Leviticus 25:9
Once every 50 years comes the great day of the Jubilee, the day when all debts are forgiven.
For this special year and for the first time, the latest cryptographic technology can be used to obtain better debt jubilees.
Hallelujah!
Leviticus 25:9
Once every 50 years comes the great day of the Jubilee, the day when all debts are forgiven.
For this special year and for the first time, the latest cryptographic technology can be used to obtain better debt jubilees.
Hallelujah!
וְעַתָּה, אִם‑תִּשָּׂא חַטָּאתָם; וְאִם‑אַיִן–מְחֵנִי נָא, מִסִּפְרְךָ אֲשֶׁר כָּתָבְתָּ
Exodus 32:31
Erecting false idols leads to the fall: you don’t build an enduring house over pseudo-anonymity, inefficient Sybil-resistance, insecure scripts, and unstable policies. And what is worse, with entry limited to only a very limited few.
Instead, when you build a great house, you invite everyone to enjoy it.
לֹא, תִּגְנֹבוּ; וְלֹא‑תְכַחֲשׁוּ וְלֹא‑תְשַׁקְּרוּ, אִישׁ בַּעֲמִיתוֹ
Lev. 19:11
As the human mind is inscrutable to others, so its elucubrations are the truly purest form of property. Raziel protects your secrets from the Adversary and provides proofs against its malicious machinations: you shall not be robbed neither of your data nor of your code, for they are your inalienable property.
Hallelujah!
הַנִּסְתָּרֹת לַיהֹוָה אֱלֹהֵינוּ וְהַנִּגְלֹת ֹלָֹנוֹּ ֹוֹּלְֹבָֹנֵֹיֹנֹוּ עַד עוֹלָם לַעֲשׂוֹת אֶת כָּל דִּבְרֵי הַתּוֹרָה הַזֹּאת
Deut. 29, 29
There is a pain, a void in your heart, an aching to be safe: the Adversary covets your secrets, with weapons not of this world, trying to read your mind to keep it blind. And predominantly helped by the “information revelation” dilemma: when you loose the lock that keep your lips closed, you risk to loose that precious treasure that you own even more than the clothes that dress you; your thoughts and information. On the other hand, as the mind is inscrutable to other humans, your information is rendered your property under a Higher Law. So let it be this fundamental dilemma of human existence: what to say or what to keep; how to reconcile talking and keeping secrets?
Rejoice! I bring you good news of great joy which will be for all! From now on and thanks to secure computation, deus ex machina, you can use other’s information without falling into the temptation of misappropiating it; or let others use your own information without it being stolen from you!
Hallelujah!
A quick summary from my experiences with Hadoop:
It’s all over the news: a vulnerability has been found on OpenSSL that leaks memory contents on server and clients. Named Heartbleed, it has a very simple patch and some informative posts have already been written about it (Troy Hunt, Matthew Green).
What nobody is saying is that the real root cause is the lack of modern memory management in the C language: OpenSSL added a wrapper around malloc() to manage memory in a more secure and efficient way, effectively bypassing some improvements that have been made in this area during a decade; specifically, it tries to improve the reuse of allocated memory by avoiding to free() it. Now enter Heartbleed: by a very simple bug (intentional or not), the attacker is able to retrieve chosen memory areas. What was the real use of that layer?
Face it: it’s a no-win situation. No matter how many ways these layers are going to be written, there will always be a chance for error. You can’t have secure code in C.
But re-writing and/or throwing away thousands of security related programs written in C is no-brainer: the only way to securely run these programs is with the help of some memory debuggers techniques, like those used by Insure++ or Rational Purify. For example, the next technical report contains a detailed analysis of some of these techniques that prevent these kind of vulnerabilities:
Big Data is shaking up everything, from education, economics, businesses and the sciences: the changes may be as big as the ones introduced by the printing press. As promoted, its biggest impact is that now we don’t need to research how to automate and teach a computer to do things: just inferring probabilities from big amounts of data is enough.
In the past, data collection, storing and analyzing methods were expensive and time consuming: in the year 2000, digital information was just one-quarter of the world’s stored information. Now we can easily capture and store ever-growing amounts of data: today, only 1% of all the stored information is non-digital, since the digital data is growing exponentially.
But behind the Big Data hype, there’s also Big Unawareness of statistical sciences:
In the other words, Big Data does not equal Big Insights: science, deep reasoning and proper inferencing are as necessary as ever, and statisticians are beginning to modify and fine-tune their toolsets: as a remedy, I predict that tools from the Automated Reasoning field will also be increasingly adopted to fight this data avalanche.
A graphical summary to Caspers Jones’ latest book, “[amazon_link id=“0321903420” target=“_blank”]The Technical and Social History of Software Engineering[/amazon_link]”, aggregating the data of thousands of projects:
As languages improved (and their number, so more languages are available for specific tasks), so did the programmer’s productivity, lowering the defect potential at the same time: this document about software engineering laws also provides another interesting outlook of the same datasets.