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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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Prepare your cam to capture the Blood Moon

On 27 July 2018, South Africans can witness a total lunar eclipse, as the earth’s shadow completely covers the moon.

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Also known as a blood or red moon, a total lunar eclipse is the most dramatic of all lunar eclipses and presents an exciting photographic opportunity for any aspiring photographer or would-be astronomers.

“A lunar eclipse is a rare cosmic sight. For centuries these events have inspired wonder, interest and sometimes fear amongst observers. Of course, if you are lucky to be around when one occurs, you would want to capture it all on camera,” says Dana Eitzen, Corporate and Marketing Communications Executive at Canon South Africa.

Canon ambassador and acclaimed landscape photographer David Noton has provided his top tips to keep in mind when photographing this occasion.   In South Africa, the eclipse will be visible from about 19h14 on Friday, 27 July until 01h28 on the Saturday morning. The lunar eclipse will see the light from the sun blocked by the earth as it passes in front of the moon. The moon will turn red because of an effect known as Rayleigh Scattering, where bands of green and violet light become filtered through the atmosphere.

A partial eclipse will begin at 20h24 when the moon will start to turn red. The total eclipse begins at about 21h30 when the moon is completely red. The eclipse reaches its maximum at 22h21 when the moon is closest to the centre of the shadow.

David Noton advises:

  1. Download the right apps to be in-the-know

The sun’s position in the sky at any given time of day varies massively with latitude and season. That is not the case with the moon as its passage through the heavens is governed by its complex elliptical orbit of the earth. That orbit results in monthly, rather than seasonal variations, as the moon moves through its lunar cycle. The result is big differences in the timing of its appearance and its trajectory through the sky. Luckily, we no longer need to rely on weight tables to consult the behaviour of the moon, we can simply download an app on to our phone. The Photographer’s Ephemeris is useful for giving moonrise and moonset times, bearings and phases; while the Photopills app gives comprehensive information on the position of the moon in our sky.  Armed with these two apps, I’m planning to shoot the Blood Moon rising in Dorset, England. I’m aiming to capture the moon within the first fifteen minutes of moonrise so I can catch it low in the sky and juxtapose it against an object on the horizon line for scale – this could be as simple as a tree on a hill.

 

  1. Invest in a lens with optimal zoom  

On the 27th July, one of the key challenges we’ll face is shooting the moon large in the frame so we can see every crater on the asteroid pockmarked surface. It’s a task normally reserved for astronomers with super powerful telescopes, but if you’ve got a long telephoto lens on a full frame DSLR with around 600 mm of focal length, it can be done, depending on the composition. I will be using the Canon EOS 5D Mark IV with an EF 200-400mm f/4L IS USM Ext. 1.4 x lens.

  1. Use a tripod to capture the intimate details

As you frame up your shot, one thing will become immediately apparent; lunar tracking is incredibly challenging as the moon moves through the sky surprisingly quickly. As you’ll be using a long lens for this shoot, it’s important to invest in a sturdy tripod to help capture the best possible image. Although it will be tempting to take the shot by hand, it’s important to remember that your subject is over 384,000km away from you and even with a high shutter speed, the slightest of movements will become exaggerated.

  1. Integrate the moon into your landscape

Whilst images of the moon large in the frame can be beautifully detailed, they are essentially astronomical in their appeal. Personally, I’m far more drawn to using the lunar allure as an element in my landscapes, or using the moonlight as a light source. The latter is difficult, as the amount of light the moon reflects is tiny, whilst the lunar surface is so bright by comparison. Up to now, night photography meant long, long exposures but with cameras such as the Canon EOS-1D X Mark II and the Canon EOS 5D Mark IV now capable of astonishing low light performance, a whole new nocturnal world of opportunities has been opened to photographers.

  1. Master the shutter speed for your subject 

The most evocative and genuine use of the moon in landscape portraits results from situations when the light on the moon balances with the twilight in the surrounding sky. Such images have a subtle appeal, mood and believability.  By definition, any scene incorporating a medium or wide-angle view is going to render the moon as a tiny pin prick of light, but its presence will still be felt. Our eyes naturally gravitate to it, however insignificant it may seem. Of course, the issue of shutter speed is always there; too slow an exposure and all we’ll see is an unsightly lunar streak, even with a wide-angle lens.

