Category Archives: artificial intelligence

Disruptive technology predictions: 2020 will see the creation of completely connected environments

Mainstream adoption of disruptive technologies in 2020 will finally see data, automation and IoT technologies come together to create connected cities and societies, NTT predicts. The company predicts that 2020 will finally see all the hype words of the past decade come together to create completely connected environments that are capable of running themselves autonomously to build more intelligent cities, workplaces and businesses – and on a secure basis. Data, AI and secure by design … More

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OpenText Enfuse 2019: The Carbonite acquisition, new apps, and updates

LAS VEGAS — The topic of endpoint security was front and centre on the first day of OpenText Enfuse 2019.

OpenText’s chief executive officer, Mark Barrenechea, said in his keynote that endpoint security becomes all the more vital as cloud computing continues to accelerate.

“We look at the momentum of moving into the cloud. You’re in a five to six-year window where everything will be centralized and operating in the cloud,” said Barrenechea. “As more gets centralized into the cloud, it just exposes how important that edge is.”

The topic of endpoint security was especially relevant yesterday after the Waterloo-based company announced its intent to acquire Carbonite for just under $1.5 billion, continuing its aggressive acquisition strategy over the last couple of years, which includes Liaison Technologies and Hightail.

Although the acquisition is not expected to officially finalize for about 90 days, Barrenechea expressed his excitement about what Carbonite will bring to OpenText’s endpoint security portfolio.

Barrenechea said the endpoint is strategic and this acquisition signals OpenText’s “commitment of winning at the endpoint”.

According to Barrenechea, OpenText already secures about 40 million endpoints, but once Carbonite is officially brought into the fold, that number will increase to about 100 million.

Most importantly in what Carbonite brings to the table, according to OpenText’s chief product officer, Muhi Majzoub, is the endpoint antivirus and the data backup for endpoint devices which allows users to simply wipe their devices and move on rather than be held hostage by ransomware.

Although what they bring from a solutions standpoint is important, Majzoub pointed out that he thinks this should be seen as a big move for OpenText into the SMB world; as Carbonite brings with it experience and customers in that space.

OpenText Enfuse 2019 kicked off on Tuesday in Las Vegas with a bevy of announcements. Credit: Buckley Smith

Updated security portfolio

Beyond the Carbonite announcement, OpenText also used its bi-annual solutions and updates release to announce a bevy of updates to its security portfolio.

Barrenechea continued to emphasize the importance of security in his keynote, saying that security needs to be “job #1”.

“It has to be all the way from the boardroom, to the CEO, to the company leadership team, the dev-ops team, in engineering, in the human behavior,” he said.

With this in mind, he noted that this same prioritization of security needs to be applied to software.

The updates to OpenText’s security platform include:

  • Threat Hunting Service is a new service which provides customers with a team of OpenText security experts using EnCase Endpoint Security and Magellan to aid in the quick identification, monitoring, and remediation of threats.
  • EnCase TM Endpoint Security improves endpoint detection and response capabilities to assist security teams in finding and removing threat actors from networks in quicker turnaround times.
  • EnCase TM Forensics delivers updates to indexing and search capabilities. The update also allows users to browse the Apple File System snapshot as well as access a collection of Microsoft OST artifacts.
  • Tableau Forensic Imager will now provide users the ability to pause and resume any forensic imaging jobs, even after a power cycle.

New solutions from OpenText

While the first day of OpenText Enfuse 2019 saw a number of updates to existing solutions and portfolios, the company did announce two new applications.

The first one was Core for Federated Compliance – available now for Documentum – which is a centralized application designed to provide oversight of the records policies across a multitude of content repositories.

The second new release was Core Experience Insights. This SaaS application is designed to provide marketing departments with visibility over the customer experience journey. This includes website interactions, social media content, email engagement, and call centre performance.

Old apps moving to the cloud

In his keynote, Barrenechea pointed out in the last year, venture capital funds invested zero dollars to on-premise software, while cloud software received 100 per cent of software investment.

And with that in mind, several of OpenText’s top existing solutions are getting the cloud-native treatment. This includes Content Services, Content Suite Platform, Documentum, Extended ECM Platform, and InfoArchive.

This will bring with it automatic updates and the ability to run the apps both on and off the cloud. The company said in its release that it is looking at this as a big step towards the launch of OpenText Cloud Editions in 2020.

It is likely that we will see much more of this in the future as Barrenechea explained that he believes everything (not just OpenText solutions) will be in the cloud in the next five to six years.

EIM solutions updates

It wouldn’t be an Enfuse event without some announcements about OpenText’s enterprise information management solutions. Updates to the portfolio include:

  • Automated machine-translations of documents in global investigations and automated sentiment analysis were added to Axcelerate – OpenText’s platform for eDiscovery and investigations – in partnership with Veritone.
  • eDocs – OpenText’s electronic document management solution – has been updated to include AI-powered search.
  • Web Content Management Solution now includes content suggestion generation and translation.
  • Updates to Extended ECM Platform will allow users to automate multiple simultaneous content-driven processes through asynchronous processing.
  • Vendor Invoice Management will now be able to automate content-related processes, powered by machine learning and optical character recognition.
  • New integrations between the Experience portfolio and Hightail, Google Translate, Brightcove’s video hosting platform, Salesforce, the Salesforce Marketing Cloud, and SAP.
  • New integrations for Documentum for Life Sciences with Microsoft SharePoint Online and OpenText’s Contract Center is now integrated with SAP.
  • New visualizations in Magellan Analytics Studio.
  • New authoring tools in Exstream – OpenText’s customer communications management platform.
  • A new mobile app for Documentum – OpenText’s ECM suite.

