In late September, cybersecurity journalist Brian Krebs’ website was overwhelmed by a massive DDoS attack that hit at a rate of 620Gbps, forcing Akamai to temporarily suspend service. In a blog post describing the cyber assault, Krebs said the attack had likely been conducted with the help of a botnet that enslaved a significant number of compromised IoT devices, including routers, IP cameras and digital video recorders (DVRs).
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Security is “often overlooked” for the IoT
The Online Trust Alliance (OTA) has determined that the overwhelming majority of publicly reported Internet of Things (IoT) vulnerabilities publicly disclosed over the last year could have been easily avoided.
According Craig Spiezle, Executive Director and President of the Online Trust Alliance, security and privacy is often overlooked in the rush to bring connected devices to market.
“If businesses do not make a systemic change we risk seeing the weaponization of these devices and an erosion of consumer confidence impacting the IoT industry on a whole due to their security and privacy shortcomings,” he stated.
The most glaring IoT security failures analyzed by the OTA included the omission or lack of rigorous security testing throughout the development process; the lack of a discoverable process or capability to responsibly report observed vulnerabilities; insecure or no network pairing control options and a lack of testing for common code exploits and limited transport security and encrypted storage for user IDs and passwords. Last, but certainly not least, the OTA found that a number of IoT devices lacked a sustainable and supportable plan to address vulnerabilities through the product lifecycle, including a dearth of software and firmware update capabilities, along with insecure and untested security patches and updates.
“Security starts from product development through launch and beyond but during our observations we found that an alarming number of IoT devices failed to anticipate the need of ongoing product support,” said Spiezle. “Devices with inadequate security patching systems further opens the door to threats impacting the safety of consumers and businesses alike.”
As we’ve previously discussed on Rambus Press, the current security paradigm associated with the mobile and PC world is undeniably flawed. Indeed, serious or even critical vulnerabilities disclosed on an almost daily basis are patched with hurriedly coded software and firmware updates. While a ‘good enough’ approach may have been tolerated for smartphones and tablets, the industry cannot afford to relegate security to a tertiary concern for an IoT that may very well ultimately affect every aspect of our daily lives. A new paradigm, designed from the ground up to provide secure foundations for connected devices, is clearly long overdue. Devices should be secured throughout their lifecycle from chip manufacture, to day-to-day deployment, to decommissioning.
According to Steven Woo, VP of Systems and Solutions at Rambus, the semiconductor industry is slowly beginning to realize IoT security is a critical goal that needs to be treated as a first-class design parameter. Nevertheless, software is often selected as the security medium of choice because it is relatively simple to deploy and layer on top of existing systems.
“It’s certainly no secret that software-based security can be hacked. However, a silicon-based hardware root-of-trust offers a range of robust security options for IoT devices. Enabled by Moore’s Law, integration of a silicon root-of-trust into IoT silicon makes a lot of sense. As more and more devices are brought online, the importance of heightened security will only increase. Providing hardware-based security via a root-of-trust is going to be very important going forward,” he added.
Security is “often overlooked” for the IoT
The Online Trust Alliance (OTA) has determined that the overwhelming majority of publicly reported Internet of Things (IoT) vulnerabilities publicly disclosed over the last year could have been easily avoided.
Redesigning smart sensors for the IoT
Ed Sperling of Semiconductor Engineering observes that sensor technology is beginning to change on a fundamental level. Indeed, companies are now looking beyond the five senses – on which early sensors were modeled – to tailoring the versatile technology for specific applications.
Redesigning smart sensors for the IoT
Ed Sperling of Semiconductor Engineering observes that sensor technology is beginning to change on a fundamental level. Indeed, companies are now looking beyond the five senses – on which early sensors were modeled – to tailoring the versatile technology for specific applications.
“In some cases, sensors don’t have to be as accurate as the sight, smell, touch, taste and hearing of a person. In others, they can be augmented to far exceed human limitations,” he explains. “And while the human brain remains more efficient and effective at certain operations, such as adding context around sensory data, sensors connected to digital logic can react more quickly and predictably to known stimuli.”
Perhaps not surprisingly, the majority of early vision technology was conducted primarily for medical research purposes, with scientists working to cure blindness and compensate for impaired vision.
“[However], machine vision has a different purpose,” says Sperling. “Rather than striving for visual acuity that is as good or better than a person’s eyesight, current efforts add the ability to sense objects in the non-visible spectra, such as infrared imaging, or radar to detect objects around corners or other objects that are not visible to people.”
According to Steve Woo, VP of Enterprise Solutions Technology at Rambus, the proliferation of next-gen sensors means the growth rate of data will be enormous.
“[Nevertheless], this is [far] more data than can be moved back to the data center. It will require more edge computing, where there will be filters or pre-processing. So you basically can have simple processing to get to more meaningful data,” he says. “You may also start to see more machine learning in the end points, where you scan information and learn the important events about that data and send along consolidated information. There are ways you can do that with reasonable security back and forth over the air.”
