IoT Security
Article | July 5, 2023
Manufacturers were already digitizing their processes before March 2020. The COVID-19 pandemic gave IT and operational professionals in the manufacturing space reasons to want to move faster. Teams that can’t work on the factory floor (pandemic, weather, closed roads, etc.) need a way to monitor and control processes over the network. Supply chain woes—like wildly fluctuating demand and the container ship that blocked the Suez Canal—highlighted the need for agility. A skilled labor shortage has further accelerated plans for automation.
Digitization brings visibility and agility
The fourth industrial revolution, also known as Industry 4.0, lays the foundation of modern digital manufacturing. It brings together cyber and physical systems, automation, industrial IoT, and better vertical and horizontal integration.
The network has a starring role in digital manufacturing, connecting people and applications in any location to factory-floor assets like sensors, actuators, cameras, and industrial automation and control systems (IACS). Benefits of digitization include improved overall equipment effectiveness (OEE) uptime, product quality, worker safety, cybersecurity, 24/7 asset monitoring and faster new product introduction and accelerating plant buildouts.
Four essentials for manufacturing networks
As IT and operational professionals work to innovate traditional manufacturing facilities and operations, we must consider that digital manufacturing requires more networks. Here are guidelines for making sure your manufacturing network is up to the task.
Use network devices specifically designed for industrial environments like factories
In addition to high performance and reliability, industrial routers, switches, and firewalls need to withstand harsh environmental conditions like extreme temperatures, shock, vibration, and humidity. They also need to be able to control access, have support for real-time industrial protocols, and enable the flow of key operational data to move across applications in the cloud. Further, the operational networks they build need to be scalable and highly resilient. We designed our industrial routers and switches to meet these requirements.
Give IT and OT visibility and control into what they care about
The manufacturing network is a joint project of the IT and OT teams. If you’re on the IT team, you want a solution that works with your existing network management and security applications, and doesn’t require significant training or disruption. You want to automate network maintenance and quickly identify and solve performance issues, especially in this business-critical space. If you’re on the OT team, you’re probably not an IT expert. You want visibility of issues that impact availability, product quality, workforce effectiveness and straightforward recommendations to resolve them. Cisco DNA Center – proven in the largest IT networks – meets all these needs. It automates time-consuming manual tasks, continuously monitors network health, and provides reports and controls on an easy-to-use dashboard. Cisco Cyber Vision gives you visibility into assets and processes.
For agile manufacturing, look for “plug-and-play” deployment
Manufacturers are simultaneously expanding production, hyper-customizing products, improving operations, and launching new products and services. To achieve these goals, you need the agility to scale product capacity, change product mix, and reallocate resources as needed. Quickly shift networking and production resources where you need them using Cisco DNA Center’s plug-and-play onboarding and provisioning.
Pay careful attention to cybersecurity
Cybersecurity starts with knowing everything that is connected to your industrial network, who’s talking to each other and what they are saying. Cisco Cyber Vision automatically takes a complete inventory. OT teams use a graphical interface to create production zones (aka network segments) containing all assets that need to communicate. (The painting controller doesn’t need to talk to the assembly-line controller.) Cisco Identity Services Engine (ISE) deploys polices that block unintended communications between segments to keep malware infections from spreading. Cisco Cyber Vision also takes a baseline of each asset’s usual communications patterns, alerting OT and IT teams to unusual behavior that could be a sign of a security breach.
Prepare to do more with less
The manufacturing skills shortage has widened the skills gap, with fewer experts left on the plant floor to prevent mistakes and solve crises. Connecting your plant floor helps you do more with less. A resilient network with the four qualities I’ve described—rugged devices, IT and OT collaboration, simpler and agile network management, and cybersecurity—helps you proactively identify potential problems, discover the cause, and resolve them before they affect production or quality.
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IoT Security
Article | July 17, 2023
The nature of digital and physical security is evolving as a result of cloud-based IoT software, which enables both security components to be combined and used to exploit data better.
Commercial use of cloud-based IoT software is possible, and cloud-based solutions have some advantages in the area of security. IoT technology, which is essential to this development, is driving worldwide development in many areas and revolutionizing daily operations for many businesses.
Data is essential to success in almost every sector, and security is no exception. To better understand what's going on in your business, you can combine cloud-based solutions that contain all the information on a single interface. For instance, integrating security camera feeds with cloud-based access control systems enables real-time visual identification verification.
The Impact of Combining Physical and Cyber Security
Combining digital and physical security, often known as security convergence, helps optimize IoT and cloud-based security systems. A cloud-based physical security system needs cybersecurity software to guard against internet flaws and intrusions. Similarly, physical security measures prevent sensitive data from getting into the wrong hands. Teams for physical and cyber security might combine to provide a more comprehensive action plan. The more seamlessly all physical and digital security components are linked, the more secure and future-proof a commercial system will be.
When organizations use IoT technology, cybersecurity is a significant concern. However, by combining physical and digital security, organizations can make sure their cloud-based systems are well protected from vulnerabilities. In addition, the security and IT teams will also be better able to manage the evolving security landscape when the organization combines physical and digital security ideas.
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Enterprise Iot
Article | July 20, 2023
Explore the emerging complexities of IoT data governance with 7 key challenges to tackle. Address data privacy, security, and ethical concerns, empowering your business for success in 2023 and beyond.
