Enterprise Iot
Article | July 20, 2023
We live in the age of technological advancement and progress is happening at an unprecedented speed. With newer technologies emerging every day, it is unreasonable to not be intrigued by their implications on business. Artificial Intelligence and the Internet of Things are two independent technologies that are changing the face of several industries, one advancement at a time. While Artificial Intelligence promises to automate and simplify everyday tasks for humans, the Internet of Things is rapidly bridging the gap between physical and digital. The convergence of these two technologies promises to simplify lives through connected devices.
This convergence has already been witnessed in several industries and is being hailed as the Artificial Intelligence of Things or AIoT. Experts across industries claim that Artificial Intelligence of Things is set to redefine the future of the industry and mold intelligent and connected systems.
Applications
The Artificial Intelligence of Things is a congruence of AI and IoT infrastructures being used to achieve several applications across industries more accurately and efficiently. We already know that IoT generates scores of data, but this data is pretty useless in its raw form, it the organization, analysis, and interpretation of the data that makes it invaluable. Manually parsing through all of that data can take months given the sheer volume of it. This is where AI comes in. Modern AIs are programmed to efficiently handle large amounts of data to turn them into coherent pieces of information. Together, IoT and AI make for a great technological tool for business. Take a look at some other applications of AIoT in business.
Marketing
Good marketing comes from a series of well informed and well-researched decisions. For example, deciding on where the budget is allotted, what market strategy is put into action, or which campaign is prioritized. While human decisions can be fallible, most businesses today cannot afford to make big mistakes. This is where AIoT turns into a big help. Through the Artificial Internet of Things, marketers can get reports about market trends, probabilities, customer behavior, and more, most of these in real-time. These reports help marketers make informed decisions that are much likely to result in success.
Drones
Drones are one of the biggest advancements of IoT technology. In fact, drones are so popular with such varied applications, that drones can be talked of as a separate technology in themselves. These flying machines were originally invented for military purposes such as surveillance or weapon deployment but markets have rapidly found utility in drones for many other purposes. Today, they are being used as delivery bots, nature conservation, surveillance mechanisms, research tools, safety equipment, field substitutes, agriculture, geo-mapping, and a lot more.
With AIoT, drones have become smarter, more adaptable, and way more useful. As Artificial intelligence allows drones to make minor decisions, their applications have gotten wider and more sophisticated. In a brilliant use case of AIoT, a drone enthusiast named Peter Kohler has started the Plastic Tide Project which uses drones to locate plastic on the ocean surfaces. The drones are powered by AI which allows them to locate plastic and not other elements like marine life or corals. These drones then hover over the plastic waste and speed up the ocean cleaning process.
Drones can be used to map farmlands, determine the optimum farming processes and schedules, count the cattle, monitor their health, and even undergo certain physical tasks in agriculture, all thanks to the Artificial Intelligence of Things.
AR/VR
Augmented Reality and Virtual Reality are both heavily data-dependent technologies. There cannot be a convincing virtual reality unless there is data available for creating the said simulation. AR and VR have both found applications in several industries like healthcare, gaming, training, education, design, and manufacturing. Most of these applications fall in the critically important category and therefore, the AR or VR must be accurate to the minutest detail. This can only be achieved with mounds of data from the actual reality. With the help of IoT, this data is not accessible, and AI interprets it in a way that it can be turned into several different formats.
Infrastructure
One of the most useful applications of AIoT has been infrastructure. Artificial Intelligence of Things has fuelled innovation and planning for smart cities across the world. With the open data available for urban planning, cities are now becoming safer and more convenient to live in. AIoT has also made it possible to optimize energy consumption and ensure safer roadways through traffic surveillance. With smart energy grids, smart streetlights, and smart public transport, energy consumption and carbon emissions are both controlled.
Moreover, AIoT has given a whole new life to urban design, and now comfort and aesthetics do not have to be sacrificed for convenience.
