Blockchains are often advertised as the perfect complement to the Internet of Things (IoT) system, but to understand why these two seemingly unrelated technologies are combined, so many people will be optimistic, we need to first look at The major challenges facing the IoT industry today are focused on several levels: technical challenges, business challenges and social challenges.
What is the "Internet of Things"?
The Internet of Things (IoT) simply refers to a system in which individual devices are connected to each other and can interact. The connection method is usually implemented through the Internet. We can compare the well-known Internet to "Internet of People", and the network of machines and devices is the "Internet of Things."
However, it should be noted that when we refer to the Internet of Things, it usually refers to the entire Internet of Things "system" rather than a single device. And then all our discussions are based on this consensus, which means that we are talking about the entire IoT system.
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Today's IoT systems are increasingly present in or access a large number of devices, and there may be potential mutual impedance between these connected devices, and these devices often require infrastructure in different structures and Run in design standards. To make matters worse, the deployment of IoT devices is getting faster and faster , making this technical problem that has not been completely solved so far more and more closely related to our daily life. Let us now look at some of the major technical challenges facing the IoT system.
From the Internet perspective, the vast majority of IoT devices in the world today are part of a hub-and-spoke topology or a server-client architecture. Each networked device can be thought of as a terminal that needs to communicate with the central server on a regular basis to upload data, communicate with other devices, and receive commands. In most networks, even if two IoT device terminals are only a few meters apart, they cannot directly interact with each other and must rely on a central server to coordinate communication. This central server, even though it is composed of several distributed computers, is still a centralized management mode and is likely to become a component of Single Point of Failure (SPoF). This means that if you want to attack (or disable it, or directly control) a large network of IoT devices, you only need to attack or control that central server. That is to say, by controlling this central server, it controls all operations of the devices in the entire network, from sending and receiving commands to uploading data. This is not only an obvious and serious security risk, but also brings huge management pressure to the operators of the Centralized Internet of Things.
In addition to the single point of failure, the centrally managed IoT network also binds the project's upfront investment, ongoing management costs, data storage and computing power to the management and maintenance of a single entity (central server). With the popularity of the Internet of Things, the interconnection and scale expansion of devices (imagined from hundreds of millions to trillions of devices), this centralized management model will become vulnerable in an instant. For equipment maintenance, the problem is even more serious. With the development of technology, in order to ensure the longest service life of the devices of the IoT system deployed in the field, the centralized network management system needs to continuously update the outdated hardware and software in a timely manner. This update Stress, it goes without saying.
For Internet of Things terminals (usually sensors), most IoT devices still rely on passwords in plain text format. Worse, when establishing identity and permissions for devices on the network, manufacturers often choose a default password or reuse a common password . As a result, the device is vulnerable to attacks by malware (such as Mirai) . Such a bad safety habit in practice is not only due to the general lack of security awareness and common sense, but also to the complexity of managing such a large and loosely centralized group of devices. This way of password setting further limits the security of communication between devices, because due to the lack of data decryption, once the centralized server is crossed, there is no way to verify device identity, information source, and scalability.
Data collected and sent from most IoT devices is now not traceable at all without identity-encrypted identity, signature, and identity-based encryption; data is not getting a completely independent and trusted In the case of guarantees by the three parties, people cannot trust these data at all. In this case, inter-device communication and transaction friction will increase dramatically. This brings a new security risk: those data that are not encrypted or not encrypted will be intercepted and even tampered with during transmission. As a result, other entities (such as others, companies, devices) will further reduce the trust in the data generated by these devices, and may also damage the reputation of the Internet of Things owners.
If the Internet of Things is seen as an integral part, then the IoT network is inevitably an extremely long value chain that actually contains many different components and participants. We follow the data flow, the terminal – there is a sensor to collect data; then to the gateway – responsible for managing sensors, integrating and uploading data; then the storage system (such as the cloud) – storing and providing data; finally the analysis engine – those Ability to process data and generate actionable instructions. In each step, or between these steps, all the software and hardware involved must adopt a unified set of communication standards.