Legal solutions

OpenText’s legal industry solutions also received updates, including:

  • New AI features like sentiment analysis and entity extraction powered by Magellan – OpenText’s AI and analytics platform – for Axcelerate, allowing for the automatic detection of people and places referenced in sets of documents while organizing communications by tone and emotional language.
  • Axcelerate has added automated machine translations powered by Veritone’s aiWARE – an AI operating system – which will automatically translate over 29 languages to English.
  • eDOCS MindServer – OpenText’s AI-enhanced search engine that powers OpenText
    Axcelerate – is being added to the legal portfolio to securely crawl and index information to draw out relevant information without the need to know precise keywords.

Google publicizes Ascension partnership after healthcare data reveal

Google has unveiled its partnership with Ascension, one of U.S.’s largest healthcare providers, hours after a Wall Street Journal article revealed that the search giant has been collecting detailed personal health data without notifying the doctors or patients.

The report detailed “Project Nightingale”, a collaboration between Google and Ascension to create a predictive patient care program. Wall Street Journal wrote that around 150 Google employees had access to lab results, doctor diagnoses, and hospitalization records amounting to a complete health history, with patient names and dates of birth, all without notifying doctors or patients. 

As a non-profit organization, Ascension operates more than 2,600 sites across 21 states, including 151 hospitals and more than 50 senior care facilities.

Google has been fiercely competing in the healthcare space. Over the years, it has worked with healthcare organizations including Cleveland Clinic, American Cancer Society, and Doctors on Demand. At its Google I/O 2018 keynote, Google Chief Executive Officer Sundar Pichai demonstrated how AI can be used to diagnose diabetic retinopathy.

Both Google and Ascension released their respective press releases just hours after the Wall Street Journal’s article was published.

In its press release, Google maintained that its work complies with industry regulations. It specifically mentioned the Health Insurance Portability and Accountability Act (HIPAA), a law passed in 1996 that outlines the protection and confidential handling of sensitive health data. HIPAA restricts how doctors and healthcare providers can share and use patient information.

Google also detailed its other projects with Ascension. Aside from creating healthcare AI solutions, it’s also looking to host Ascension’s infrastructures and providing G Suite productivity tools.

Ascension said that all data is guarded by “robust data security and protection effort”.

 

Analytics 101

From today’s smart home applications to autonomous vehicles of the future, the efficiency of automated decision-making is becoming widely embraced. Sci-fi concepts such as “machine learning” and “artificial intelligence” have been realized; however, it is important to understand that these terms are not interchangeable but evolve in complexity and knowledge to drive better decisions.

Distinguishing Between Machine Learning, Deep Learning and Artificial Intelligence

Put simply, analytics is the scientific process of transforming data into insight for making better decisions. Within the world of cybersecurity, this definition can be expanded to mean the collection and interpretation of security event data from multiple sources, and in different formats for identifying threat characteristics.

Simple explanations for each are as follows:

  • Machine Learning: Automated analytics that learn over time, recognizing patterns in data.  Key for cybersecurity because of the volume and velocity of Big Data.
  • Deep Learning: Uses many layers of input and output nodes (similar to brain neurons), with the ability to learn.  Typically makes use of the automation of Machine Learning.
  • Artificial Intelligence: The most complex and intelligent analytical technology, as a self-learning system applying complex algorithms which mimic human-brain processes such as anticipation, decision making, reasoning, and problem solving.

Benefits of Analytics within Cybersecurity

Big Data, the term coined in October 1997, is ubiquitous in cybersecurity as the volume, velocity and veracity of threats continue to explode. Security teams are overwhelmed by the immense volume of intelligence they must sift through to protect their environments from cyber threats. Analytics expand the capabilities of humans by sifting through enormous quantities of data and presenting it as actionable intelligence.

While the technologies must be used strategically and can be applied differently depending upon the problem at hand, here are some scenarios where human-machine teaming of analysts and analytic technologies can make all the difference:

  • Identify hidden malware with Machine Learning: Machine Learning algorithms recognize patterns far more quickly than your average human. This pattern recognition can detect behaviors that cause security breaches, whether known or unknown, periodically “learning” to become smarter. Machine Learning can be descriptive, diagnostic, predictive, or prescriptive in its analytic assessments, but typically is diagnostic and/or predictive in nature.
  • Defend against new threats with Deep Learning: Complex and multi-dimensional, Deep Learning reflects similar multi-faceted security behaviors in its actual algorithms; if the situation is complex, the algorithm is likely to be complex. It can detect, protect, and correct old or new threats by learning what is reasonable within any environment and identifying outliers and unique relationships.  Deep Learning can be descriptive, diagnostic, predictive, and prescriptive as well.
  • Anticipate threats with Artificial Intelligence: Artificial Intelligence uses reason and logic to understand its ecosystem. Like a human brain, AI considers value judgements and outcomes in determining good or bad, right or wrong.  It utilizes a number of complex analytics, including Deep Learning and Natural Language Processing (NLP). While Machine Learning and Deep Learning can span descriptive to prescriptive analytics, AI is extremely good at the more mature analytics of predictive and prescriptive.

With any security solution, therefore, it is important to identify the use case and ask “what problem are you trying to solve” to select Machine Learning, Deep Learning, or Artificial Intelligence analytics.  In fact, sometimes a combination of these approaches is required, like many McAfee products including McAfee Investigator.  Human-machine teaming as well as a layered approach to security can further help to detect, protect, and correct the most simple or complex of breaches, providing a complete solution for customers’ needs.

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