7 Big Problems with the Internet of Things

In a few short years, the Internet of Things (IoT) has gone from a technology — or set of technologies — that were cutting edge to the situation today where connected household items, or automobiles, are common. However, growth is only really gathering speed now with San Francisco-based Cisco estimating that the "Internet of Everything cisco article" — its take on the IoT — could have has many as 50 billion connected devices by 2020.

According to Helsinki, Finland-based F-Secure, a cybersecurity company citing research from Gartner, over the next two years, the number of IoT devices entering households will climb steeply from nine devices per household currently to 500 by 2022, with IoT connectivity being bundled into products whether people want it or not.

In fact according to Mikko Hypponen, chief research officer for F-Secure in research on the IoT published last month, in the future, devices without IoT capabilities may be more expensive because they'll lack data that can be harvested by manufacturers. It’s this very data that makes the IoT such an interesting proposition for enterprises. That data, though, comes with risks, along with a number of other notable risks and problems associated with the IoT that enterprises will have to overcome in the coming years.

Last month, the World Economic Forum published its Global Risks Report for 2018, the 13th year it has published it. Each year, researchers with the Global Risks Report work with experts and decision-makers across the world to identify and analyze the most pressing risks that the world face. As the pace of change accelerates, and as risk interconnections deepen, this year’s report highlights the growing strain we are placing on many of the global systems we rely upon. The IoT and the problems related to cyberattacks take a prominent position in the report.

If the IoT has a problem, or is exposed to weaknesses, then the enterprises that are connected to it are equally threatened. In fact, while security is undoubtedly one of the major issues impacting the development, there are a number of other problems that stem directly from this. Here are 7 major IoT problems for enterprises connecting to the IoT.

1. Walled Off Internet

According to the World Economic Forum, the growing number of cross border attacks will start pushing national governments towards breaking up the internet in national, or even regional “walled gardens.” There are other pressures too that will push them to do this, including economic protectionism, regulatory divergence and the loss of government power relative to global online companies.

This will create major problems for the concept — and practice of a global IoT — leading to the erection of barriers to the flow of content and transactions. “Some might welcome a move towards a less hyper-globalized online world, but many would not, resistance would be likely, as would the rapid growth of illegal workarounds. The pace of technological development would slow and its trajectory would change,” the report reads.

2. Cloud attacks

Given that a large amount of the data that will run the Io T will be stored in the cloud it is likely that cloud providers will be one of the principle targets in this kind of war. While there is growing awareness of this problem, cybersecurity is still under-resourced in comparison to the potential scale of the threat. To get some kind of idea of the problem, the World Economic Forum report cites analysis that suggests that the takedown of a single cloud provider could cause $50 billion to $120 billion of economic damage — a loss somewhere between Hurricane Sandy and Hurricane Katrina.

The annual economic cost of cybercrime is now estimated at north of $1 trillion, a multiple of 2017’s record-year aggregate cost of approximately $300 billion from natural disasters.

3. AI-Built Security Issues

Although the threat magnitude of ransomware has already grown 35x over the last year with ransomworms and other types of attacks, there is more to come. Rick Pither, who leads Austin, Texas-based SparkCognition’s Global Security website Sales and Embedded OEM business agrees that the problems for cloud vendors are only emerging.

He said that the next big target for ransomware is likely to be cloud service providers and other commercial services with a goal of creating revenue streams. The complex, hyperconnected networks cloud providers have ?developed can produce a single point of failure for hundreds of businesses, government entities, critical infrastructures, and healthcare organizations. If not in the next year, he said soon we will begin to see malware completely created by machines based on automated vulnerability detection and complex data analysis. Polymorphic malware is not new, but it is about to take on a new face by leveraging AI to create sophisticated new code that can learn to evade detection through machine written routines.

4. Botnet Problems

Millions of new connected consumer devices make a wide attack surface for hackers, who will continue to probe the connections between low-power, somewhat dumb devices and critical infrastructure, Shaun Cooley, VP and CTO at San Jose, California based Cisco website said. The biggest security challenge he sees is the creation of Distributed Destruction of Service (DDoS) attacks that employ swarms of poorly-protected consumer devices to attack public infrastructure through massively coordinated misuse of communication channels. 

