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IBM’s Watson tackles crime

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IBM Security has announced Watson for Cyber Security, a new cloud-based version of the company’s cognitive technology trained on the language of security as part of a year-long research project.

To further scale the system, IBM plans to collaborate with eight universities to greatly expand the collection of security data IBM has trained the cognitive system with.

Training Watson for Cyber Security is a critical step in the advancement of cognitive security. Watson is learning the nuances of security research findings and discovering patterns and evidence of hidden

cyber attacks and threats that could otherwise be missed. Starting this fall, IBM will work with leading universities and their students to further train Watson on the language of cybersecurity, including: California State Polytechnic University, Pomona; Pennsylvania State University; Massachusetts Institute of Technology; New York University; the University of Maryland, Baltimore County (UMBC); the University of New Brunswick; the University of Ottawa and the University of Waterloo.

Today’s news is part of a pioneering cognitive security project to address the looming cybersecurity skills gap. IBM efforts are designed to improve security analysts’ capabilities using cognitive systems that automate the connections between data, emerging threats and remediation strategies. IBM intends to begin beta production deployments that take advantage of IBM Watson for Cyber Security later this year.

IBM’s world-renowned X-Force research library will be a central part of the materials fed to Watson for Cyber Security. This body of knowledge includes 20 years of security research, details on 8 million spam and phishing attacks and over 100,000 documented vulnerabilities.

Watson to Address Looming Security Skills Gap

The volume of security data presented to analysts is staggering. The average organization sees over

200,000 pieces of security event data per day1 with enterprises spending $1.3 million a year dealing with false positives alone, wasting nearly 21,000 hours2. Couple this with 75,000-plus known software vulnerabilities reported in the National Vulnerability Database3, 10,000 security research papers published each year and over 60,000 security blogs published each month4– and security analysts are severely challenged to move with informed speed.

Designed on the IBM Cloud, Watson for Cyber Security will be the first technology to offer cognition of security data at scale using Watson’s ability to reason and learn from “unstructured data” – 80 percent of all data on the internet that traditional security tools cannot process, including blogs, articles, videos, reports, alerts, and other information. In fact, IBM analysis found that the average organization leverages only 8 percent of this unstructured data. Watson for Cyber Security also uses natural language processing to understand the vague and imprecise nature of human language in unstructured data.

As a result, Watson for Cyber Security is designed to provide insights into emerging threats, as well as recommendations on how to stop them, increasing the speed and capabilities of security professionals.

IBM will also incorporate other Watson capabilities including the system’s data mining techniques for outlier detection, graphical presentation tools and techniques for finding connections between related data points in different documents. For example, Watson can find data on an emerging form of malware in an online security bulletin and data from a security analyst’s blog on an emerging remediation strategy.

“Even if the industry was able to fill the estimated 1.5 million open cyber security jobs by 2020, we’d still have a skills crisis in security,” said Marc van Zadelhoff, General Manager, IBM Security. “The volume and velocity of data in security is one of our greatest challenges in dealing with cybercrime. By leveraging Watson’s ability to bring context to staggering amounts of unstructured data, impossible for people alone to process, we will bring new insights, recommendations, and knowledge to security professionals, bringing greater speed and precision to the most advanced cybersecurity analysts, and providing novice analysts with on-the-job training.”

Universities to Help Train IBM Watson for Cyber Security

IBM plans to collaborate with eight universities that have some of the world’s best cybersecurity programs to further train Watson and introduce their students to cognitive computing. The universities include: California State Polytechnic University, Pomona; Pennsylvania State University; Massachusetts Institute of Technology; New York University; UMBC; the University of New Brunswick; the University of Ottawa and the University of Waterloo.

Students will help train Watson on the language of cybersecurity, initially working to help build Watson’s corpus of knowledge by annotating and feeding the system security reports and data. As students work closely with IBM Security experts to learn the nuances of these security intelligence reports, they’ll also be amongst the first in the world to gain hands-on experience in this emerging field of cognitive security.

This work will build on IBM’s work in developing and training Watson for Cyber Security. IBM currently plans to process up to 15,000 security documents per month over the next phase of the training with the university partners, clients and IBM experts collaborating.

These documents will include threat intelligence reports, cybercrime strategies and threat databases. Training Watson will also help build the taxonomy for Watson in cybersecurity including the understanding of hashes, infection methods and indicators of compromise and help identify advanced persistent threats.

In another effort to further scientific advancements in cognitive security, UMBC also announced a multi-year collaboration with IBM Research to create an Accelerated Cognitive Cybersecurity Laboratory (ACCL) in the College of Engineering and Information Technology. Faculty and students working in the ACCL will apply cognitive computing to complex cybersecurity challenges to build upon their own prior research. They will also collaborate with IBM scientists and leverage IBM’s advanced computing systems to add speed and scale to new cybersecurity solutions.

“This collaboration will allow our students and faculty to work with IBM to advance the state-of-the-art in cognitive computing and cybersecurity,” said Anupam Joshi, director of UMBC’s Center for Cybersecurity and chair of computer science and electrical engineering, at UMBC, who will lead the ACCL at UMBC.