 

On a clear night, mastering the shutter speed of your camera is integral to capturing the moon – exposing at 1/250 sec @ f8 ISO 100 (depending on focal length) is what you’ll need to stop the motion from blurring and if you are to get the technique right, with the high quality of cameras such as the Canon EOS 5DS R, you might even be able to see the twelve cameras that were left up there by NASA in the 60’s!

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How Africa can embrace AI

Currently, no African country is among the top 10 countries expected to benefit most from AI and automation. But, the continent has the potential to catch up with the rest of world if we act fast, says ZOAIB HOOSEN, Microsoft Managing Director.

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To play catch up, we must take advantage of our best and most powerful resource – our human capital. According to a report by the World Economic Forum (WEF), more than 60 percent of the population in sub-Saharan Africa is under the age of 25.

These are the people who are poised to create a future where humans and AI can work together for the good of society. In fact, the most recent WEF Global Shapers survey found that almost 80 percent of youth believe technology like AI is creating jobs rather than destroying them.

Staying ahead of the trends to stay employed

AI developments are expected to impact existing jobs, as AI can replicate certain activities at greater speed and scale. In some areas, AI could learn faster than humans, if not yet as deeply.

According to Gartner, while AI will improve the productivity of many jobs and create millions more new positions, it could impact many others. The simpler and less creative the job, the earlier, a bot for example, could replace it.

It’s important to stay ahead of the trends and find opportunities to expand our knowledge and skills while learning how to work more closely and symbiotically with technology.

Another global study by Accenture, found that the adoption of AI will create several new job categories requiring important and yet surprising skills. These include trainers, who are tasked with teaching AI systems how to perform; explainers, who bridge the gap between technologist and business leader; and sustainers, who ensure that AI systems are operating as designed.

It’s clear that successfully integrating human intelligence with AI, so they co-exist in a two-way learning relationship, will become more critical than ever.

Combining STEM with the arts

Young people have a leg up on those already in the working world because they can easily develop the necessary skills for these new roles. It’s therefore essential that our education system constantly evolves to equip youth with the right skills and way of thinking to be successful in jobs that may not even exist yet.

As the division of tasks between man and machine changes, we must re-evaluate the type of knowledge and skills imparted to future generations.

For example, technical skills will be required to design and implement AI systems, but interpersonal skills, creativity and emotional intelligence will also become crucial in giving humans an advantage over machines.

“At one level, AI will require that even more people specialise in digital skills and data science. But skilling-up for an AI-powered world involves more than science, technology, engineering and math. As computers behave more like humans, the social sciences and humanities will become even more important. Languages, art, history, economics, ethics, philosophy, psychology and human development courses can teach critical, philosophical and ethics-based skills that will be instrumental in the development and management of AI solutions.” This is according to Microsoft president, Brad Smith, and EVP of AI and research, Harry Shum, who recently authored the book “The Future Computed”, which primarily deals with AI and its role in society.

Interestingly, institutions like Stanford University are already implementing this forward-thinking approach. The university offers a programme called CS+X, which integrates its computer science degree with humanities degrees, resulting in a Bachelor of Arts and Science qualification.

Revisiting laws and regulation

For this type of evolution to happen, the onus is on policy makers to revisit current laws and even bring in new regulations. Policy makers need to identify the groups most at risk of losing their jobs and create strategies to reintegrate them into the economy.

Simultaneously, though AI could be hugely beneficial in areas such as curbing poor access to healthcare and improving diagnoses for example, physicians may avoid using this technology for fear of malpractice. To avoid this, we need regulation that closes the gap between the pace of technological change and that of regulatory response. It will also become essential to develop a code of ethics for this new ecosystem.

Preparing for the future

With the recent convergence of a transformative set of technologies, economies are entering a period in which AI has the potential overcome physical limitations and open up new sources of value and growth.

To avoid missing out on this opportunity, policy makers and business leaders must prepare for, and work toward, a future with AI. We must do so not with the idea that AI is simply another productivity enhancer. Rather, we must see AI as the tool that can transform our thinking about how growth is created.

It comes down to a choice of our people and economies being part of the technological disruption, or being left behind.

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