Industrial IoT, IoT Security
Article | July 11, 2023
Artificial intelligence (AI) has already made headway into becoming a general-purpose technology vastly impacting economies. Yet, the interpretation and estimated trajectory for something remotely close to what we call AI now was first explored in the 1950s.
Until this very day, AI keeps on evolving further. Though let’s face it, AI would have been useless without data. With around 2.5 quintillion bytes of data being generated every day, the numbers will shoot up as the Internet of Things (IoT) enters the game.
Let’s see what this is all about and where and how exactly IoT crosses paths with AI applications.
IoT fundamentals: Where does IoT meet AI
The benefits of IoT in AI
Challenges of IoT in AI
Why implement machine learning in IoT
IoT applications for AI
Key takeaways
IoT fundamentals: Where does IoT meet AI?
What is meant by the term internet of things (IoT) is essentially a system of correlated digital and mechanical appliances, computing devices, and sensors embedded often into everyday objects that transfer data over a network. IoT connects the internet to any and every physical thing or place in the world.
Modern IoT has advanced from the mere merging of microelectromechanical systems to wireless technologies, and faster data transfer through the internet. This resulted in a confluence of information technology and artificial intelligence, allowing unstructured machine-generated data to be evaluated for insights that could lead to new developments.
More and more industries are now referring to IoT to function more proficiently, provide better customer service, escalate the significance of their business, and implement robust decision-making.
Machine learning for IoT can be used to identify anomalies, predict emerging trends, and expand intelligence through the consumption of audio, videos, and images. The implication of machine learning in IoT can substitute manual processes and offer automated systems using statistically backed up actions in critical processes.
The benefits of IoT in AI and real life
IoT offers the following benefits to AI applications:
IoT data for business purposes
Cost and time savings
Task automation and reduction of human intervention
Higher quality of life
IoT data for business purposes
IoT can also be viewed as a data pool. That means by aggregating IoT data, one can extract useful data-driven feedback, which in turn (used properly) may foster effective decision-making. Businesses can also identify new market opportunities, not because of IoT itself but by using the data IoT provides. And since IoT offers companies access to more data, and hence advanced analytics of that data, its usage can eventually result in improved customer outcomes and enhanced service delivery.
Cost and time savings
When devices get connected, cost reductions come along with it. The gathering of different data allows for advances in efficiency, and it leads to money surplus and low-cost materials.
Task automation and reduction of human intervention
Nowadays, devices that are internet-connected can be found in every aspect of our lives, and it is safe to say that they make tasks easier. These automation features range from real-time AI-powered chatbots to home automation control systems, and all of it usually takes a click of a button.
For businesses offering AI-enabled solutions, similar advancements can be achieved with pipeline automation too. That includes significant cuts in annotation and QA time. By leveraging SuperAnnotate’s platform, hundreds of companies recorded faster task completion and more accuracy in prediction results.
Higher quality of life
IoT is not only beneficial in the business aspects but it also creates better living circumstances for us. Smart cities and agriculture, intelligent homes, and food waste solutions are some of the most common ways of IoT providing better, more sustainable living conditions for people.
Challenges of IoT in AI
Despite the numerous benefits and advancements that IoT brings to the table, there have been a few limitations with it. Some of them are listed below:
Privacy issues
Data overflow
Bug issues
Compatibility issues
Privacy issues
With the increased connection between multiple devices or their coexistence for model development purposes, more information is shared between them, which poses vulnerability to your data and makes room for caution. Added layers of protection are needed to prevent risks of data leaks and other threats.
Data overflow
Eventually, organizations will have to find a way to deal with the large numbers of IoT devices, and that will include the collection and systematic management of all the data from those IoT devices. The proper use of data lakes and warehouses, close governance, and intuitive arrangement of datasets will become an utmost priority.
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Bug issues
If one IoT device has a bug in its system, there is a large chance that every other connected device will also have it.
