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Relational inductive biases, deep learning, and graph networks

~ Adrian Colyer ~ 9 Comments
Relational inductive biases, deep learning, and graph networks Battaglia et al., arXiv'18 Earlier this week we saw the argument that causal reasoning (where most of the interesting questions lie!) requires more than just associational machine learning. Structural causal models have at their core a graph of entities and relationships between them. Today we’ll be looking ... Continue Reading

NAVEX: Precise and scalable exploit generation for dynamic web applications

~ Adrian Colyer ~ 10 Comments
NAVEX: Precise and scalable exploit generation for dynamic web applications Alhuzali et al., USENIX Security 2018 NAVEX (https://github.com/aalhuz/navex) is a very powerful tool for finding executable exploits in dynamic web applications. It combines static and dynamic analysis (to cope with dynamically generated web content) to find vulnerable points in web applications, determine whether inputs to ... Continue Reading

Unveiling and quantifying Facebook exploitation of sensitive personal data for advertising purposes

~ Adrian Colyer ~ 3 Comments
Unveiling and quantifying Facebook exploitation of sensitive personal data for advertising purposes Cabañas et al., USENIX Security 2018 Earlier this week we saw how the determined can still bypass most browser and tracker-blocking extension protections to track users around the web. Today’s paper is a great example of why you should care about that. Cabañas ... Continue Reading

Who left open the cookie jar? A comprehensive evaluation of third-party cookie policies

~ Adrian Colyer ~ 8 Comments
Who left open the cookie jar? A comprehensive evaluation of third-party cookie policies from the Franken et al., USENIX Security 2018 This paper won a ‘Distinguished paper’ award at USENIX Security 2018, as well as the 2018 Internet Defense Prize. It’s an evaluation of the defense mechanisms built into browsers (and via extensions / add-ons) ... Continue Reading