An Agenda for Establishing Secure and Resilient Smart Cities

by Dr. Steve Griffiths

The Rise of Smart Cities 

Today more than half of the world’s population lives in cities, and by 2050 this percentage is expected to rise to nearly 70 percent. In parallel to rapid growth in urbanization, technological progress has led to the mass proliferation of digital information about people, places, and things that can be rapidly transmitted and analyzed with increasingly powerful networking technologies and analytical tools. This digital proliferation is synonymous with the internet-of-things, or IoT, and has converged with urbanization to create the paradigm of “smart” cities.

A smart city is not just technologically advanced; it is a platform for the sustainable and inclusive enhancement of nearly all aspects of society. However, achieving such positive outcomes as smart cities evolve is not a simple task.  

The Evolution of Smart Cities 

While urbanization and technology have laid the foundation for smart cities, the COVID-19 pandemic that emerged in 2020 may ultimately shape long-term implementations. 

As a result of social distancing mandates implemented to mitigate disease spread, smart city technologies and services for healthcare, work, education, retail, finance, security, entertainment, food services, mobility, and essentially any other activity requiring human interaction have undergone both acceleration and transformation.

Although the fundamental architecture of smart cities remains centered around an IoT foundation upon which applications are built for defined use cases, the use cases themselves have both evolved and accelerated in their implementation. 

In healthcare alone, activities such as telemedicine, contact tracing, public health messaging, mobility pattern analysis, and robotic patient care have emerged and begun to transform the notion of healthcare delivery from one of in-person interaction to one of digital engagement. 

Likewise, urban transportation is seeing significant changes due to changing social practices resulting from the pandemic and government policies being implemented for pandemic recovery. Digital technologies will play a key role in these changes as efforts to reestablish demand for public transportation increasingly focus on flexible transit scheduling and planning and the development of multimodal digital platforms that integrate public transportation with bikes, scooters, ride-hailing, and other mobility modes. 

In short, even the most established smart cities face the innovation challenge of re-imagining city operations for a new era of heightened concerns for health and resiliency, the latter of which additionally factors into climate change considerations. Similar to the COVID-19 pandemic, climate change is now generally recognized as a globally disruptive and destructive issue that must be mitigated through increased government efforts that include the design, implementation, and operation of smart cities. 

While the noted trend towards increased city intelligence through digitalization affords many opportunities for improving the lives of citizens, it also creates a number of security concerns. 

The rapid growth in digital information collection, storage, and use has opened up multiple new attack surfaces for cyber-terrorism, cyber-warfare, and cyber-crime. While cyber-terrorism and cyber-warfare often have social and political motivations, cyber-crime is tied largely to commercial and economic interests and can impart significant financial costs on victims. Indeed, the financial impact of cyber-crimes is expected to amount to as much as US$6 trillion in 2021 considering damage and destruction of data, stolen money, lost productivity, theft of intellectual property, theft of personal and financial data, embezzlement, fraud, post-attack disruption to business operations, forensic investigation, restoration and deletion of hacked data and systems and/or reputational harm. 

This considerable cost is expected to rise to as much as US$10.5 trillion by 2025 as the storage of digital data rises in the coming years. The accumulation of digital data has only hastened as a result of the COVID-19 pandemic as the extent of consumer online interactions has been accelerated by three to four years and the extent of business product and service digitalization has been accelerated by six to ten years.  

The rapid, and now accelerated, pace of digital activity places a great burden on smart city infrastructure as operational technologies (OT) and information technologies (IT) converge to offer new services and capabilities. Legacy OT systems that are not secure combined with the proliferation of novel, but insecure, digital devices combine to make cybersecurity and cyber resilience urgent for smart cities. Preservation of the confidentiality, integrity, and availability of information in cyberspace coupled with the capacity for rapid recovery from cyber incidents must sit at the top of cyber secure and cyber resilient smart city agendas. 

A Forward-Looking Agenda for Smart Cities  

The sharing of international expertise, technologies, and best practices can play an important role in achieving cyber secure and cyber resilient smart cities. The United Arab Emirates, Singapore, and Israel are three highly urbanized countries that are aligned in their ambitions for innovation and security in the urban context. While each country scores highly in international innovation rankings, Singapore is particularly advanced in smart city technology innovation while Israel is a global leader in cyber security innovation. 

