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Energy companies struggling to counter IoT security risks, finds research

By Zenobia Hegde

While the majority of energy companies are turning to the Internet of Things (IoT) to help them meet growing demands for power and operate with greater efficiency, too many lack the security procedures to successfully deploy IoT solutions. This is according to the latest research from Inmarsat (ISAT.L), which found that more than half of global energy businesses do not have the skills and understanding required to combat the security risks associated with IoT.

In May 2017 market research specialist Vanson Bourne interviewed senior IT decision makers from 100 large energy companies across the globe for Inmarsat’s ‘The Future of IoT in Enterprise – 2017′ report. The research found that 53% of energy businesses identified a need to make heavy investments to meet both physical and digital IoT security requirements, and more than half (54%) reported that they needed additional digital skills in security to deliver successful IoT projects.

Moreover, just 30% reported that they have given special consideration to network security as part of the development of their IoT solutions, while only 38% have taken additional steps to protect against cyber-attacks.

These IoT security challenges may stem from a lack of understanding of IoT at board level within these organisations, potentially making it more difficult for project teams to secure the investment they need to effectively counter IoT security threats. In fact, according to the research, almost six in ten (59%) energy respondents stated that their board had either a partial or no understanding of IoT at all.

Commenting on the findings, Chuck Moseley, senior director for Energy at Inmarsat Enterprise said, “IoT represents a fundamental change in the way that energy grid networks and organisations will operate. The core operations of energy companies have traditionally been insulated from the destructive cyber-attacks that have destabilised other industries, as they were not connected to the internet.

But, with the advent of IoT, more and more parts of their infrastructure are being connected, creating new vulnerabilities and risks. Worryingly, our research shows that many energy businesses lack the security processes and skills to address these new vulnerabilities. This needs to be quickly addressed, and it must be driven by senior leadership within energy businesses, to ensure that they do not miss out on the huge potential value that IoT can bring to the energy sector.”

Moseley concluded: “For energy companies to thrive in this climate, IoT security needs to be at the top of the agenda and it is essential that boards raise their understanding of the risks they face. This involves ensuring that the fundamental network infrastructure underpinning device connectivity aligns with the highest security and reliability standards, and that the end points are configured correctly.”

Satellite communications networks can offer a more secure and reliable method of enabling energy companies to safely transport data from their connected things to and from anywhere on the planet. With up to 99.9% uptime, Inmarsat’s L-band services are enabling IoT solutions in the energy sector globally, even in the most remote and hostile environments.

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Seek Thermal To Debut New Technology and White Paper at the IoT Tech Expo North America

By IoT – Internet of Things

Seek Thermal™, the company behind some of the most groundbreaking, low cost, and high-resolution thermal imaging products and core platforms, is exhibiting at the IoT Tech Expo North America, November 29-30, 2017 in Santa Clara, CA.At the show, Seek Thermal is showcasing the company’s thermal imaging technology and demonstrating a concept designed specifically for IoT. […]

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Interconnecting legacy technologies and LTE will revolutionise operations in MCC, says ETELM

By Zenobia Hegde

Technologies in Mission Critical Communications (MCC) are incorporating functionality with LTE, but during this transition period, the performance must not be affected, says Pierre Minot, president of ETELM, a manufacturer of advanced Mission Critical communications infrastructures.

Speaking during a session titled ‘PMR broadband communication – technical implementation’ at PMRExpo in Germany, Minot commented: “LTE offers new broadband and data-hungry possibilities; however, it brings its own challenges. At present, there is a major drive to introduce more MC standards by working with users and manufacturers to ensure services are adopted internationally.”

“The process of standardisation is a long one – it takes time for standards to be tested and vendors to implement enhancements. While LTE is currently being utilised with consumers in mind, it is expected to take around five to seven years to reach full maturity for MC users, although certain features will be implemented sooner.”

ETELM has long championed LTE and TETRA working together, as opposed to replacing each other. This will enable legacy equipment and infrastructure to be revitalised, without the expense of upgrades each time a new technology becomes available. Minot explained the different use cases of migration from TETRA to LTE and the challenges that each of these use cases bring in terms of services, performances and devices.

