Kaspersky Lab experts have found that a variety of seemingly safe products that are connected to the Internet can pose serious security vulnerabilities to a home owner.
Taking a random selection of the latest Internet-of-Things (IoT) products, Kaspersky Lab researchers have discovered serious threats to the connected home. These include a coffeemaker that exposes the homeowner’s Wi-Fi password, a baby video monitor that can be controlled by a malicious third-party, and a smartphone-controlled home security system that can be fooled with a magnet.
In 2014, Kaspersky Lab’s security expert David Jacoby looked around his living-room, and decided to investigate how susceptible the devices he owned were to a cyber-attack. He discovered that almost all of them were vulnerable. Following this, in 2015 a team of Kaspersky Lab antimalware experts repeated the experiment with one little difference: while David’s research was concentrated mostly on network-attached servers, routers and Smart TVs, this latest research was focused on the various connected devices available on the smart home market.
The devices selected for the experiment were as follows: a USB-dongle for video streaming, a smartphone-controlled IP camera, a smartphone-controlled coffee maker, and a smartphone-controlled home security system. The investigation discovered that almost all of these devices contained vulnerabilities.
A baby-monitor camera in the experiment allowed a hacker, whilst using the same network as the camera owner, to connect to the camera, watch the video from it and launch audio on the camera itself. Other cameras from the same vendor allowed hackers to collect owner passwords and the experiment showed it was also possible for a hacker on the same network to retrieve the root password from the camera and maliciously modify the camera’s firmware.
When it comes to app-controlled coffeemakers, it’s not even necessary for an attacker to be on the same network as the victim. The coffeemaker examined during the experiment was sending enough unencrypted information for an attacker to discover the password for the coffeemaker owner’s entire Wi-Fi network.
When looking at a smartphone-controlled home security system, Kaspersky Lab researchers found that the system’s software had just minor issues and was secure enough to resist a cyberattack. Instead, the vulnerability was found in one of the sensors used by the system.
The contact sensor, which is designed to set off the alarm when a door or a window is opened, works by detecting a magnetic field emitted by a magnet mounted on the door or window. When the door or window is opened the magnetic field disappears, causing the sensor to send alarm messages to the system. However, if the magnetic field remains in place, no alarm will be sent.
During the home security system experiment, Kaspersky Lab experts were able to use a simple magnet to replace the magnetic field of the magnet on the window. This meant they could open and close a window without setting off the alarm. The big problem with this vulnerability is that it is impossible to fix it with a software update; the issue is in the design of the home security system itself. What’s more concerning is that magnetic field sensor-based devices are a common type of sensors, used by a multiple home security systems on the market.
“Our experiment, reassuringly, has shown that vendors are considering cyber-security as they develop their IoT devices. Nevertheless, any connected, app-controlled device, is almost certain to have at least one security issue. Criminals might exploit several of these issues at once, which is why it is so important for vendors to fix all issues – even those that are not critical. These vulnerabilities should be fixed before the product even hits the market, as it can be much harder to fix a problem when a device has already been sold to thousands of homeowners”, said Victor Alyushin, Security Researcher at Kaspersky Lab.
In order to help users protect their lives and loved ones from the risks of vulnerable smart home IoT devices, Kaspersky Lab experts advise them to follow several simple rules:
1. Before buying any IoT device, search the Internet for news of any vulnerabilities within that device. The IoT is a very hot topic and a lot of researchers are doing a great job of finding security issues in products of this kind: from baby monitors to app controlled rifles. It is very possible that the device you are going to purchase has been already examined by security researchers and it is possible to find out whether the issues found in the device have been patched.
2. It is not always a great idea to buy the most recent products released on the market. Along with the standard bugs you get in new products, recently-launched devices might contain security issues that haven’t yet been discovered by security researchers. The best advice here is buy products that have already experienced several software updates.
3. When choosing what part of your life you’re going to make a little bit smarter, consider the security risks. If your home is the place where you store many items of material value, it is probably a good idea to choose a professional alarm system, that can replace or complement your existing app-controlled home alarm system; or set-up the existing system in such a way that any potential vulnerabilities would not affect its operation. When choosing a device that will collect information about your personal life and the lives of your family, like a baby monitor, it may be wise to choose the simplest RF-model on the market, one that is only capable of transmitting an audio signal, without Internet connectivity. If that is not an option, than follow our first advice – choose wisely.
