A longitudinal, end-to-end view of the DNSSEC ecosystem

A longitudinal, end-to-end view of the DNSSEC ecosystem Chung et al., USENIX Security 2017 DNS, the Domain Name System, provides a vital function on the Internet, mapping names to values. Unprotected, it's also an attractive target for hackers with attack vectors such DNS spoofing and cache poisoning. Thus about two decades ago a set of … Continue reading A longitudinal, end-to-end view of the DNSSEC ecosystem

To type or not to type: quantifying detectable bugs in JavaScript

To type or not to type: quantifying detectable bugs in JavaScript Gao et al., ICSE 2017 This is a terrific piece of work with immediate practical applications for many project teams. Is it worth the extra effort to add static type annotations to a JavaScript project? Should I use Facebook's Flow or Microsoft's TypeScript if … Continue reading To type or not to type: quantifying detectable bugs in JavaScript

Bringing the web up to speed with WebAssembly

Bringing the web up to speed with WebAssembly Haas et al., PLDI 2017 This is a joint paper from authors at Google, Mozilla, Microsoft and Apple describing the motivations for WebAssembly together with a very concise exposition of its core semantics. If you're following along with the paper, I found it helpful to dip into … Continue reading Bringing the web up to speed with WebAssembly

Struc2vec: learning node representations from structural identity

struc2vec: learning node representations from structural identity Ribeiro et al., KDD'17 This is a paper about identifying nodes in graphs that play a similar role based solely on the structure of the graph, for example computing the structural identity of individuals in social networks. That's nice and all that, but what I personally find most … Continue reading Struc2vec: learning node representations from structural identity

Accelerating innovation through analogy mining

Accelerating innovation through analogy mining Hope et al., KDD'17 Today's choice won a best paper award at KDD'17. It's a really interesting twist on information retrieval, building on a foundation of GloVe and word vectors to create purpose and mechanism vectors for a corpus of product descriptions. Using these vectors, the authors show how to … Continue reading Accelerating innovation through analogy mining

Adversarial examples for evaluating reading comprehension systems

Adversarial examples for evaluating reading comprehension systems Jia & Liang, EMNLP 2017 We've now seen a number of papers investigating adversarial examples for images. In today's paper choice, Jia and Liang explore adversarial examples for text samples in the context of reading comprehension systems. The results are frankly a bit of a wake-up call for … Continue reading Adversarial examples for evaluating reading comprehension systems

Universal adversarial perturbations

Universal adversarial perturbations Moosavi-Dezfooli et al., CVPR 2017. I'm fascinated by the existence of adversarial perturbations - imperceptible changes to the inputs to deep network classifiers that cause them to mis-predict labels. We took a good look at some of the research into adversarial images earlier this year, where we learned that all deep networks … Continue reading Universal adversarial perturbations