USENIX Enigma 2017 — Nestan Tsiskaridze's 'Leveraging the Power of Automated Reasoning in Security Analysis of Web Applications and Beyond' →
This is a joint work with Clark Barrett (NYU/Stanford University), Morgan Deters (NYU), Tianyi Liang (The University of Iowa), Andrew Reynolds (The University of Iowa/EPFL), Cesare Tinelli (The University of Iowa) and Nestan Tsiskaridze, University of California, Santa Barbara.
Macie the Discoverer →
News that Macie The Discoverer has arrived in your S3 bucket... Data Security Automation - potentially - at it's finest? You be the judge.
The Disingenuous →
Do you unequivocally trust iRobot with your personal data, including internal mapping of your home? Read this post to learn more.
NKOTBlockchain →
Eh, wot? New Kids on the Blockchain? No - simply put, it's the proliferation of Blockhain technology (in this case distributed database schema) into industrial processes. via the UK's The Engineer, and writer Andrew Wade, comes the news of said blockhain spread. Today's MustRead!
University of Washington's Bergstrom & West, 'Calling Bullshit, In the Age Of Big Data' - Lecture Series →
via the University of Washington's Information School instructors Carl Bergstrom, Pd.D. and Jevin West, Ph.D., comes this superlative lecture series identifying bullshit within the scope of today's oft-used phrase 'Big Data'...
Splunked, The Leak →
via the eponymous Richard Chirgwin, whilst writing at El Reg, comes this unfortunate tale of security flaws within Splunk Enterprise (now, happily patched). First discovered by John Page (aka hyp3rlinx), and published via an advisory at Full Discosure. Here's hyp3rlinxs' source.
For the Record: We have always been pleased with Splunk products, and, most importantly, they are fast and focused when fixing issues.
The takeway? Make an effort to be extraordinarily cognizant of the threats posed by log and machine generated data aggregation in the enterprise. That is all.
Machine-Based Investigation: Fully →
via Motherboard writer Michael Byrne, comes this well-wrought piece on the apparent proliferation of 'bots on Twitter, ie., the implications of algorithm-driven entities on the Twitterverse. The fascinating component to this study by Onur Varol, Emilio Ferrara, Clayton A. Davis, Filippo Menczer and Alessandro Flammini, was the utilization of a machine-learning apparatus (and the feature-sets therein) to tease out the truth. Additional documentation (in the form of the paper) is available on arXIv. Today's MustRead.
"Part of what makes the new research interesting is the sheer number of features used in the classification model..." - Motherboard's Michael Byrne