Energy
As we discussed above, Artificial Intelligence of Things is instrumental in optimizing energy consumption in urban areas. However, the applications of AIoT in the energy sector are not limited to smart cities. Many utilities providers across the globe are already gearing up to incorporate AIoT in their process. The expected benefits from the Artificial Intelligence of Things range from improved grid management, power quality, reliability, and restoration resilience to enhanced cybersecurity and better integration of distributed energy.
Most utilities providers have still not adopted the new technology but with the increasing complexity of grid management and higher customer experience demands, there is no denying that they will have to deploy AIoT solutions to tackle these.
Robotics
In layman’s experience robots are either extremely sophisticated machines from sci-fi that undertake every task humans can and more, or they are these clunky things that can pass you the butter. In practice, however, robotics is a lot more practical than these ideas. Today, robotics is at the forefront of AIoT applications.
The Artificial Intelligence of Things is being used in robotics for several applications such as surgical procedures, manufacturing, and even first aid. In healthcare specifically, AIoT powered robots are taking huge leaps. Robotic surgery eliminates the chance of human error and offers a much more precise surgical experience with minimum invasion. This enhances the success rate of surgery and aids faster recovery in patients.
Logistics
The convergence of AI and IoT has made a huge impact on logistics as it is now possible to automate the entire process, track the goods, as well as monitor the entire trajectory from deployment to delivery. With the addition of drones and robotics, even the last mile delivery can be automated with zero human intervention. This makes for faster delivery, better customer experience, as well as a well-designed supply chain management system.
Industrial
As the concept of adding smart sensors to physical objects emerged in the 1980s, a new term was coined a decade later—Industrial Internet of Things. IIoT is now a huge phenomenon of automating and optimizing industrial operation technologies across the globe. As IIoT is deployed in several factions of the industry including manufacturing, supply chain management, human resources, and energy management, these devices and sensors generate a massive amount of data daily. The data generated from even a single process can be dizzying, and this is where AI makes a difference. AI can not only manage this data but also find the relevant points of data and analyze it for business purposes.
Edge Computing
Artificial Intelligence has given way for another technology i.e. Edge computing. Edge computing allows a device to process data itself rather than rely on remote data servers to do so. It may seem like a small feat but think of the possibilities it offers—drones don’t have to be connected to find their way, smart appliances can interact with each other without a shared network, and thermostats can change the temperature based on your past preferences automatically.
Edge computing is by no way a new technology but, in the future, it offers huge possibilities like smart automobiles and aircraft, or even robots in every home.
Frequently Asked Questions
What are the examples of Artificial Intelligence?
Some of the most common examples of Artificial Intelligence are Google Maps and Uber. The AI allows you to find routes to any destination and even hail rides there.
How does AI help IoT?
Artificial Intelligence can comb through millions of data points in seconds to come up with patterns and analyze them. As IoT generates a lot of data continuously, AI is a powerful and complementary technology that helps IoT.
Is IoT related to Artificial Intelligence?
Internet of Things and Artificial Intelligence are two separate technologies that interact with each other well as their functions aid each other progress. AI helps with the data generated by IoT, and IoT provides relevant data for AI to analyze.
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Industrial IoT, IoT Security
Article | July 11, 2023
The evolution of internet-based market models has changed the way businesses operate. Present-day businesses know that data visualization in business intelligence is integral to competitive success. Therefore, businesses are now expanding their data and intelligence retrieval capacities. As a result, IoT (Internet of Things) data visualization is gaining popularity among industrialists and researchers across various disciplines.
In corporate finance, IoT-based efficient data visualization analyses data from multiple sources with the help of corporate analytics management tools and manages data quality for business intelligence to reduce the risk of leaks.
Impact of IoT Data Visualization on Corporate Finance BI
Data is everywhere— right from a customer's first visit to your company’s website until he signs out, all the behavioral patterns and data are tracked. All this data becomes useless unless it is utilized for a particular purpose.
Analyzing this data to predict future trends is one of the significant benefits of smart data visualization tools and technologies. It helps to slice and dice the data gained from different sources of different complexity levels to the minute granular level. Business intelligence utilizes these insights and the existing database to run risk analysis.
