How Can Cloud Storage Deal With Security Issues?

How Can Cloud Storage Deal With Security Issues?

As detailed by Chris Pedigo of Lacework.com, 2019 saw some dark days for the cloud. While companies storing information in such data centers usually find that method cost-effective and efficient, the exceptions were notable, and troubling.

In April, 540 million Facebook records were exposed via Cultura Colectiva, a Mexican content provider. In May, Instagram saw 49 million records laid bare. July brought the Capital One breach, in which 80,000 bank account numbers (and 140,000 social security numbers) were exposed. And September saw the Autoclerk breach, where travel reservations were hacked, including those of military personnel involved with sensitive operations.

As a result, businesses are increasingly turning to blockchain to secure their cloud storage. An integral part of the larger trend toward Blockchain as a Service (BaaS), the distributed security makes this decentralized ledger far less vulnerable to hackers than the centralized servers preferred by most companies in the past.

The reasons have been well-documented. There are the cryptographic hashes unique to each block, which results in the chain’s immutability — i.e., none of the blocks can be modified without altering the whole chain. There is the peer-to-peer network, to which all data is distributed. Because it is not stored by any single entity but rather a node of users, the information within the chain cannot be changed by an outside actor. That ties into another security measure — the consensus protocol, under which all users need to verify a new block.

Finally, there is proof-of-work (PoW), the algorithm used to verify the transactions that lead to the creation of new blocks in the chain.

Again, such security is one of the great appeals of blockchain, and spending on the technology, which has tripled since 2017, is expected to reach $16 billion by 2023. Healthcare in particular is expected to reap the benefits of this technology, as blockchain spending in that sector is projected to reach $1.4 billion by 2024.

At present, however, healthcare lags behind financial services, manufacturing and energy and utilities in the industries that executives view as being most advanced in blockchain development, per a Business Insider survey. Forty-six percent of those polled believe that financial services have made the greatest strides in that area, compared to 12 percent for manufacturing, 12 percent for energy and utilities and 11 percent for healthcare. (Another eight percent view governmental use as being the most advanced.)

But it is expected that there will be precious few industries that won’t be impacted by this technology in the years to come. One report listed 58 possible areas in which blockchain can be applied, ranging from voting to ride-sharing to advertising.

The conclusion is a simple one: A decentralized storage system like blockchain can do for information what it has been doing for cryptocurrencies, keeping it safe and sound, and accessible only to those on the chain in question. The trend toward blockchain will only continue in the years ahead, and cut across all sectors.

Google Opens Up Machine Learning Tools to Businesses in Beta

Google Opens Up Machine Learning Tools to Businesses in Beta

Google has been on top of cutting-edge technology since its now-ubiquitous search engine rose to prominence. You may or may not have noticed, but the search engine has gotten smarter: it learns from your behavior and alters your results based on search trends and location.

Essentially, Google is the king of algorithms. And guess what? Its machine learning algorithms can belong to your business, too. Recently, Google opened its Cloud Machine Learning platform to all businesses in public beta. Essentially, it allows businesses to train their own models at a faster rate using Google’s system — just a few hours compared to days or more.

Google, now part of conglomerate umbrella Alphabet, is much more than a search engine now, so this service has little to do with your daily queries. Still, it encompasses what we’ve come to expect from Google: speed, intelligence, and constant improvement. That is machine learning in a nutshell, too.

So, how can businesses utilize Google’s Cloud Machine Learning? We can take one example for starter’s: Airbus Defense and Space. This company used the system to automate the process of detecting and correcting satellite images that contain imperfections, like cloud formations, for example.

According to Mathias Ortner, the company’s Data Analysis and Image Processing Lead, “Google Cloud Machine Learning enabled us to improve the accuracy and speed at which we analyze the images captured from our satellites. It solved a problem that has existed for decades.”

More problems can be solved with machine learning — this only scratches the surface. Google has launched two separate services: their Machine Learning Advanced Solutions Lab, which allows businesses to work with Google engineers to solve complex problems, and the Cloud Start program, which offers educational workshops to teach them the fundamentals.

Considering it was Google’s engineers that worked with Niantic before the launch of Pokemon Go, an opportunity to work with the tech giant could definitely be transformative for many. With more businesses in the machine learning game, more customers across the board will benefit from smarter services geared to get even smarter over time.