IoT botnets can direct enormous swarms of connected sensors like thermostats or sprinkler controllers to cause damaging and unpredictable spikes in infrastructure use, leading to things like power surges, destructive water hammer attacks, or reduced availability of critical infrastructure on a city or state-wide level. Solutions for these attacks do exist, from smarter control software that can tell the difference between emergency and erroneous sensor data, and standards that put bounds on what data devices are allowed to send, or how often they're allowed to send it. But the challenge of securing consumer-grade sensors and devices remains, especially as they connect, in droves, to our shared infrastructure. 

5. Limited AI

AJ Abdallat is CEO of Beyond Limits website, an organization that was born from the labs of the Caltech deep space program. He points out that most of the current AI offerings on the market have substantial limits. After all, the machine learning and big data based AI that currently pervade are powerful tools for identifying associations in large quantities of data, but don’t have much on humans in terms of working out the complex phenomena of cause and effect, or to identify modifiable factors that can engender desired outcomes.

As big data and machine learning powered AI’s gains processing power, they can incorporate into their algorithms more and more information, more and more variables that may affect data associations. But with little human intervention, inevitably some variables may display strong correlation by pure chance, with little actual predictive effect. 

The practical applications of AI to the IoT include, Smart IoT that connects and optimizing devices, data and the IoT; AI-Enabled Cybersecurity that offers data security encryption and enhanced situational awareness to provide document, data, and network locking using smart distributed data secured by an AI key.

6. Lack of Confidence

Amsterdam, Netherlands-based Gemalto is a cybersecurity firm that has researched the impact of security on the development of the IoT. If found that that 90 percent of consumers lack confidence in the security of Internet of Things devices. This comes as more than two-thirds of consumers and almost 80% of organizations support governments getting involved in setting IoT security. In fact its recent State of IoT Security research report, released at the end of October showed the following data.

• 96 percent of businesses and 90 percent of consumers believe there should be IoT security regulations
• 54 percent of consumers own an average of four IoT devices, but only 14 percent believe that they are knowledgeable on IoT device security
• 65 percent of consumers are concerned about a hacker controlling their IoT device, while 60 percent are concerned about data being leaked

"It's clear that both consumers and businesses have serious concerns around IoT security and little confidence that IoT service providers and device manufacturers will be able to protect IoT devices and more importantly the integrity of the data created, stored and transmitted by these devices," said Jason Hart, CTO of Data Protection at Gemalto said in a statement about the report. "Until there is confidence in IoT amongst businesses and consumers, it won't see mainstream adoption,” said Hart.

7. Understanding IoT

In 2018, the real issue is how to increase the ability for people to understand the changes and their implications more clearly, and to take concrete actions to take advantage of the potential upside. "The pace of change has exceeded the rate of human capability to absorb — the cup is already full," said Jeff Kavanaugh, VP and Senior Partner in High Tech & Manufacturing for Infosys website.

Internet of Things is moving into it’s adolescence as connected devices become smarter and more immersive, and expectations to convert IoT data to insights and financial value increase. Also, algorithms and data visualization templates have evolved so that new use cases can take advantage of earlier ones. The exponential adoption of IoT will drive down sensor and acquisition costs, enabling more and more viable business cases that have previously been too expensive. 

By David Roe

Math Works Great—Until You Try to Map It Onto the World

RUSLAN KHASANOV

IN 1900, THE great mathematician David Hilbert presented a list of 23 unsolved problems worth investigating in the new century. The list became a road map for the field, guiding mathematicians through unexplored regions of the mathematical universe as they ticked off problems one by one. But one of the problems was not like the others. It required connecting the mathematical universe to the real one.

