The cloud revolution is opening up new opportunities for organizations to embrace emerging technologies, rethink business models and improve the lives of employees and customers, but it also has a darker side – increased security risks.
The recent Accenture case is a harsh reminder of how organizations today must apply strict data governance controls. According to Upguard Security, highly critical data assets including security secret API data, authentication credentials, certificates, decryption keys, customer information and more, were stored on exposed AWS S3 buckets.
Today, security professionals must increasingly strike a balance between overseeing routine business needs and managing long-term security risks. Just as the cyber threat evolves, so should the governance and policies associated to it.
CloudSense is the world first AI-driven data governance platform. Its out-of-the-box security policies allow the security team to automatically detect and mitigate exposed sensitive data, as happened in the Accenture incident.
Cloud governance is central to D.Day Labs’ offering, and we are committed to making sure that sensitive data will not fall into the wrong hands.
For more information: https://www.engadget.com/2017/10/10/accenture-four-servers-sensitive-data-unprotected/
AI is key in unlocking and protecting the value of dark enterprise data. But what exactly dark data means? CIO insights sheds light on the term:
Deep attention networks are one of the core technologies we use in D.Day Labs. The idea (in a nutshell) is to focus the neural network on the where to order Dilantin important features of the data (text or even an image). Our research team incorporated attention network as part of the data processing pipeline in DataSense. Attention networks allow DataSense to achieve state-of-the-art accuracy in classification.
One of the biggest criticism about deep learning, is its inability to explain how a prediction is made. It is almost impossible to find the mathematical reasoning behind the decision, let alone a reasoning that will make sense to people. This also imposes a GDPR risk, as was published in a recent Oxford paper.
For the first time, we released an AI-driven product, that sheds light on the way that machines “think”. Amir Balaish, our data science leader and an attention networks expert, gave a talk in a recent PyData conference (see below). Amir explained the technical base and mathematical grounds of attention networks with real-world uses in text and image processing.
Although we cannot share our clients’ data, we can show our results on public data. The Yelp dataset, is widely used among NLP researchers; the task is to predict whether a restaurant review is positive or negative.
In the example below, we processed the reviews with the deep neural network. The words in red were the most influential in the hierarchical attention network decision.
http://lawnmowerrenttoown.com/zero A bad review:
go site A good review:
And of course, Amir’s talk.
A scanned document is a key data source in big enterprises, such as your bank and insurance company. Documents which are not filled-in correctly impose an immense legal risk. Any party of a contract might deny its agreement to the terms. Until now, documents were validated in a manual way. Humans are prone to error, so it’s impossible to validate documents on a large scale. Another aspect is the GDPR consent, which can be in the form of a scanned document (for instance, as part of know-your-client [KYC] process).
In D.Day Labs, we believe that data intelligence is key to every aspect of data processing. Due to an increasing demand from our client base, we developed scanned documents validation, as can be seen in the images below. The correct fields are marked in green, while missing fields are marked in red. DataSense classifies the document category based on artificial intelligence. Then our algorithms use unconventional deep learning and computer vision to find the missing fields.
Artificial intelligence creates new opportunities to solve old problems in data governance. Stay tuned for more research updates!
The EU’s General Data Protection Regulation (GDPR) presents the most ambitious and comprehensive changes to data protection rules in 20 years, with fines reaching up to 4% of annual turnover. The GDPR applies to all companies worldwide that process data assets of EU citizens and comes into force on May 25th, 2018.
Form a task group that will gather all the relevant stockholders together. The CISO, CIO, CRO and the compliance officers should outline a plan to achieve compliance. The good news is that in most enterprises, existing IT solutions and the cyber-security tools can support GDPR compliance. For more information please refer to the attached presentation.
D.Day Labs’ DataSense is a comprehensive data management platform that covers most of the GDPR data-related requirements. It automatically discovers and maps sensitive records in every data repository (such as file silos, databases and even cloud storage). The core technology uses advanced machine learning algorithms that classify and extract the most important properties of every data record (for example – PIIs – Personally Identifiable Information).
The artificial intelligence replaces the human factor, so the manual and tedious work of locating, classifying and indexing PIIs is no longer required. We have consulted with top GDPR experts and curated an out-of-the-box GDPR policy (as part of DataSense’s policy center). Once applied, the enterprise immediately meets GDPR requirements and is notified on compliance violations. DataSense also automatically enforces the data protection policy on end points and servers For more information please refer to our whitepaper.
Contact us for more information about DataSense and the GDPR.