Contents
1 The Case for Maintaining IoT Data Governance
2 Challenges of IoT Data Governance
2.1 Lack of Organizational Commitment
2.2 Data Privacy Concerns
2.3 Lack of Endpoint Security for IoT Devices
2.4 Issues with IoT Device Authentication
2.5 Increasing Volume of Unstructured Data
2.6 Unethical Use of IoT Data
2.7 Inadequate Data Governance Protocols
3 Addressing IoT Data Governance Challenges
3.1 Security by Design
3.2 Awareness Initiatives
3.3 Standardized Data Governance Policies
4 Conclusion
1 The Case for Maintaining IoT Data Governance
The growing use of IoT devices across various industries has caused a surge in data volume. Most of these devices store sensitive company data, which plays a crucial role in business operations but can have dire consequences if it falls into the wrong hands. Thus, companies need to understand what is IoT governance and its implementation to safeguard sensitive data from unauthorized access and malicious exploitation.
2 Top Challenges in IoT Data Governance for Businesses
2.1 Lack of Organizational Commitment
Organizational commitment is essential for effective IoT data governance. There needs to be a clear purpose and goals regarding data governance that are communicated to all stakeholders. Not focusing on organizational commitment can result in a lack of alignment between the organization's goals and the IoT data governance strategy, as well as uncertainty about ownership and accountability for data governance across the organization.
2.2 Data Privacy Concerns
Ensuring data privacy is a significant concern when implementing IoT data management to maintain IoT data governance security. With the vast amount of data generated by IoT devices, there is an increased risk of personal and sensitive data being compromised. Therefore, it is crucial to identify potential vulnerabilities, mitigate the risk of data privacy breaches in IoT environments, and anonymize user data for consumer devices.
2.3 Lack of Endpoint Security for IoT Devices
IoT devices are often designed with limited processing power and memory, and as such, many connected devices do not have built-in security features. This makes them attractive targets for hackers seeking to access confidential data or disrupt operations. Without proper endpoint security measures, IoT devices can be compromised, leading to data breaches, network downtime, and other security incidents that can compromise the entire system's integrity.
2.4 Issues with IoT Device Authentication
When IoT devices are designed without proper authentication mechanisms, it can be challenging to verify their identities. This results in possible unauthorized access, data breaches, and other security incidents. To supplement IoT data management practices, companies must implement secure authentication protocols specifically designed for IoT environments, such as device certificates, digital signatures, and multi-factor authentication, to maintain IoT data governance.
2.5 Increasing Volume of Unstructured Data
IoT devices generate vast amounts of data in various formats and structures, including text, images, audio, and video, which can be difficult to process, manage, and analyze. This data is often stored in different locations and formats, making it challenging to ensure quality and consistency. Moreover, this flood of unstructured data can contain sensitive information that must be protected to comply with regulations and standards. For effective IoT data governance, it is necessary to implement data classification, metadata management, and data quality management to make sense of unstructured data.
2.6 Unethical Use of IoT Data
IoT devices collect data that can be sensitive and personal, and misuse can lead to various negative consequences. Data from IoT devices can be used to develop insights, but it must be handled carefully to avoid privacy violations, discrimination, or other negative consequences. Ensuring data ethics requires organizations to consider the potential impacts of their data collection and use practices on various stakeholders. This involves addressing issues such as data privacy, data ownership, transparency, and bias in IoT data analytics.
2.7 Inadequate Data Governance Protocols
Without proper data governance protocols, IoT data may be inaccurate, incomplete, or difficult to access or analyze, reducing the effectiveness of IoT systems and limiting the potential benefits they can provide. Additionally, inadequate data governance protocols can lead to security and privacy vulnerabilities, potentially exposing sensitive data to unauthorized access or theft. This can result in legal and regulatory penalties, reputational damage, and a loss of customer trust.
3 Addressing IoT Data Governance Challenges
3.1 Security by Design
This approach involves integrating security and governance considerations into the design and development of IoT systems from the outset. This helps minimize vulnerabilities, prevent breaches that may compromise the confidentiality, integrity, and availability of IoT data, and help maintain IoT data governance. In addition, by prioritizing security in the design phase, organizations can implement security controls and features tailored to their IoT systems' specific needs, which can help prevent unauthorized access, manipulation, or theft of IoT data.
3.2 Awareness Initiatives
IoT data governance challenges can arise due to an improperly trained workforce that may not recognize the purpose and benefits of data governance practices. Awareness initiatives can help organizations develop a culture of security and privacy. These initiatives can educate employees and stakeholders about the risks and best practices associated with IoT data governance, including the importance of data security, privacy, and ethical considerations. By raising awareness of these issues, organizations can promote a culture of responsible data management, encourage stakeholders to adhere to data governance policies and procedures, and reduce the risk of human error or intentional misconduct that could compromise IoT data.
3.3 Standardized Data Governance Policies
Collaboration between local, regional, and federal governments and businesses is essential to establishing frameworks for implementing IoT and related technologies within their jurisdictions. Cooperation between governments and enterprises is crucial for implementing a standardized IoT data governance policy. This will protect end-users by mandating basic standards in procurement processes and creating regulations and guidelines that promote responsible data governance.
4 IoT Data Governance: Future Outlook
Data is one of the most valuable resources for organizations today, and addressing the problem of IoT data governance will ensure that the IoT of enterprises is used effectively and responsibly. Straits Research reported that the worldwide data governance market had a worth of USD 2.1 billion in 2021 and is projected to reach an estimated USD 11.68 billion by 2030. IoT devices are a key driving factor behind the growth of the data governance market, and as the amount of data generated and the number of devices grows, so will the complexity of data governance. By maintaining strong data governance policies and tracking changes in policies and best practices, businesses can ensure compliance and maintain trust in the long run.
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Article | April 15, 2020
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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