Hilbert’s sixth problem called upon researchers to axiomatize the laws of physics—that is, rigorously construct them from a basic set of starting assumptions, or axioms. Doing so would reveal contradictions between laws that demanded different axioms. And deriving the entire body of physical laws from the same axioms would prove they were not merely haphazard, incoherent descriptions of disparate phenomena, but instead formed a unified, mathematically airtight, internally consistent theory of reality. “Once again it was an issue of unification, which pervades physics to this day,” said Marshall Slemrod, a mathematician at the University of Wisconsin, Madison.

Axiomatizing all of physics was a tall order, so Hilbert proposed a specific task: Determine whether the microscopic and macroscopic pictures of a gas rest on equivalent axiomatic foundations, and are thus different manifestations of a single theory. Experts approached this problem by attempting to mathematically translate the Boltzmann equation, which describes a gas as microscopic particles bouncing around at a range of speeds, into the Navier-Stokes equations, which describe the gas on larger scales as a continuous, flowing entity. Could the particle and fluid pictures be rigorously linked?

While Hilbert’s broader aim of axiomatizing physics remains unfulfilled, recent research has yielded an unexpected answer to the particle-fluid question. The Boltzmann equation does not translate into the Navier-Stokes equations in all cases, because the Navier-Stokes equations—despite being exceptionally useful for modeling the weather, ocean currents, pipes, cars, airplane wings and other hydrodynamic systems, and despite the million-dollar prize offered for their exact solutions—are incomplete. The evidence suggests that truer equations of fluid dynamics can be found in a little-known, relatively unheralded theory developed by the Dutch mathematician and physicist Diederik Korteweg in the early 1900s. And yet, for some gases, even the Korteweg equations fall short, and there is no fluid picture at all.

“Navier-Stokes makes very good predictions for the air in the room,” said Slemrod, who presented the evidence last month in the journal Mathematical Modelling of Natural Phenomena. But at high altitudes, and in other near-vacuum situations, “the equations become less and less accurate.”

Remarkably, this surprising conclusion could have been reached long ago, before Hilbert ever posed the sixth problem. In 1879, another titan of science, the Scottish physicist James Clerk Maxwell, pointed out that the Navier-Stokes equations fail to explain a near-vacuum experiment called the Crookes radiometer—apparently unbeknownst to Hilbert. “It would have been nice if he read Maxwell,” Slemrod observed.

In the Crookes radiometer, invented in 1873 by Sir William Crookes, exposure to light creates a heat and pressure gradient inside the partial vacuum chamber, turning the vanes.  NEVIT DILEMEM | CC BY-SA 3.0

Many mathematicians worked hard on the particle-fluid question after 1900, including Hilbert himself. He began by rewriting the complicated Boltzmann equation as the sum of a series of decreasing terms. Theoretically, this chunky decomposition of the equation would be more easily recognizable as a different, but axiomatically equivalent, physical description of a gas—perhaps, a fluid description. The terms in the series quickly become unruly, however; energy, instead of diminishing at shorter and shorter distances in the gas, seems to amplify. This prevented Hilbert and others from summing up the series and interpreting it. Nonetheless, there was reason for optimism: The leading terms of the series looked like the Navier-Stokes equations when a gas becomes denser and more fluidlike. “So the physicists were happy, sort of,” said Ilya Karlin, a physicist at ETH Zurich in Switzerland. “It’s in all the textbooks.”

But did the Boltzmann equation, which the Austrian physicist Ludwig Boltzmann derived in 1872, actually converge to the Navier-Stokes equations, developed decades earlier by Claude-Louis Navier of France and George Stokes of Ireland and England, or to something else? The question remained open. In the early 1990s, Karlin, then a student working with Alexander Gorban in Krasnoyarsk, Siberia, took another crack at the series that had foiled Hilbert. The location proved helpful. “We always joked that … it’s the edge of the civilized world, so you sit there and think of great problems.”

Karlin and Gorban developed a simplified model of the Boltzmann equation that contained the essential difficulties of the original, and expanded the model equation in a series. Then, using a few mathematical tricks, they managed to sum it up exactly. The solution was not what they had expected. The problematic amplifying parts of the series were bundled together as an extra term in the solution. When, years later, Slemrod came across the Russian scientists’ work, he recognized the term’s significance. “Marshall noticed that the structure of the exact equations that come out of my solution is not Navier-Stokes,” Karlin said, “but something very much reminding us [of] the equations of Korteweg, for the two-phase fluid.”