The UAE has rapidly built smart city visibility, particularly related to developments in the emirates of Abu Dhabi and Dubai, and has visible initiatives to ensure that these cities are cyber secure and resilient, including the 2020 formation of a Cybersecurity Council headed by a recently appointed government Head of Cyber Security. 

Among emirate level initiatives, Dubai has established a Cyber Security Strategy and in Abu Dhabi, the Advanced Technology Research Council (ATRC) was formed in 2020 and has set forth a research and development strategy that clearly puts cybersecurity at the forefront by including cryptography, digital security, and secure systems as three of seven top priority research areas for the emirate.  

An agenda for smart city collaboration among the UAE, Singapore and Israel would certainly involve the exchange of best practices regarding legal and regulatory frameworks as well as engagement in technology investment and trade. 

However, ecosystem development is what underpins long-term sustainability and hence international collaboration should further entail targeted initiatives addressing human capital, R&D, and innovation. Human capital development is very important given the growing shortage of skilled cyber security manpower. R&D supports the development of human capital and further brings value to the development of cutting-edge approaches to smart city services, security, and resiliency. 

R&D topics of particular merit within the cyber security context include the protection of edge devices, application of artificial intelligence techniques, application of blockchain, and in the coming years, the implementation of quantum technologies. Innovation further builds on human capital and R&D advances to establish commercially viable new technologies tailored to applications.

On this latter point, R&D and innovation collaboration may focus on specific smart city sectors of common interest and growing importance. Given that both healthcare and transportation are being re-imagined as a result of COVID-19, focused initial collaboration efforts in these domains, for instance, could lead to large rewards for all involved. 

Urbanization and technological trends make the rise of smart cities inevitable. As discussed in this paper, however, smart cities will inherently face threats and challenges. Collaboration among countries that have common interests in securing a successful future for their smart cities can help mitigate these threats. The UAE, Singapore, and Israel are three such countries that can reap the benefits of collaboration through a holistic partnership that addresses human capital, R&D, and innovation while taking into consideration applications with both near and long-term importance. 

The full conference session to which the story relates is available online, here:

Dr. Steve Griffiths is the Senior Vice President of Research and Development and Professor of Practice at Khalifa University. 

The post The Role of Tech-Building Resilience through Smart Cities and Cybersecurity appeared first on Khalifa University.

A Global Effort to Capture the Most Elusive Culprit

For something presumed so essential to the structure of galaxies and, by extension, the universe, we know surprisingly little about black holes. A major reason for knowing so little is due to the fact we can’t even see them; we see light, and not even light can escape a black hole’s immense gravitational pull. Nearly a century’s theoretical physics indicates that black holes were pervasive throughout the cosmos, a widely accepted view among physicists, despite the absence of any tangible evidence.

Albert Einstein had a few doubts as to whether his theory -that matter can curve space and time- was correct. His theory of general relativity hinged on the idea of areas of space with massive amounts of gravity. We’ve witnessed hints of the existence of black holes since 1990, typically when a star ventured too close to one, but a direct observation of an event horizon remained elusive. Until now.

With the publication of the first ever picture of a black hole this month, any residual doubt that they exist is gone. The image is a groundbreaking achievement for the Event Horizon Telescope (EHT), an international observatory spanning the globe. Two years ago, an international collective of scientists joined forces to take pictures of two black holes located at the centers of galaxies: one in the Milky Way, known as Sagittarius A*, and one in a nearby galaxy called M87, known as M87. Scientists linked eight radio telescope observatories in Chile, Mexico, Antarctica, Spain, Arizona and Hawaii and combined their images taken over the course of a week in April 2017. Linking radio dishes across the Earth created a virtual planet-sized telescope with a magnifying power capable of imaging black hole event horizons.

“Rather than looking at the black hole itself—which does not permit light to escape—researchers looked at gas surrounding it in the event horizon. The gas in this area heats up to billions of degrees, creating a silhouette which can be measured,” said Dr. Jorge Dias, Professor of Computer Imaging at Khalifa University. “Just taking pictures of the black hole from various points around the Earth isn’t enough, as the light waves rolling in from M87 were never collected at a single focal point. Instead, the data was received by each telescope and physically carried to a single location to be processed”.

Dr. Jorge Dias is part of the team at Khalifa University that works on Image and Signal Analysis. His work impacts the viability of a vast swath of future tech, from computer vision, to robotics, and machine learning. Unlike our own vision, which we primarily experience seamlessly and simultaneously to cognition, machines take in data through sensors and transmit numbers, which are interpreted through predefined algorithms. Machine learning is tightly related to sensory input and remains a focus for researchers.