Minot continued: “As smart cities develop around the world, it is important that MCC infrastructures are built during the initial planning, development, and design phase, rather than being an afterthought. This is the only way to ensure smart cities become safe cities. As blue light services continue to face increasingly challenging and complex situations, there is a need to bridge the channels between individual services, so they may come together and act as one, while utilising advanced applications.”

In response to the need for hybrid networks, ETELM’s 4GLinked solution is the first fully integrated platform connecting multiple MC technologies over a single LTE EPC core, allowing seamless communications and services across technologies – to the benefit of any use case.

“Performance is a key factor that only a fully standardised solution that doesn’t bring any third-party technology can ensure,”continued Minot. “With ETELM’s 4GLinked solution, it is one unified, standardised platform that is much easier to maintain and operate than having several infrastructures connected by gateways.”

4GLinked was successfully tested with many vendors at the ETSI MCPTT Plugtests in June 2017 and all interfaces are compliant with ETSI/3GPP LTE rel13. 4GLinked has also been successfully deployed and tested by customers.

ETELM is well known for its more than 35 years’ experience developing advanced radio communications infrastructure. With continuous innovations, ETELM has overcome legacy issues by integrating its TETRA solution to the LTE Core, which enables its TETRA base stations to connect directly to the same LTE Core network as any 4G LTE base station.

To find out more about ETELM, visit booth F01 at PMRExpo in Frankfurt, Germany (28-30 November 2017), or for further information, visit the website.

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Maxim Integrated Showcases Turnkey Security Solutions for Protecting Embedded Systems at TRUSTECH 2017

By IoT – Internet of Things

At TRUSTECH 2017 in Cannes, France (November 28-30, 2017), Maxim Integrated Products, Inc. will demonstrate new turnkey technologies that protect embedded and connected systems from invasive attacks. As cyberattacks continue making headlines, design engineers struggle to safeguard their products while meeting stringent time-to-market and budget constraints. Meanwhile, safety standard certification costs continue to rise. Maxim’s embedded […]

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Huawei and Gemalto team up to accelerate NarrowBand IoT deployments

By Zenobia Hegde

To help device manufacturers meet a growing demand for long-lasting low-power NarrowBand (NB) IoT modules, Gemalto and Huawei – via its semiconductor arm, HiSilicon – are working together to develop the next generation of modules that combine an extra level of security and consume very low power.

By combining the expertise from both companies, these NB-IoT modules will help manufacturers reduce the cost and size of their devices, and lengthen the battery life of the devices to up to ten years.

NB IoT has been developed to address lower bit rates and lower cost segments, and works virtually anywhere. It offers ultra-low power consumption enabling devices to be battery operated for periods of up to 10 years. Applications include smart parking sensors, intruder and fire alarms, personal healthcare appliances, tracking devices, and street lamps to name a few. According to ABI Research, NB IoT modules connecting objects to networks are forecast to represent over 20% of all cellular shipments by 2021.

“2017 is the year of commercial NB IoT rollouts for us, and we will be building 30 such networks in 20 countries worldwide by the end of the year. Huawei has been a major player in this arena, and we continue to capitalise on this vast opportunity,” said XiongWei, president of LTE solution, Huawei.

“We look to supply the market with solutions that provide stable connectivity, low energy consumption, and cost efficiency. The network roll-out will now come with an enhanced integration and flexibility thanks to this collaboration with Gemalto.”

“The combination of our expertise in IoT cellular connectivity, and digital s​ecurity, and Huawei’s high-performance NB IoT chipsets will help device manufacturers and service providers take the plunge into cellular IoT mass deployment thanks to a standardised solution,” said Suzanne Tong-Li, SVP Greater China and Korea for Mobile Services and IoT and China president, Gemalto. “Our collaboration simplifies the implementatio​​​n of NB IoT projects combining solid security and flexibility.”

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Trusted Objects introduces its personalisation tool kit for IoT Secure Element prototyping and testing

By Zenobia Hegde

In the Internet of Things industry, many systems integrators and application developers are facing obstacles when developing and testing security solutions in their applications. Due to IoT market fragmentation, the personalisation of a small volume of Secure Elements can be challenging for an industry used to deal with billions of devices in a consolidated market.