Compatibility issues
Because there are no international standards of compatibility for IoT, it's harder for different devices to communicate with one another.
Why implement machine learning in IoT
More and more companies are combining IoT with machine learning projects so they can achieve analytical skills on a large variety of use cases which allows their businesses to have access to fresh insights and adopt innovative automation. By implementing machine learning for IoT, they can leverage the following:
Convert data into a coherent format
Arrange the machine learning model on device, edge, and cloud
Enable use of data on edge devices directly for complex decision making
IoT applications for AI
Although we have covered the basics of IoT, its implications for AI are not as simple. Many corporations are adopting IoT which allows them to have an advanced approach to growing and advancing their business. Novel IoT applications are offering organizations the ability to plan and implement more vigorous risk management strategies. Some of the more common uses of IoT in AI encompass the following:
Transport logistics
Not only does IoT expand the material flow systems in transport logistics, but it also improves the automatic identification and global positioning of freight. It also increases energy efficiency and consequently declines the consumption of energy.
Smart cities
Although the term smart city is still incomplete, it mainly refers to an urban area that endorses sustainable enlargement and high quality of life. Giffinger et al.’s model explains the features of a smart city, including the people, the government, the economy, and lifestyle.
E-health control
The two main objectives of future health care are e-health control and prevention. People nowadays can choose to be monitored by physicians even if they do not live in the same country or place. Tracing and monitoring peoples’ health history makes IoT-assisted e-health extremely useful. IoT healthcare solutions could also benefit the specialists, as they can collect information to advance their medical calculations.
Key takeaways
Ever since its development, IoT, especially AI-enabled IoT, as discussed, has been enhancing our daily lives and directing us to work smarter while having complete control over the process. Besides having smart appliances to elevate homes, IoT devices can also be essential for providing insights and an actual look for businesses into their systems. Heading forward, IoT will continue to develop as more organizations get to understand its potential usage and tangible benefits.
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Enterprise Iot
Article | May 11, 2023
As consumer demands evolve, fleet managers are turning to IoT to deliver products faster and more efficiently. The progress being made in edge computing represents the full potential of IoT: the power of data on the move. However, operating on the edge also reveals some of IoT’s greatest challenges: maintaining network security as the number of endpoints multiplies; rethinking traditional business models as industries become increasingly interdependent; and, perhaps most importantly, establishing a seamless, reliable network across borders, cultures, and regulatory environments.
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IoT Security
Article | July 17, 2023
Nothing is more innovative or sophisticated than the products being made by the wearables industry in the "smart" era. Individuals track, analyze, monitor, and transmit personal data using these tangible wearable gadgets. Moreover, the adaptable wearable technology is opening up new horizons with business-focused smartphone apps. However, it is still in its early stages, and according to recent developments in this field, the major players in wearable technology are concentrating on developing products with a focus on business applications.
These intelligent Internet of Things (IoT) devices are now widely employed in a variety of businesses and help detect biometric data such as heart rate and sleep habits, among others. In the coming ten years, wearable IoT technology or devices ought to become an integral part of every individual’s daily life.
Businesses around the world are incorporating the newest technologies into their functioning and are looking at digitally altering their impact in the market. With the majority of people already accustomed to using smartphones, they are now also getting familiar with utilizing wearable technology, such as smartwatches, jewelry, and fitness bands. Therefore, the demand for applications is increasing along with technology as we become more technologically adept.
Rising Wearable Industries
Health and Fitness Wearables
The health, fitness, and fashion industries are closely related to any wearable technology or device. People are now frequently using smartwatches to monitor their heart rate and the number of steps they take when walking or running, which has boosted the industries with this technology. IoT devices include medical sensors to track progress in terms of health. It is possible to determine how healthy a person's lifestyle is by gathering accurate health statistics from these devices. Additionally, it monitors sleeping patterns, enhancing your overall quest for wellness.
