenges; one example is when bad actors use bots for large-scale attacks, while another is when attack signals constantly evolve to adapt...
- Topics:
- trust engineering,
- Security
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Co-authors: Sakshi Jain, Grace Tang, Gaurav Vashist, Yu Wang, John Lu, Ravish Chhabra, Shruti Sharma, Dana Tom, and Ranjeet Ranjan...
- Topics:
- trust engineering,
- Security
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Co-authors: Grace Tang, Pavan K. Ganganahalli Marulappa, Montinee Khunvirojpanich, and Ting Chen LinkedIn is an active professional...
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Our members place their trust in us, and expect and deserve a safe and trusted community where they can express themselves...