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Linkstream
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Various links I find interesting. Mostly hardcore tech :) // by @oleksandr_now. See @notatky for the personal stuff
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note for Samsung users: every single protection measure in KNOX is broken, including KASLR, DFI, SELinux and RKP in general. Talk with details and end-to-end exploitation demos is expected July 27 at BH USA'17
Also there are two talks announced which demonstrate different but notably completely automated, AI-driven antivirus and IDS bypass techniques for Android and Windows, respectively. We're going into totally movieplot territory here :)
This is one solid advice, if hard to follow at times.
https://erikbern.com/2017/07/06/optimizing-for-iteration-speed.html
hmm, need to refresh my postquantum crypto curriculum...
https://en.wikipedia.org/wiki/Supersingular_isogeny_key_exchange
Deep learning sometimes just means deep memory
https://arxiv.org/abs/1703.06857
— …I'm a full stack engineer
— Which way does the stack grow on x86?
— [blank stare]
// michaelklishin@twitter
you can entrust government bureaucrats with your sensitive and private data, like witness protection program data, for sure!

they also get severely punished if they leak it, like half a month’s pay in fines for leaking pretty much the entire military and civilian database set (for entire EU, not only Sweden)

https://www.privateinternetaccess.com/blog/2017/07/swedish-administration-tried-glossing-leaking-eus-secure-stesta-intranet-russia/
Soft skills 2.0: talking with the machines. Teaching your fellow machines.
https://arxiv.org/abs/1707.06742
Malicious Arithmetic, mmm, tasty!
> MASCOT: Faster Malicious Arithmetic Secure Computation with Oblivious Transfer
https://eprint.iacr.org/2016/505.pdf
hmm, this one is unexpected, but given a second thought... mixing uncorrelated features just slightly biases them into normal distribution, keeping other properties intact, hence no wonder it works
Small Statistical Models by Random Feature Mixing '08
http://www.cs.jhu.edu/~mdredze/publications/mobile_nlp_feature_mixing.pdf