Gaming Wearables
Gaming is a significant new market for wearable technology and one which is booming. The most prevalent category of wearables in the market is virtual reality (VR) headsets. With VR devices like the Oculus Rift or Playstation VR, players are immediately immersed in otherworldly experiences. Several kinds of breathtaking experiences are now accessible to players everywhere, thanks to VR wearables.
Connected Cars
Automobiles are steadily gaining traction among IoT devices, but they are still a small market (just 0.05 percent of all connected devices are cars), and Ford and Tesla are vying for the top spot. Ford has dominated the connected car market, with Subaru being the only other manufacturer to see any appreciable growth in new connections since July 2020. In contrast, other producers are fighting for a sizable market share as the potential to grow this segment is highly exponential.
Conclusion
Today, wearable technology is planned, developed, distributed, and used in a variety of consumer and corporate markets. The ways in which these markets overlap and influence one another are constantly changing. IoT will significantly change how businesses engage with customers, streamline their operations, and contribute to the creation of a system that relies on such data.
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IoT Security
Article | July 5, 2023
Explore the IoT security solutions for critical issues and proactive solutions for the safe implementation of connected devices. Delve into cross-domain interactions for secure data storage.
Contents
1. Introduction
1.1 Significance of IoT Security for Safe Implementation
2. IoT Security Landscape
2.1 Emerging Threats in IoT Environments
2.2 Importance of Proactive Security Measures
3. Challenges Posed in IoT Systems
3.1 Cross-Domain Interactions
3.2 Denial of Service (DoS) Attacks
3.3 Insecure Interfaces and APIs
3.4 Vulnerable Third-Party Components
3.5 Safeguarding Data Storage and Retention
4. Solutions to Prevent Threats
4.1 Secure Integration and Communication
4.2 Traffic Monitoring and Analysis
4.3 Robust Authentication and Authorization Protocols
4.4 Patch Management and Vulnerability Monitoring
4.5 Access Control and User Authentication
5 Conclusion
1. Introduction
1.1 Significance of IoT Security for Safe Implementation
The significance of IoT connectivity and security for safe implementation is paramount in today's interconnected world. Some essential points highlight its importance at both the business and advanced levels. IoT devices collect and transmit vast amounts of sensitive data. Without proper security measures, this data can be intercepted, leading to breaches of privacy and potential misuse of personal or corporate information. Implementing robust IoT security ensures the protection of data throughout its lifecycle. Safeguarding Critical Infrastructure is crucial as Many IoT deployments are integrated into critical infrastructure systems such as power grids, transportation networks, and healthcare facilities. A breach in the security of these interconnected systems can have severe consequences, including disruption of services, financial losses, and even threats to public safety. IoT security helps mitigate these risks by preventing unauthorized access and potential attacks.
Mitigating financial losses, ensuring operational continuity and preventing IoT botnets and DDoS attacks contribute to security as IoT devices are often integrated into complex ecosystems, supporting various business operations. In recent years, compromised IoT devices have been used to create massive botnets for launching distributed denial-of-service (DDoS) attacks. These attacks can overwhelm networks and cause significant disruptions, affecting the targeted businesses and the internet infrastructure as a whole. Robust IoT security measures, such as strong authentication and regular device updates, can help prevent these attacks.
2. IoT Security Landscape
2.1 Emerging Threats in IoT Environments
Botnets and DDoS Attacks
Botnets, consisting of compromised IoT devices, can be leveraged to launch massive distributed denial-of-service (DDoS) attacks. These attacks overwhelm networks, rendering them inaccessible and causing disruptions to critical services.
Inadequate Authentication and Authorization
Weak or non-existent authentication and authorization mechanisms in IoT devices can allow unauthorized access to sensitive data or control of connected systems. This can lead to unauthorized manipulation, data breaches, and privacy violations.
Firmware and Software Vulnerabilities
IoT devices often rely on firmware and software components that may contain vulnerabilities. Attackers can exploit these weaknesses to gain unauthorized access, execute malicious code, or extract sensitive information.