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Smart home arrives in SA

The smart home is no longer a distant vision confined to advanced economies, writes ARTHUR GOLDSTUCK.

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The smart home is a wonderful vision for controlling every aspect of one’s living environment via remote control, apps and sensors. But, because it is both complex and expensive, there has been little appetite for it in South Africa.

The two main routes for smart home installation are both fraught with peril – financial and technical.

The first is to call on a specialist installation company. Surprisingly, there are many in South Africa. Google “smart home” +”South Africa”, and thousands of results appear. The problem is that, because the industry is so new, few have built up solid track records and reputations. Costs vary wildly, few standards exist, and the cost of after-sales service will turn out to be more important than the upfront price.

The second route is to assemble the components of a smart home, and attempt self-installation. For the non-technical, this is often a non-starter. Not only does one need a fairly good knowledge of Wi-Fi configuration, but also a broad understanding of the Internet of Things (IoT) – the ability for devices to sense their environment, connect to each other, and share information.

The good news, though, is that it is getting easier and more cost effective all the time.

My first efforts in this direction started a few years ago with finding smart plugs on Amazon.com. These are power adaptors that turn regular sockets into “smart sockets” by adding Wi-Fi and an on-off switch, among other. A smart lightbulb was sourced from Gearbest in China. At the time, these were the cheapest and most basic elements for a starter smart home environment.

Via a smartphone app, the light could be switched on from the other side of the world. It sounds trivial and silly, but on such basic functions the future is slowly built.

Fast forward a year or two, and these components are available from hundreds of outlets, they have plummeted in cost, and the range of options is bewildering. That, of course, makes the quest even more bewildering. Who can be trusted for quality, fulfilment and after-sales support? Which products will be obsolete in the next year or two as technology advances even more rapidly?

These are some of the challenges that a leading South African technology distributor, Syntech, decided to address in adding smart home products to its portfolio. It selected LifeSmart, a global brand with proven expertise in both IoT and smart home products.

Equally significantly, LifeSmart combines IoT with artificial intelligence and machine learning, meaning that the devices “learn” the best ways of connecting, sharing and integrating new elements. Because they all fall under the same brand, they are designed to integrate with the LifeSmart app, which is available for Android and iOS phones, as well as Android TV.

Click here to read about how LifeSmart makes installing smart home devices easier.

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Matrics must prepare for AI

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students writing a test

By Vian Chinner, CEO and founder of Xineoh.

Many in the matric class of 2018 are currently weighing up their options for the future. With the country’s high unemployment rate casting a shadow on their opportunities, these future jobseekers have been encouraged to look into which skills are required by the market, tailoring their occupational training to align with demand and thereby improving their chances of finding a job, writes Vian Chinner – a South African innovator, data scientist and CEO of the machine learning company specialising in consumer behaviour prediction, Xineoh.

With rapid innovation and development in the field of artificial intelligence (AI), all careers – including high-demand professions like engineers, teachers and electricians – will look significantly different in the years to come.

Notably, the third wave of internet connectivity, whereby our physical world begins to merge with that of the internet, is upon us. This is evident in how widespread AI is being implemented across industries as well as in our homes with the use of automation solutions and bots like Siri, Google Assistant, Alexa and Microsoft’s Cortana. So much data is collected from the physical world every day and AI makes sense of it all.

Not only do new industries related to technology like AI open new career paths, such as those specialising in data science, but it will also modify those which already exist. 

So, what should matriculants be considering when deciding what route to take?

For highly academic individuals, who are exceptionally strong in mathematics, data science is definitely the way to go. There is, and will continue to be, massive demand internationally as well as locally, with Element-AI noting that there are only between 0 and 100 data scientists in South Africa, with the true number being closer to 0.

In terms of getting a foot in the door to become a successful data scientist, practical experience, working with an AI-focused business, is essential. Students should consider getting an internship while they are studying or going straight into an internship, learning on the job and taking specialist online courses from institutions like Stanford University and MIT as they go.

This career path is, however, limited to the highly academic and mathematically gifted, but the technology is inevitably going to overlap with all other professions and so, those who are looking to begin their careers should take note of which skills will be in demand in future, versus which will be made redundant by AI.

In the next few years, technicians who are able to install and maintain new technology will be highly sought after. On the other hand, many entry level jobs will likely be taken care of by AI – from the slicing and dicing currently done by assistant chefs, to the laying of bricks by labourers in the building sector.

As a rule, students should be looking at the skills required for the job one step up from an entry level position and working towards developing these. Those training to be journalists, for instance, should work towards the skill level of an editor and a bookkeeping trainee, the role of financial consultant.

This also means that new workforce entrants should be prepared to walk into a more demanding role, with more responsibility, than perhaps previously anticipated and that the country’s education and training system should adapt to the shift in required skills.

The matric classes of 2018 have completed their schooling in the information age and we should be equipping them, and future generations, for the future market – AI is central to this.

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