To solve this issue and allow application developers to be totally reactive to market demands Trusted Objects is introducing its personalisation tool kit that allows systems integrators to effortlessly personalise Secure Elements in order to easily set up a Proof of Concept whenever they want to address new markets, develop new applications, or simply test new features.

Trusted Objects personalisation tool kit includes hardware equipment dedicated to initialising and personalising small quantities of Secure Elements. The kit is delivered with user-friendly software that allows application developers to start personalising their Secure Elements with just three clicks, and an installation guide. Security is a very serious matter at Trusted Objects, so while the tool kit usage is limited to downloading standardised test keys within the Secure Elements; it has to be operated in a secure environment compliant with Trusted Objects security guidelines.

When the application developers are ready to evolve from the POC to real-size applications, Trusted Objects and its partners propose their services to adapt personalisation procedures to large batches of Secure Elements with diversified keys, generated under secure conditions in a certified secure environment.

Trusted Objects personalisation tool kit will be available from January 2018 onwards.

Sami Anbouba, CEO of Trusted Objects, declares: “As security is now on top of the agenda of the IoT market, our aim is to facilitate the adoption of Secure Elements for end-to-end solutions. With our personalisation tool kit, application developers can start their POC within a very short time frame, and then, get our dedicated support when switching to a real life secure application.”

Trusted Objects will be exhibiting at Trustech, a major event for the secure transactions industry, taking place in Cannes, France, on November 28 – 30, 2017. Come and visit us on booth Lerins C 006.

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Huawei releases Site on Demand solution to help operators bridge digital divide in emerging markets

By Zenobia Hegde

Huawei has announced a Site on Demand solution that helps operators in emerging markets cut site total cost of ownership (TCO) by breaking down the boundaries of infrastructure and network equipment to improve network capabilities using cloud and big data technology.

The Site on Demand solution enables operators to more cost-efficiently provide MBB coverage and capacity, improve MBB penetration, and deliver interconnections to a greater number of users. This aim is to help operators in emerging markets to bridge the digital divide.

Huawei’s long experience working in emerging markets means the company better understands the challenges and opportunities of mobile broadband in these countries. The emerging markets represent enormous population and traffic dividends, and operators face serious challenges in developing MBB businesses due to weak infrastructure, difficult, time-consuming site acquisitions, and high O&M costs.

“Emerging markets cannot simply copy the mobile network solutions of developed markets,” explained Cao Ming, vice president of Huawei’s Wireless Network Product Line. “Instead, they need to have their own network development plans tailored to their business and service requirements. They need to select the most appropriate products and solutions to serve their purposes. Huawei is committed to making innovative wireless network solutions to help operators deliver better MBB services to more and more users.”

Huawei’s Site on Demand solution is designed to help operators in emerging markets address these challenges. The solution encompasses three new sites for a broad range of scenarios relying on innovations such as cloud technology, machine learning, and Site Hosting to save end-to-end (E2E) site TCO and improve investment efficiency for operators.

The new innovative sites include the integrated TubeStar solution for urban macro coverage, the PoleStar solution for suburban coverage, the RuralStar solution for accurate coverage in rural areas, and the VillaRadio solution for urban in-depth coverage. In these new sites, infrastructure and network equipment are tightly integrated, allowing for zero-site deployment, self-backhaul, and centralised power supply. This can reduce TCO by approximately 30% for urban deployments and over 50% for suburban network coverage.

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What’s Keeping Deep Learning In Academia From Reaching Its Full Potential?

By Scott Clark

Deep learning is gaining a foothold in the enterprise as a way to improve the development and performance of critical business applications. It started to gain traction in companies optimizing advertising and recommendation systems, like Google, Yelp, and Baidu. But the space has seen a huge level of innovation over the past few years due to tools like open-source deep learning frameworks–like TensorFlow, MXNet, or Caffe 2–that democratize access to powerful deep learning techniques for companies of all sizes. Additionally, the rise of GPU-enabled cloud infrastructure on platforms like AWS and Azure has made it easier than ever for firms to build and scale these pipelines faster and cheaper than ever before.