It gives an overview of your financial performance and the risks and exposures it faces. And if you switch the KPIs at the center of any dashboard, your entire team can instantly access the most important and relevant data.
IoT data visualization can measure big data on customers more efficiently, allowing organizations to add value to their customers. Customized tools will analyze your customers’ data and produce reports according to specific customer needs to help you get a deeper insight. Corporations can also utilize this data to better understand their competitors’ benchmarks.
Customizable IoT Data to Store Millions of Data Points in One Place
IoT collects millions of data from various complex sources. The data visualization dashboard contains multiple widgets that convert this data into various forms, such as line graphs, geographical maps, bar charts, pie charts, gauges, heat maps, etc.
This information, transmitted into multiple visualizations, helps organizations to unlock every piece of data into a valuable asset.
The Benefits of Using IoT Data Visualization
Businesses can collect, analyze and monitor a variety of data using IoT, such as internet usage data, video surveillance data, mobile app usage, and social media. It helps businesses to design products and provide personalized value-added services to drive better consumer engagement. Here are some key benefits IoT data visualization offers:
Unlock multiple insights across various verticals
Addressing important financial concerns proactively
Combination of multiple data sources into a single insightful dashboard
Multi-layered visual data.
Combines new data with the existing data to analyze new business opportunities.
Better performance on IoT data flow.
Analyze multiple data correlations in real-time
Improved Collaboration
Well-coordinated and efficient performance.
Cost reduction
Accurate data interpretation
Mitigate risk factor
Better decision making
Conclusion
Hands down, IoT data visualization intelligence in a company’s business operations will lead to better decision-making. But, before you choose an IoT data visualization tool for your business, you should know what kind of data you need to analyze and if you need any additional historical data. Because IoT services offer data visualization tools and techniques to analyze and monitor the data accordingly to predict future trends. So, it’s important to identify the goals before selecting a tool for your organization.
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IoT Security
Article | July 17, 2023
Enhancing IoT security: Unveiling the significance of penetration testing in securing real-world IoT applications, identifying vulnerabilities, and mitigating risks for the protection of IoT data.
Contents
1. Introduction to IoT Application Security and Penetration Testing
1.1 Vulnerabilities of IoT application security
2. Fundamentals of IoT Penetration Testing
3. Considerations for IoT Penetration Testing
4. Methodologies and Approaches for IoT Penetration Testing
5. Takeaway
1. Introduction to IoT Application Security and Penetration Testing
Securing real-world IoT applications is paramount as the Internet of Things (IoT) permeates various aspects of any individuals lives. Penetration testing serves as a vital tool in identifying vulnerabilities and assessing the resilience of IoT systems against cyber threats. In this article, delve into the significance of penetration testing in securing IoT applications, exploring its role in identifying weaknesses, mitigating risks, and ensuring the integrity and confidentiality of IoT data.
1.1 Vulnerabilities of IoT application security
Expanded Attack Surface: The proliferation of IoT devices has dramatically expanded the attack surface, increasing the potential for security breach enterprise networks. With billions of interconnected devices, each presenting a potential vulnerability, the risk of unauthorized access, data breaches, and other security incidents is significantly heightened.
Risks: IoT devices often possess limited computational resources, making them susceptible to software and firmware vulnerabilities. Their resource-constrained nature can limit the implementation of robust security measures, leaving them exposed to potential attacks. Furthermore, a significant concern is the prevalence of default or weak credentials on these devices.
Diverse Threat Landscape: The threat landscape surrounding IoT devices is extensive and ever-evolving. It encompasses various attack vectors, including malware, botnets, DDoS attacks, physical tampering, and data privacy breaches. One notable example is the Mirai botnet, which compromised a vast number of IoT devices to launch large-scale DDoS attacks, leading to significant disruptions in internet services. In addition, IoT devices can serve as entry points for infiltrating larger networks and systems, allowing attackers to pivot and gain control over critical infrastructure.