“The Global mm-VLBI Array had to cancel out the background static created by taking images from across the world and sharpen them. As there are no direct connections between the radio dishes, the recordings at each site needed to be stable enough to be compared without ‘jitters’, with VLBI using atomic clocks to time-stamp the recorded data. To ensure recordings were made simultaneously, VLBI required synchronization at the level of a millionth of a second, achieved through using Global Positioning Service clocks at each geographical location,” explained Dr. Dias.

Once all the data was measured and aggregated, the picture still needed to be created. The light collected gives an indication of the structure of the black hole, but since there are only eight telescope locations, there still wasn’t enough data to reconstruct a picture. To make an image possible, imaging algorithms were developed to fill in the gaps.>

“Emerging computational methods push the boundaries of interdisciplinary imaging to fantastic results. The Continuous High-resolution Image Reconstruction using Patch priors (CHIRP) algorithm used machine learning to fill in the gaps, much like completing a jigsaw puzzle with missing pieces,” Dr. Dias.

Astronomers had so far only observed black holes by the behavior of the objects around them. The visible light, x-rays and radio waves emitted by stars can be seen by advanced telescopes to measure a black hole’s effect on its surroundings—meaning scientists had an idea of what a black hole would look like. Computer-powered observatories scan for and record bright points of light that are emitted as a black hole affects a nearby star; the CHIRP algorithm takes this data and identifies common patterns among black holes. It then learns these patterns and uses them to predict what would appear in the areas we can’t get data for using the EHT. And it’s not like we didn’t have a lot of data: in one night, the EHT generated enough data to fill half a ton of hard drives. Getting access to the data from the South Pole Telescope required waiting for the end of the Antarctic winter, so the hard copies could be shipped out.

The CHIRP algorithm is an example of the concept of neural networks. Their mechanism is closely related to how the human biological neural network functions—learning from examples. Neural networks have a set of inputs and one output, which they are taught to give based on some fixed input patterns. If a neuron encounters an input pattern it has not been taught, it outputs something as closely associated with its taught input pattern as possible.

Continuing the puzzle analogy, if you know the puzzle is supposed to show a face, you can assemble the outline and then use the computer algorithm to create a recognizable image. The problem? There are billions of different faces and it’s impossible to know which face would be the right one. We could have an infinite number of possibilities for the image of a black hole, so how do we know which is correct when we don’t know what it looks like in the first place?

To combat this, the Event Horizon Telescope Collaboration split into four separate teams to analyze the data independently and ensure no bias affected the resulting image. Different features were imposed on the input to the algorithms, and the output images were compared. If a lot of different features give the same kind of final image, the algorithm can be trusted. An elaborate series of tests was conducted to ensure the image was not the result of a technical glitch or fluke, especially since creating the image required filtering out the noise caused by atmospheric humidity warping radio waves and precisely synchronizing the signals captured by the telescopes, among other factors adding to the difficulty.

After months of the teams working independently, they reconvened in Cambridge, Massachusetts, and ran their algorithms in the same room, at the same time. The result? The now famous image of the supermassive black hole at the center of the M87 galaxy.

The image shows a bright ring formed as light bends in the intense gravity around a black hole that is 6.5 billion times more massive than the sun. The accretion disk—the ring of light—is on its side with regards to Earth, with the hole facing us and spinning clockwise. The image is brighter where gas flows around towards us. M87* is massive even by supermassive standards but located 54 million light-years away. Despite Sagittarius A* sitting a mere 26,000 light-years away, M87* was easier to image—and what we’re seeing in the black hole image.

Photo evidence of a black hole has been postulated for years, but finally accomplishing it is a stunning accomplishment of machine learning and Image and Signal Analysis. Modern physics starts with basic assumptions, builds verifiable theories, and then verifies them: that’s what’s happened here. A theory has to be given every possible new opportunity to fail, and the theory of General Relativity has withstood this one. This image represents the first steps into a profound new kind of astronomy and paves the way for an array of space telescopes throughout cislunar space (the volume inside the Moon’s orbit) as we seek ever sharper and clearer images of M87*, Sagittarius A* and the supermassive black holes to be found in the center of every nearby galaxy.

Jade Sterling
News and Features Writer
1 May 2019

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