Now IBM’s Watson joins IoT revolution in agriculture
Global expansion of the Watson Decision Platform taps into AI, weather and IoT data to boost production
IBM has announced the global expansion of Watson Decision Platform for Agriculture, with AI technology tailored for new crops and specific regions to help feed a growing population. For the first time, IBM is providing a global agriculture solution that combines predictive technology with data from The Weather Company, an IBM Business, and IoT data to help give farmers around the world greater insights about planning, ploughing, planting, spraying and harvesting.
By 2050, the world will need to feed two billion more people without an increase in arable land . IBM is combining power weather data – including historical, current and forecast data and weather prediction models from The Weather Company – with crop models to help improve yield forecast accuracy, generate value, and increase both farm production and profitability.
Roric Paulman, owner/operator of Paulman Farms in Southwest Nebraska, said: “As a farmer, the wild card is always weather. IBM overlays weather details with my own data and historical information to help me apply, verify, and make decisions. For example, our farm is in a highly restricted water basin, so the ability to better anticipate rain not only saves me money but also helps me save precious natural resources.”
New crop models include corn, wheat, soy, cotton, sorghum, barley, sugar cane and potato, with more coming soon. These models will now be available in the Africa, U.S. Canada, Mexico, and Brazil, as well as new markets across Europe and Australia.
Kristen Lauria, general manager of Watson Media and Weather Solutions at IBM, said: “These days farmers don’t just farm food, they also cultivate data – from drones flying over fields to smart irrigation systems, and IoT sensors affixed to combines, seeders, sprayers and other equipment. Most of the time, this data is left on the vine — never analysed or used to derive insights. Watson Decision Platform for Agriculture aims to change that by offering tools and solutions to help growers make more informed decisions about their crops.”
The average farm generates an estimated 500,000 data points per day, which will grow to 4 million data points by 2036 . Applying AI and analysis to aggregated field, machine and environmental data can help improve shared insights between growers and enterprises across the agriculture ecosystem. With a better view of the fields, growers can see what’s working on certain farms and share best practices with other farmers. The platform assesses data in an electronic field record to identify and communicate crop management patterns and insights. Enterprise businesses such as food companies, grain processors, or produce distributors can then work with farmers to leverage those insights. It helps track crop yield as well as the environmental, weather and plant biologic conditions that go into a good or bad yield, such as irrigation management, pest and disease risk analysis and cohort analysis for comparing similar subsets of fields.
The result isn’t just more productive farmers. Watson Decision Platform for Agriculture could help a livestock company eliminate a certain mold or fungus from feed supply grains or help identify the best crop irrigation practices for farmers to use in drought-stricken areas like California. It could help deliver the perfect French fry for a fast food chain that needs longer – not fatter – potatoes from its network of growers. Or it could help a beer distributor produce a more affordable premium beer by growing higher quality barley that meets the standard required to become malting barley.
Watson Decision Platform for Agriculture is built on IBM PAIRS Geoscope from IBM Research, which quickly processes massive, complex geospatial and time-based datasets collected by satellites, drones, aerial flights, millions of IoT sensors and weather models. It crunches large, complex data and creates insights quickly and easily so farmers and food companies can focus on growing crops for global communities.
IBM and The Weather Company help the agriculture industry find value in weather insights. IBM Research collaborates with start up Hello Tractor to integrate The Weather Company data, remote sensing data (e.g., satellite), and IoT data from tractors. IBM also works with crop nutrition leader Yara to include hyperlocal weather forecasts in its digital platform for real-time recommendations, tailored to specific fields or crops. IBM acquired The Weather Company in 2016 and has since been helping clients better understand and mitigate the cost of weather on their businesses. The global expansion of Watson Decision Platform for Agriculture is the latest innovation in IBM’s efforts to make weather a more predictable business consideration. Also just announced, Weather Signals is a new AI-based tool that merges The Weather Company data with a company’s own operations data to reveal how minor fluctuations in weather affects business.
The combination of rich weather forecast data from The Weather Company and IBM’s AI and Cloud technologies is designed to provide a unique capability, which is being leveraged by agriculture, energy and utility companies, airlines, retailers and many others to make informed business decisions.
 The UN Department of Economic and Social Affairs, “World Population Prospects: The 2017 Revision”
 Business Insider Intelligence, 2016 report: https://www.businessinsider.com/internet-of-things-smart-agriculture-2016-10
What if Amazon used AI to take on factories?