Korteweg modeled the dynamics of fluids in which there is not only dissipation of energy (which is characterized by the Navier-Stokes equations), but also dispersion, or the smearing of energy into its component frequencies, as in a rainbow. Dissipation results from a fluid’s viscosity, or internal friction. But dispersion is caused by its capillarity—the surface tension effect that makes some liquids rise in straws. In most fluids, capillarity is negligible compared to viscosity. But it isn’t always. And mathematically, it never is. It was this capillarity, Slemrod argued in a 2012 paper, that appeared as the extra term in Karlin and Gorban’s solution to their Boltzmann-like equation. Although the finding has not yet been generalized to the full Boltzmann equation, it indicates that the particle description of a gas, when translated into a fluid description, converges not to the Navier-Stokes equations, but to the more general, far less famous Korteweg equations.

Click to Open Overlay Gallery

Alexander Gorban, a professor of applied mathematics at the University of Leicester in England (left), and his former student Ilya Karlin, a professor at ETH Zurich in Switzerland.  COURTESY OF ALEXANDER GORBAN AND ILYA KARLIN

Slemrod “gives very solid arguments that Korteweg hydrodynamics has a much wider area of applicability than Navier-Stokes,” said Gorban, who is now a professor of applied mathematics at the University of Leicester in England. Still, Gorban notes, his work with Karlin suggests that some gases of particles cannot even be captured by the Korteweg equations. When short-distance interactions between particles become strong enough, he said, such as at the edge of a shock wave, even capillarity cannot fully account for their behavior, and “there exist no hydrodynamics.”

The incompleteness of the Navier-Stokes equations becomes apparent in an old experiment that is often for sale in museum gift shops. The Crookes radiometer, a windmill housed inside a partial vacuum chamber made of glass, rotates when exposed to light. In 1879, Maxwell attempted to describe the turning vanes of the Crookes radiometer by modeling the thin air inside the vacuum chamber as a fluid. Maxwell determined that if the equations “given by Professor Stokes,” as he called them, told the full story of the fluid, the vanes would not turn. The turning of the vanes can, however, be modeled as a capillarity effect, and described by the Korteweg equations.

To “mathematicians who have never been in a laboratory in their life, I finally get their attention and say, ‘Look at this thing!” said Slemrod, referring to the Crookes radiometer. “There are real things happening here, and you can learn from them!’”

Slemrod hopes that employing the Korteweg equations rather than Navier-Stokes will be useful for modeling near-vacuum gases, like the thin air surrounding orbiting satellites. “My hope is that it might be possible to use this corrected version down near the vacuum instead of the Boltzmann equation, [which] is a nasty object to solve,” he said.

Leo Corry, a historian of mathematics at Tel Aviv University in Israel who has written a book about David Hilbert and his sixth problem, notes that Hilbert’s original aim seems to have gotten lost in the details of the particle-fluid question and remains unaddressed. “Notice that the words ‘axiom’ or even ‘foundation’ or ‘conceptual analysis’ do not appear even once in Slemrod’s review,” Corry said.

If anything, Hilbert’s goal of axiomatizing physics grew more daunting as the 20th century progressed. Even more challenging than the complicated relationship between particle and fluid dynamics is the seemingly irreconcilable conflict between quantum mechanics and general relativity— descriptions of nature at still smaller and larger scales.

But even if the particle-fluid question isn’t a perfect proxy for the sixth problem, it has taken on a life of its own. “I would not even dare to say that it is less important than what Hilbert had in mind when putting forward his sixth problem,” Corry said. “I would not argue with anyone saying that, indeed, it is much more important and impressive.”

Editor’s Note: Marshall Slemrod receives funding from the Simons Foundation as a 2012 Collaboration Grant awardee.

Original story reprinted with permission from Quanta Magazine, an editorially independent publication of theSimons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.