Lack of Encryption and Data Integrity
Insufficient or absent encryption mechanisms in IoT communications can expose sensitive data to interception and tampering. Without data integrity safeguards, malicious actors can modify data transmitted between devices, compromising the integrity and reliability of the system.
Physical Attacks and Tampering
IoT devices deployed in public or accessible locations are vulnerable to physical attacks. These attacks include tampering, theft, or destruction of devices, which can disrupt services, compromise data, or manipulate the functioning of the IoT ecosystem.
Insider Threats
Insiders with authorized access to IoT systems, such as employees or contractors, may abuse their privileges or inadvertently introduce vulnerabilities. This can include unauthorized access to sensitive data, intentional manipulation of systems, or unintentional actions compromising security.
Supply Chain Risks
The complex and global nature of IoT device supply chains introduces potential risks. Malicious actors can exploit vulnerabilities in the manufacturing or distribution process, implanting backdoors or tampering with devices before they reach end-users.
2.2 Importance of Proactive Security Measures
Security measures are vital for ensuring the safety and reliability of IoT environments. Organizations can mitigate risks and stay ahead of potential vulnerabilities and threats by taking a proactive approach. These measures include conducting regular vulnerability assessments, implementing robust monitoring and detection systems, and practicing incident response preparedness. Proactive security measures also promote a 'Security by Design' approach, integrating security controls from the outset of IoT development. Compliance with regulations, safeguarding data privacy, and achieving long-term cost savings are additional benefits of proactive security. Being proactive enables organizations to minimize the impact of security incidents, protect sensitive data, and maintain their IoT systems' secure and reliable operation.
3. Challenges Posed in IoT Systems
3.1 Cross-Domain Interactions
Cross-domain interactions refer to the communication and interaction between IoT devices, systems, or networks that operate in different domains or environments. These interactions occur when IoT devices need to connect and exchange data with external systems, platforms, or networks beyond their immediate domain. Incompatibilities in protocols, communication standards, or authentication mechanisms can create vulnerabilities and potential entry points for attackers.
3.2 Denial of Service (DoS) Attacks
Denial of Service attacks are malicious activities aimed at disrupting or rendering a target system, network, or service unavailable to its intended users. In a DoS attack, the attacker overwhelms the targeted infrastructure with an excessive amount of traffic or resource requests, causing a significant degradation in performance or a complete service outage. Protecting IoT devices and networks from DoS attacks that aim to disrupt their normal operation by overwhelming them with excessive traffic or resource requests becomes challenging. The issue here lies in distinguishing legitimate traffic from malicious traffic, as attackers constantly evolve their techniques.
3.3 Insecure Interfaces and APIs
Insecure interfaces and application programming interfaces (APIs) refer to vulnerabilities or weaknesses in the interfaces and APIs used by IoT devices for communication and data exchange. An interface is a point of interaction between different components or systems, while an API allows applications to communicate with each other. Insecure interfaces and APIs can be exploited by attackers to gain unauthorized access to IoT devices or intercept sensitive data. Ensuring secure authentication and authorization mechanisms, proper encryption of data in transit, and secure storage of API keys and credentials, thus, becomes a challenge.
3.4 Vulnerable Third-Party Components
Vulnerable third-party components refer to software, libraries, frameworks, or modules developed and maintained by external parties and integrated into IoT devices or systems. These components may contain security vulnerabilities that attackers can exploit to gain unauthorized access, manipulate data, or compromise the overall security of the IoT ecosystem. Pain points arise from the challenge of assessing the security of third-party components, as organizations may have limited visibility into their development processes or dependencies.