Botnets: IoT devices can be infected with malware and become part of a botnet, which can be used for various malicious activities. Botnets are often utilized to launch distributed denial-of-service (DDoS) attacks, where a network of compromised devices overwhelms a target system with traffic, causing it to become inaccessible.
Ransomware: IoT devices are also vulnerable to ransomware attacks. Ransomware is malicious software that encrypts the data on a device and demands a ransom payment in exchange for the decryption key.
Data Breaches: IoT devices can be targeted to steal sensitive data, including personal identifiable information (PII) or financial data. Due to inadequate security measures, such as weak authentication or unencrypted data transmissions, attackers can exploit IoT devices as entry points to gain unauthorized access to networks and systems.
2. Fundamentals of IoT Penetration Testing
IoT penetration testing, also known as ethical hacking or security assessment, is a critical process for testing and identifying vulnerabilities and assessing the security posture of IoT devices, networks, and applications. It involves simulating real-world attacks to uncover weaknesses and provide insights for remediation.
IoT penetration testing involves identifying vulnerabilities, conducting targeted attacks, and evaluating the effectiveness of security controls in IoT systems. IoT pen-testing aims to proactively identify and address potential weaknesses that malicious actors could exploit. The methodology of IoT pen-testing typically follows a structured approach. It begins with attack surface mapping, which involves identifying all potential entry and exit points that an attacker could leverage within the IoT solution. This step is crucial for understanding the system's architecture and potential vulnerabilities. Pentesters spend considerable time gathering information, studying device documentation, analyzing communication protocols, and assessing the device's hardware and software components.
Once the attack surface is mapped, the following steps involve vulnerability identification and exploitation. This includes conducting security tests, exploiting vulnerabilities, and evaluating the system's resilience to attacks. The penetration testers simulate real-world attack scenarios to assess the device's ability to withstand threats. After exploitation, post-exploitation activities are performed to determine the extent of the compromise and evaluate the potential impact on the device and the overall IoT ecosystem. Finally, a detailed technical report summarizes the findings, vulnerabilities, and recommendations for improving the device's security.
3. Considerations for IoT Penetration Testing
Fuzzing and Protocol Reverse Engineering: Employ advanced techniques like fuzzing to identify vulnerabilities in communication protocols used by IoT devices. Fuzzing involves sending malformed or unexpected data to inputs and analyzing the system's response to uncover potential weaknesses.
Radio Frequency (RF) Analysis: Perform RF analysis to identify weaknesses in wireless communication between IoT devices. This includes analyzing RF signals, monitoring wireless communication protocols, and identifying potential vulnerabilities such as replay attacks or unauthorized signal interception.
Red Team Exercises: Conduct red team exercises to simulate real-world attack scenarios and evaluate the organization's detection and response capabilities. Red team exercises go beyond traditional penetration testing by emulating the actions and techniques of skilled attackers. This helps uncover any weaknesses in incident response, detection, and mitigation processes related to IoT security incidents.
Embedded System Analysis: Gain expertise in analyzing and reverse engineering embedded systems commonly found in IoT devices. This includes understanding microcontrollers, debugging interfaces, firmware extraction techniques, and analyzing the device's hardware architecture. Embedded system analysis helps identify low-level vulnerabilities and potential attack vectors.
Zero-Day Vulnerability Research: Engage in zero-day vulnerability research to identify previously unknown vulnerabilities in IoT devices and associated software. This requires advanced skills in vulnerability discovery, exploit development, and the ability to responsibly disclose vulnerabilities to vendors.
4. Methodologies and Approaches for IoT Penetration Testing
Mobile, Web and Cloud Application Testing
Mobile, web, and cloud application testing is integral to IoT penetration testing, focusing on assessing the security of applications that interact with IoT devices. This methodology involves various steps to evaluate the security of these applications across different platforms. For mobile applications, the methodology includes reviewing the binary code, conducting reverse engineering to understand the inner workings, and analyzing the file system structure. Sensitive information such as keys and certificates embedded within the mobile app are scrutinized for secure storage and handling. The assessment extends to examining the application's resistance to unauthorized modifications. In web applications, the testing covers common vulnerabilities like cross-site scripting (XSS), insecure direct object references (IDOR), and injection attacks. Application reversing techniques are employed to gain insights into the application's logic and potential vulnerabilities. Additionally, hardcoded API keys are identified and assessed for their security implications.