By ANTONY BOURNE, IFS Global Industry Director for Manufacturing
Amazon recently announced record profits of $3.03bn, breaking its own record for the third consecutive time. However, Amazon appears to be at a crossroads as to where it heads next. Beyond pouring additional energy into Amazon Prime, many have wondered whether the company may decide to enter an entirely new sector such as manufacturing to drive future growth, after all, it seems a logical step for the company with its finger in so many pies.
At this point, it is unclear whether Amazon would truly ‘get its hands dirty’ by manufacturing its own products on a grand scale. But what if it did? It’s worth exploring this reality. What if Amazon did decide to move into manufacturing, a sector dominated by traditional firms and one that is yet to see an explosive tech rival enter? After all, many similarly positioned tech giants have stuck to providing data analytics services or consulting to these firms rather than genuinely engaging with and analysing manufacturing techniques directly.
If Amazon did factories
If Amazon decided to take a step into manufacturing, it is likely that they could use the Echo range as a template of what AI can achieve. In recent years,Amazon gained expertise on the way to designing its Echo home speaker range that features Alexa, an artificial intelligence and IoT-based digital assistant.Amazon could replicate a similar form with the deployment of AI and Industrial IoT (IIoT) to create an autonomously-run smart manufacturing plant. Such a plant could feature IIoT sensors to enable the machinery to be run remotely and self-aware; managing external inputs and outputs such as supply deliveries and the shipping of finished goods. Just-in-time logistics would remove the need for warehousing while other machines could be placed in charge of maintenance using AI and remote access. Through this, Amazon could radically reduce the need for human labour and interaction in manufacturing as the use of AI, IIoT and data analytics will leave only the human role for monitoring and strategic evaluation. Amazon has been using autonomous robots in their logistics and distribution centres since 2017. As demonstrated with the Echo range, this technology is available now, with the full capabilities of Blockchain and 5G soon to be realised and allowing an exponentially-increased amount of data to be received, processed and communicated.
Manufacturing with knowledge
Theorising what Amazon’s manufacturing debut would look like provides a stark learning opportunity for traditional manufacturers. After all, wheneverAmazon has entered the fray in other traditional industries such as retail and logistics, the sector has never remained the same again. The key takeaway for manufacturers is that now is the time to start leveraging the sort of technologies and approaches to data management that Amazon is already doing in its current operations. When thinking about how to implement AI and new technologies in existing environments, specific end-business goals and targets must be considered, or else the end result will fail to live up to the most optimistic of expectations. As with any target and goal, the more targeted your objectives, the more competitive and transformative your results. Once specific targets and deliverables have been considered, the resources and methods of implementation must also be considered. As Amazon did with early automation of their distribution and logistics centres, manufacturers need to implement change gradually and be focused on achieving small and incremental results that will generate wider momentum and the appetite to lead more expansive changes.
In implementing newer technologies, manufacturers need to bear in mind two fundamental aspects of implementation: software and hardware solutions. Enterprise Resource Planning (ERP) software, which is increasingly bolstered by AI, will enable manufacturers to leverage the data from connected IoT devices, sensors, and automated systems from the factory floor and the wider business. ERP software will be the key to making strategic decisions and executing routine operational tasks more efficiently. This will allow manufacturers to keep on top of trends and deliver real-time forecasting and spot any potential problems before they impact the wider business.
As for the hardware, stock management drones and sensor-embedded hardware will be the eyes through which manufacturers view the impact emerging technologies bring to their operations. Unlike manual stock audits and counting, drones with AI capabilities can monitor stock intelligently around production so that operations are not disrupted or halted. Manufacturers will be able to see what is working, what is going wrong, and where there is potential for further improvement and change.
Knowledge for manufacturing
For many traditional manufacturers, they may see Amazon as a looming threat, and smart-factory technologies such as AI and Robotic Process Automation (RPA) as a far off utopia. However, 2019 presents a perfect opportunity for manufacturers themselves to really determine how the tech giants and emerging technologies will affect the industry. Technologies such as AI and IoT are available today; and the full benefits of these technologies will only deepen as they are implemented alongside the maturing of other emerging technologies such as 5G and Blockchain in the next 3-5 years. Manufacturers need to analyse the needs which these technologies can address and produce a proper plan on how to gradually implement these technologies to address specific targets and deliverables. AI-based software and hardware solutions will fundamentally revolutionise manufacturing, yet for 2019, manufacturers just have to be willing to make the first steps in modernisation.