As Woo previously told Rambus Press, the rapidly evolving Internet of Things (IoT) has prompted the semiconductor industry to place an emphasis on more efficiently capturing, securing, moving and analyzing an increasing volume of digital data.
“We share the industry’s vision of 50 billion connected devices by 2020, which will also include always-on, always-connected smart sensor endpoints tasked with capturing and delivering a wide range of data.”
Moore’s Law, says Woo, remains a critical factor in making this vision a reality, as the size of refractive imagers is currently limited by optics. Then again, as Sperling points out in the Semiconductor Engineering article referenced above, many applications don’t actually require extensive high resolution imaging capabilities provided by a standard lens-based configuration.
“How can we build even smaller imagers? By replacing the traditional camera lens with a diffraction grating, while leveraging advanced algorithms and chip processing capabilities,” Woo explains. “Now this is where Moore’s Law comes into play, because it continues to help enable the technology necessary for Rambus scientists to create and refine miniature, lensless smart sensors (LSS). While Moore’s Law has been a driving force in the computing industry for decades, we’re seeing a growing number of benefits in computation imaging and sensing applications such as LSS.”
According to Woo, Rambus’ low power sipping sensor technology is capable of performing a wide range of functions, including image change detection, point tracking, range finding, sophisticated gesture recognition, object recognition and image capturing.
“These versatile capabilities make LSS technology suitable for at least five key ‘smart’ verticals, including consumer, cities, transportation, manufacturing and medical,” he adds.
Interested in learning more about the technology behind Rambus lensless smart sensors? You can check out our LSS article archive here.
Optimizing edge nodes for the IoT
Jacob Harel of Zeidman Technologies recently noted that IoT developers are currently spending the majority of their resources finding ways to collect and analyze data.
“The twist, and pitfall, is that the amount of data moving through the system can swamp the system’s servers and hubs and overwhelm the databases,” he wrote in an Embedded Computing Design article.
“With the large number of new and sophisticated sensors available today that can easily connect to controllers and communicate through the network, eager engineers and product managers are happy to embrace the technology and take all the sensors they can get. The same goes for data—the bigger the better.”
As Harel notes, the attitude of “any [IoT] data is good data” may very well be one of the biggest issues product managers need to control.
“Finding ways to do more processing on the IoT edge device can reduce the amount of data sent,” he explained. “This can enable the use of smaller bandwidth, lower power communication, and overall lower power consumption for the system.”
It should be noted that McObject CEO Steve Graves recently expressed similar sentiments in a separate Embedded Computing Design article.
“A vast number of edge devices will need to store, retrieve and analyze some data right where they sit, before shipping anything ‘upstream’ to gateway or server-based data aggregation points that we usually think of in connection with Big Data,” Graves opined. “These data-crunching edge devices are more interesting ‘things’ that, in and of themselves, provide value to their users. These things ingest and produce a respectable amount of data that must be managed on the device, before it ever becomes part of Big Data (Cloud-based or otherwise).”
Meanwhile, Tom Kevan of Desktop Engineering says the IoT is already pushing measurement analytics to the edge of the network by essentially redefining the sensor’s place in the electromechanical ecosystem.
“No longer a discrete component working in isolation, the sensor interacts with computing and communications components to provide intelligence via two-way communications,” he explained. “[Companies] must adopt a systems engineering perspective, looking beyond individual components and viewing the sensor as part of a larger whole. Using this perspective, engineers must determine how the sensor fits and interacts with the other components in the node.”
In addition, emphasizes Kevan, design engineers must fit more and more functionality and components into smaller spaces. Perhaps not surprisingly, these design demands place a significant premium on miniaturization and packaging technologies.
“The power consumption design criterion for IoT sensor nodes has one rule: do more with less,” he continued. “This means that the node must be able to sense a physical property, perform analytics and transmit data to the Internet on a significantly reduced power budget, regardless of the power source technology.”
As we’ve previously discussed on Rambus Press, simple-function, sensor-laden endpoints can be expected to become ubiquitous as new layers of the IoT infrastructure go online. These environmentally aware, optimized ‘lite’ endpoints will capture, analyze and transfer data to various devices and the Cloud, but must do so with the right balance of power, performance, price and size.
One possible way of achieving this balance is to replace traditional lensed cameras with diffractive optics-based sensing, which is precisely why Rambus scientists pioneered Lensless Smart Sensor (LSS) technology for a new age of ubiquitous connectivity. To be sure, LSS is capable of reducing the cost and size of image-based sensing as compared to traditional cameras and other commonly-used sensing technologies.
More specifically, LSS technology offers an attractive mix of size, field of view, price and privacy – whether deployed as an occupant detection and counting sensor for smart home and commercial applications, or as an eye tracker in smart glass/augmented reality (AR)/virtual reality (VR) systems.
Interested in learning more about LSS? You can check out our official product page here and our article archive here.