Now, its use is extending to fields like financial services, oil and gas, and many other industries. Tractica, a market intelligence firm, predicts that deep learning enterprise software spending will surpass $40 billion worldwide by 2024. Companies that handle large amounts of data are tapping into deep learning to strengthen areas like machine perception, big data analytics, and the Internet of Things.

In the academic world outside of computer science from physics to public policy, though, where deep learning is rapidly being adopted and could be hugely beneficial, it’s often used in a way that leaves performance on the table.

Where academia falls short

Getting the most out of machine learning or deep learning frameworks requires optimization of the configuration parameters that govern these systems. These are the tunable parameters that need to be set before any learning actually takes place. Finding the right configurations can provide many orders of magnitude improvements in accuracy, performance or efficiency. Yet, the majority of professors and students who use deep learning outside of computer science, where these techniques are developed, are often using one of three traditional, suboptimal methods to tune, or optimize, the configuration parameters of these systems. They may use manual search–trying to optimize high-dimensional problems by hand or intuition via trial-and-error; grid search–building an exhaustive set of possible parameters and testing each one individually at great cost; or randomized search–the most effective in practice, but unfortunately the equivalent of trying to climb a mountain by jumping out of an airplane hoping you eventually land on the peak.

(gor kisselev/Shutterstock)

While these methods are easy to implement, they often fall short of the best possible solution and waste precious computational resources that are often scarce in academic settings. Experts often do not apply more advanced techniques because they are so orthogonal to the core research they are doing and the need to find, administer, and optimize more sophisticated optimization methods often wastes expert time. This challenge can also cause experts to rely on less powerful but easier to tune methods, and not even attempt deep learning. While researchers have used these methods for years, it’s not always the most effective way to conduct research.

The need for Bayesian Optimization

Bayesian optimization automatically fine tunes the parameters of these algorithms and machine learning models without accessing the underlying data or model itself. The process probes the underlying system to observe various outputs. It detects how previous configurations have performed to determine the best, most intelligent thing to try next. This helps researchers and domain experts arrive at the best possible model and frees up time to focus on more pressing parts of their research.

Bayesian optimization has already been applied outside of deep learning to other problems in academia from gravitational lensing to polymer synthesis to materials design and beyond. Additionally, a number of professors and students are already using this method at universities like MIT, University of Waterloo and Carnegie Mellon to optimize their deep learning models and conduct life-changing research. George Chen, assistant professor at Carnegie Mellon’s Heinz College of Public Policy and Information Systems, uses Bayesian Optimization to fine tune the machine learning models he uses in his experiments. His research consists of medical imaging analysis that automates the process of locating a specific organ in the human body. The implications of his research could help prevent unnecessary procedures in patients with congenital heart defects and others. Before applying Bayesian Optimization to his research, Chen had to guess and check the best parameters for his data models. Now, he’s able to automate the process and receive updates on his mobile phone so he can spend time completing other necessary parts of the research process.

Unfortunately, the vast majority of researchers leveraging deep learning outside of academia are not using these powerful techniques. This costs them time and resources or even completely prevents them from achieving their research goals via deep learning. When those experts are forced to do multidimensional, guess-and-check equations in their head, they usually have to spend valuable computational resources on modeling and work with sub-optimal results. Deploying Bayesian Optimization can accelerate the research process, free up time to focus on other important tasks and unlock better outcomes.

Scott Clark is the co-founder and CEO of SigOpt, which provides its services for free to academics around the world.. He has been applying optimal learning techniques in industry and academia for years, from bioinformatics to production advertising systems. Before SigOpt, Scott worked on the Ad Targeting team at Yelp leading the charge on academic research and outreach with projects like the Yelp Dataset Challenge and open sourcing MOE. Scott holds a PhD in Applied Mathematics and an MS in Computer Science from Cornell University and BS degrees in Mathematics, Physics, and Computational Physics from Oregon State University. Scott was chosen as one of Forbes’ 30 under 30 in 2016.