3.5 Safeguarding Data Storage and Retention
Data storage and retention refers to the management and security of data collected and generated by IoT devices throughout its lifecycle. Safeguarding stored IoT data throughout its lifecycle, including secure storage, proper data retention policies, and protection against unauthorized access or data leakage, poses a threat. Ensuring secure storage infrastructure, protecting data at rest and in transit, and defining appropriate data retention policies include safeguarding data and maintaining the privacy of stored data. Failure to implementing strong encryption, access controls, and monitoring mechanisms to protect stored IoT data leads to this issue.
4. Solutions to Prevent Threatsc
4.1 Secure Integration and Communication
Implement secure communication protocols, such as transport layer security (TLS) or virtual private networks (VPNs), to ensure encrypted and authenticated communication between IoT devices and external systems. Regularly assess and monitor the security posture of third-party integrations and cloud services to identify and mitigate potential vulnerabilities. Organizations need to invest time and resources in thoroughly understanding and implementing secure integration practices to mitigate the risks associated with cross-domain interactions.
4.2 Traffic Monitoring and Analysis
Deploy network traffic monitoring and filtering mechanisms to detect and block suspicious traffic patterns. Implement rate limiting, traffic shaping, or access control measures to prevent excessive requests from overwhelming IoT devices. Utilize distributed denial of service (DDoS) mitigation services or hardware appliances to handle volumetric attacks. Organizations must deploy robust traffic analysis and anomaly detection mechanisms to identify and mitigate DoS attacks promptly. Additionally, scaling infrastructure and implementing load-balancing mechanisms become essential to handle sudden surges in traffic during an attack.
4.3 Robust Authentication and Authorization Protocols
Apply secure coding practices and implement strong authentication and authorization mechanisms for interfaces and APIs. Utilize secure communication protocols (e.g., HTTPS) and enforce strict access controls to prevent unauthorized access. Regularly update and patch interfaces and APIs to address any known vulnerabilities. Organizations must conduct regular security audits of their interfaces and APIs, implement strong access controls, and regularly update and patch vulnerabilities to address these effectively.
4.4 Patch Management and Vulnerability Monitoring
Conduct thorough security assessments of third-party components before integration, verifying their security track record and ensuring they are regularly updated with security patches. Establish a process for monitoring and addressing vulnerabilities in third-party components, including timely patching or replacement. Establishing strict vendor evaluation criteria, conducting regular security assessments, and maintaining an up-to-date inventory of third-party components can help address these issues and mitigate the risks associated with vulnerable components.
4.5 Access Control and User Authentication
Encrypt stored IoT data to protect it from unauthorized access or leakage. Implement access controls and user authentication mechanisms to restrict data access based on role or privilege. Establish data retention policies that comply with relevant regulations and securely dispose of data when no longer needed. Clear data retention policies should be established, specifying how long data should be stored and when it should be securely deleted or anonymized to minimize data leakage risks.
It's important to note that these solutions should be tailored to specific organizational requirements and constantly evaluated and updated as new threats and vulnerabilities emerge in the IoT security landscape.
5. Conclusion
Ensuring the safe implementation of IoT requires overcoming various security challenges through proactive measures and a comprehensive approach. By implementing proactive security measures, organizations can mitigate risks and maintain the safety and reliability of IoT environments. Overcoming these challenges requires organizations to invest in certain integration practices, traffic analysis, authentication mechanisms, encryption protocols, and vendor evaluation criteria. Overcoming IoT security challenges for safe implementation necessitates a proactive and comprehensive approach encompassing vulnerability management, monitoring and detection, incident response preparedness, secure design practices, compliance with regulations, and robust data storage and retention mechanisms.
The emergence in IoT security encompasses the incorporation of machine learning and AI for improved threat detection, the application of blockchain for secure transactions and device authentication, the integration of security measures at the edge through edge computing, the establishment of standardized protocols and regulatory frameworks, the adoption of advanced authentication methods, and the automation of security processes for efficient IoT security management. These trends aim to address evolving risks, safeguard data integrity and privacy, and enable IoT systems' safe and secure implementation.
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