Firmware Penetration Testing
Firmware penetration testing is a crucial aspect of IoT security assessments, aiming to identify vulnerabilities within the firmware running on IoT devices. The methodology encompasses multiple steps to uncover weaknesses. The process begins with binary analysis, dissecting the firmware to understand its structure, functionality, and potential vulnerabilities. Reverse engineering techniques are applied to gain deeper insights into the firmware's inner workings, exposing potential weaknesses like hardcoded credentials or hidden functionality. The analysis extends to examining different file systems used in the firmware and evaluating their configurations and permissions. Sensitive keys, certificates, and cryptographic material embedded within the firmware are scrutinized for secure generation, storage, and utilization. Additionally, the resistance of the firmware to unauthorized modification is assessed, including integrity checks, secure boot mechanisms, and firmware update processes.
IoT Device Hardware Pentest
IoT device hardware penetration testing involves a systematic methodology to assess the security of IoT devices at the hardware level. This comprehensive approach aims to identify vulnerabilities and weaknesses that attackers could exploit. The methodology includes analyzing internal communication protocols like UART, I2C, and SPI to understand potential attack vectors. Open ports are examined to evaluate the security controls and risks associated with communication interfaces. The JTAG debugging interface is explored to gain low-level access and assess the device's resistance to unauthorized access. Extracting firmware from EEPROM or FLASH memory allows testers to analyze the code, configurations, and security controls. Physical tampering attempts are made to evaluate the effectiveness of the device's physical security measures.
5. Takeaway
Penetration testing is crucial in securing real-world IoT applications, enabling organizations to identify vulnerabilities and mitigate risks effectively. By conducting comprehensive and regular penetration tests, organizations can proactively identify and address security weaknesses, ensuring the integrity and confidentiality of IoT data. With the ever-growing threat landscape and increasing reliance on IoT technologies, penetration testing has become indispensable to safeguard IoT applications and protect against potential cyber-attacks.
Several key factors will shape the future of IoT penetration testing. First, the increasing complexity of IoT systems will require testing methodologies to adapt and assess intricate architectures, diverse protocols, and a wide range of devices. Second, there will be a greater emphasis on security by design, with penetration testing focusing on verifying secure coding practices, robust access controls, and secure communication protocols. Third, supply chain security will become crucial, necessitating penetration testing to assess the security measures implemented by vendors, third-party components, and firmware updates. Fourth, integrating IoT penetration testing with DevSecOps practices will ensure continuous monitoring and improvement of IoT system security. Lastly, as attackers become more sophisticated, future IoT penetration testing methodologies will need to keep pace with evolving IoT-specific attack techniques. By embracing these advancements, IoT penetration testing will play a vital role in ensuring the security and privacy of IoT deployments.
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Article | April 27, 2020
Manufacturing industry or the Industrial Internet of Things has been one of the driving verticals for development of 5G technologies. Wide 5G deployement for Industrial IoT has long been in the pipeline but we might expect it to be a reality very soon.
The true success of 5G depends on the verticals as trends suggest that that Industrial IoT alone will triple the number of needed base stations globally. And many verticals will need efficient wireless connectivity to become successful. 5G has features that are specifically designed to address the needs of vertical sectors, such as network slicing and URLLC. The ultra-reliable low latency communications and massive machine type communications required by the IIoT will soon be realized.
Table of Contents:
How Will 5G Impact Industrial IoT?
5G Accelerations for IIoT
Industrial 5G
How Will 5G Benefit Industrial IoT?
IoT is a B2B application and users just want to get actionable data from their sensors and not worry about whether it’s old data or unreliable data. I think 5G changes this dynamic significantly over the long term by standardizing and simplifying the experience and interactions, and possibly engaging more of the industry to help solve IoT’s problems but also improve the total experience.