Related Items:

Getting Hyped for Deep Learning Configs

Dealing with Deep Learning’s Big Black Box Problem

Machine Learning, Deep Learning, and AI: What’s the Difference?

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Interoute grows its global networked cloud platform in Asia Pacific

By Zenobia Hegde

Interoute, a global cloud and network provider, has opened a new point-of-presence (PoP) in Sydney, Australia. The PoP will host the 18th Interoute Virtual Data Centre (VDC) globally, the company’s third in the Asia Pacific region.

The announcement comes in response to customer demand for expanded global cloud coverage in the Asia Pacific region and extends the reach of Interoute’s new Edge SD-WAN services. Interoute Edge is used by customers to accelerate their enterprise data traffic around the world.

Using the global Interoute Cloud Fabric, public and private access networks can blend into one dynamic digital platform, where application traffic travels over the fastest available routes. The Interoute Cloud Fabric binds together all Interoute VDC cloud zones, co-location facilities, PoPs, as well as third-party cloud providers with Interoute’s ultra-low latency private network backbone.

Mark Lewis, EVP Products and Development at Interoute, said: “Sydney is a global city and businesses are demanding better local connectivity and compute capability to support their growth. As we continue to grow our footprint in the Asia Pacific region, opening a PoP in Sydney is an important step to providing businesses in this theatre with faster, more reliable and secure access to cloud and IT services.”

The Sydney location will be a core PoP on the Interoute network with local peering and resilient connectivity to Interoute’s Singapore and Hong Kong locations. It will host the 18th Interoute VDC global IaaS zone, giving customers the ability to launch virtual machines as well as Interoute Edge gateways.

With these services in Sydney set to go live in the first half of 2018, Interoute’s vast global network will expand to connect 127 major cities across 30 countries and 18 global cloud zones. Interoute offers customers a global ICT infrastructure platform that supports the integration of enterprise legacy IT with Digital environments.

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PTC to accelerate customers’ connected service strategy with launch of ThingWorx Asset Advisor

By Zenobia Hegde

PTC announced from PTC Forum Europe in Stuttgart, Germany, the launch of the ThingWorx® Asset Advisor app for service to accelerate its customers’ service transformation initiatives. ThingWorx® Asset Advisor for service enables remote monitoring and servicing of assets deployed in the field.

Built on PTC’s leading ThingWorx industrial innovation platform, ThingWorx Asset Advisor for service is a role-based app for service managers and technicians that is fast to deploy, scalable, flexible, and customisable. It provides visibility to connected assets with key role-intelligent information, offering insight into the operating condition of the asset, alerts on operating anomalies, and remote service for the connected assets.

ThingWorx Asset Advisor for service follows PTC’s launch of the ThingWorx Asset Advisor app for manufacturing this past June at LiveWorx®17 and continues PTC’s commitment to helping industrial companies simplify their digital transformation efforts.

As industrial companies focus on improving efficiency and reducing downtime of their operations, being able to connect and monitor assets to capture critical alerts in real-time is key to an effective connected service strategy. PTC has a long history of enabling customers to connect assets and remotely monitor, diagnose, and resolve service issues.

Customers adopting a connected service strategy helped PTC’s IoT business outpace the market growth rate of 30 to 40 percent in fiscal year 2017. Companies like Elekta, Diebold, Sysmex, and McKinley Elevator are improving first-time fix rates 30 percent more than industry averages; mean time to repair by 6X; and equipment uptime by 20 percent, by being able to remotely monitor and service connected assets.

The ThingWorx Asset Advisor app enables customers to accelerate the time to value by providing them with an even easier and faster path to connected service capabilities.

“The capabilities enabled through ThingWorx technology will help us deliver the machine uptime required by our customers in production environments,” said Antonio Lopez, vice president, global customer services, 3D Systems.

“Connected Service is a key use case for digital transformation by asset owners and operators. In fact, IDC believes that by 2020, 50% of global OEMs with connected service offerings will have incorporated augmented service execution and/or remote management, thus improving service margins by up to 30%. Using an IoT platform to enable this capability is a critical ingredient to success,” said Heather Ashton, research manager, Service Innovation and Connected Product Strategies, IDC.

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