However, for these standards, many IoT practitioners are self-contained, which leads to the entire IoT industry becoming an isolated island. The completely different IoT systems cannot technically communicate, let alone trade. Addressing the difficulties of communication between these silos and heterogeneous networks is one of the biggest technical challenges in today's Internet of Things, and this hinders the process of huge network effects in the Internet of Things.
Although many people are optimistic about the future of the Internet of Things , when investing in real money and IoT-related systems, most companies are still looking ahead and hesitating. In addition to numerous technical challenges, there are serious business challenges, such as business cases that are generally unclear (or completely lacking), data sensitivity, and potential strategic risks in shared data.
Investment returns inevitably drive business decisions, and investments in the Internet of Things are no exception. One of the biggest challenges facing the Internet of Things is the lack of viable business cases , whether through revenue generation or cost cutting, to justify investment. For now, it is difficult to figure out how to analyze and output value from data collected by IoT devices, which is the root cause of business cases that are not easy to find.
On the other hand, if you want to fully capture the value of all the data collected on the device, the required expertise and analysis thresholds are often high, and experts who can effectively analyze and propose rationalized actions for this data must be lacking. At this time, due to the lack of corresponding analytical capabilities within the enterprise, companies must seek external help. This in turn introduces another concern: concerns about data sensitivity . So companies will be more cautious when choosing partners and suppliers for data analysis. This cautious approach to cooperation undoubtedly severely limits the ability of companies to obtain the most appropriate talents to analyze and create value for their data; and to greatly reduce the likelihood that they will find valuable business cases. Let's think about the deeper aspects. In fact, many insights that have breakthrough value creation often come from the vertical data integration between multiple companies or industries, and each company strictly guards against their own data, making it possible to discover these precious insights. It has become more difficult.
Even if companies are willing to share data with specific vendors, there may still be potential strategic risks , and once they occur, they are often fatal. That is to say, suppliers (usually technology platforms) can capture the possibility of corporate customers through the ingenious integration and analysis of enterprise data. Data is also a strategic resource as more people see data as a key driver of performance, business efficiency and profitability. Large technology platforms (such as Google, Amazon, and Facebook) have a long-term sustainable competitive advantage through effective data aggregation and analysis, and in fact form a monopoly position. These platforms not only dominate the technology market in which they are born, but with their patented technology and large-scale data collection and analysis, they have proven that they have been able to profoundly influence a wide range of industries (such as Google and the automotive industry, Apple). With the game industry, Amazon and cloud services). Therefore, by pooling and effectively analyzing data, “suppliers” can betray “customers” and invade their markets.
With the rapid spread of digital technology, there are more and more people in the public who are aware of the ubiquity of data acquisition sensors, and are beginning to worry about the use of these data collection. The recent scandals of inappropriate use of user data by Facebook  and Google  have raised concerns among the global public and regulators. The EU's General Data Protection Regulations (GDPR) came into effect in May 2018, further pushing privacy and data ownership to the center of public opinion. However, these new regulations are still very limited in scope, as they almost all require users to agree to the supervision when they visit the website, and these websites only recognize the problem and not solve the problem fundamentally. If it's an IoT device, these problems are even more tricky, because they are intensively embedded in our living environment without our knowledge. Everything can't escape their monitoring, from your coordinates to the path of action. From voice to video. Many third-party agencies and individuals are also involved, and their actions and activities are more difficult to discern. In addition, different political jurisdictions have their own special regulatory requirements, which further complicate social issues. If the Internet of Things as a technology continues to be popular, it must address data privacy issues positively, and it needs to provide a socially acceptable solution, that is, to ensure that data is owned and used in a secure environment, or it will trigger innovation. Regulatory constraints.
In the next (link) article in this series, we will explore how blockchain technology can help solve these challenges and lead the M2M (Machine to Machine) economic era.
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 D. MacMillan and R. McMillan, “Google Exposed User Data, Feared Repercussions of Disclosing to Public,” Wall Street Journal, 8 October 2018. [Online]. Available: https://eugdpr.org/the-regulation /gdpr-faqs/. [Accessed 15 November 2018].