- Anshel Sag, analyst at Moor Insights & Strategy
• Data-Transfer Speeds
Any IoT is said to be commercially successful depending on how fast it can set up communications with other IoT devices, software based websites or applications, phones, and tablets. 5G promises exactly all of this with significant increase in transfer speeds.
5G is 10x faster than its LTE counterparts and allows IoT devices to communicate and share data faster than ever. All IoT devices will benefit from the faster speed of 5G with reduced lag and improved sending and receiving of data and notifications between connected devices.
• Greater Network Reliability
5G networks also offer more reliable and stable connection which is extremely important for any IoT including devices like locks, security cameras and monitoring systems that depend on real-time updates.
With reliable connectivity consumers will be the greater beneficiary.
It is however, imperative for manufactures to trust and invest in 5G compatible devices to reap the benefits of high-speed connectivity, very low latency, and a greater coverage that will arrive with the next generation network.
READ MORE:How Will the Emergence of 5G Affect Federated Learning?
5G Accelerations for IIoT
• Diversity in Industrial IoT
The opportunities that industrial IoT bring with is varied and its used cases span the spectrum from indoor to outdoor, less demanding to mission-critical, data rate from dozens of bps to gbps, device motion from fixed to mobility, and power source from button battery to high voltage.
Predictive maintenance, smart metering, asset tracking, and fleet management are some of the commonly known opportunities for IIoT, which be extended further by 5G through continued diversity and expansion.
• 5G Inspires Untapped Frontiers
Industrial IoT application areas such as mobile robot control in production automation and autonomous vehicles in open pit mining require wide mobility, low latency and mission-critical reliability. They rely on wireless access at 50ms to 1ms latency and service reliability from 5 nines to 6 nines.
Though 4G/LTE has attempted to address these areas of IIoT application it has failed due to unsatisfactory performance. With ultra-reliable and low latency connection, 5G will take industrial IoT to unconquered spaces.
• Managing the Enterprise 5G Network
Typically, enterprise IT is responding to the business demand from Operational Technology (OT) and mandates security, integration, visibility, control, and compatibility. In this scenario, 5G is not about “what,” but about “how”. IT needs to consider the right approach to bring 5G to the enterprise and decide whether to co-manage with the service provider (SP) or self-manage. The experience of IT in managing Industrial Ethernet and Wi-Fi may not hold when it comes to 5G. IT will likely require OT’s partnership to address complexity, security, integration, and other new challenges that 5G presents.
Industrial 5G
The potential for industrial 5G huge as it enables whole new business models.
Industrial IoT has a core requirement of the ability to connect sensors, devices, software applications, production process, workers and consumers. The connectivity requires to be seamless vertical and horizontal integrations of all layers of automation pyramids that increases operational efficiency of the plant floor and the supply chain by optimal use of data, information and analytics. This can be improved by five key elements:
• Improved Connectivity
• Availability
• Low Latency
• Flexibility
• Speed
Industrial 5G will impact these areas of the manufacturing industry to guide the success of Industrial IoT.
Industrial 5G will play a key role in helping industrial users achieve the goals of Industrial IoT. 5G offers wireless communications services with reduced latency, increased connection density, and improved flexibility compared to the current 4G generation. 5G technology has a theoretical downlink peak speed of 20 Gbps (gigabits per second), which is about 20 times faster than the current generation.
The key is to start building IoT devices with broadly adopted operating systems, built-in security all the way down to the silicon, verifiable and updatable firmware, and mainstream application development tooling.
- Anshel Sag, analyst at Moor Insights & Strategy
The push and pull in achieving 5G success in IoT will be there until technology providers and end users work together to set up a consensus on standardization. The success will also depend on best-of-breed approach allowing the introduction of new technology over the lifecycle. Software and system integration will also be important attributes to a successful 5G deployment.
READ MORE:How Will IoT Revolutionize Pharmaceutical Manufacturing?
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