IoT Security
Article | July 17, 2023
Modern computing devices can be thought of as a collection of discrete microprocessors each with a dedicated function like high-speed networking, graphics, Disk I/O, AI, and everything in between. The emergence of the intelligent edge has accelerated the number of these cloud-connected devices that contain multiple specialized sub-processors each with its own firmware layer and often a custom operating system. Many vulnerability analysis and endpoint detection and response (EDR) tools find it challenging to monitor and protect devices at the firmware level, leading to an attractive security gap for attackers to exploit.
At the same time, we have also seen growth in the number of attacks against firmware where sensitive information like credentials and encryption keys are stored in memory. A recent survey commissioned by Microsoft of 1,000 security decision-makers found that 83 percent had experienced some level of firmware security incident, but only 29 percent are allocating resources to protect that critical layer. And according to March 2021 data from the National Vulnerability Database included in a presentation from the Department of Homeland Security’s Cybersecurity and Infrastructure Agency (CISA) at the 2021 RSA, difficult-to-patch firmware attacks are continuing to rise. Microsoft’s Azure Defender for IoT team (formerly CyberX) recently announced alongside the Department of Homeland Security a series of more than 25 critical severity vulnerabilities in IoT and OT devices
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IoT Security
Article | July 5, 2023
For businesses, the transformative power of IoT is increasingly significant with the promise of improving operational efficiency and visibility, while reducing costs.
However, IoT does not come without risks and challenges. While concerns over security and data privacy continue to rise, the lack of IoT standards remains one of the biggest hurdles. The increasing number of legacy, single-vendor, and proprietary solutions cause problems with disparate systems, data silos and security gaps. As IoT successes become more dependent on seamless interoperability and data-sharing among different systems, we want to avoid the scenario of a fragmented market with numerous solutions that simply don’t work with each other.
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IoT Security
Article | June 27, 2023
The Internet of Things (IoT) and Industrial Internet of Things (IIoT) markets have experienced explosive growth as a result of the digital industrial revolution that followed the COVID-19 epidemic. To fully benefit, however, organizations have had to handle security concerns associated with these revolutionary technologies. Therefore, finding the correct security strategy is crucial for any organization because of the increasing dependency on IoT and IIoT to manage essential business systems.
IoT and IIoT can be implemented quickly, but they come with inherent vulnerabilities. This risks businesses from cyberthreats such as device theft, spoofing, denial of service attacks, and data breaches or siphoning. Attacks of this nature adversely affect an organization's operations, finances, safety, and reputation.
Many IoT and IIoT devices have passwords hard-coded into their firmware, making it challenging to patch or update security, which is a significant problem. Even when security is deployed on a device, it can usually be bypassed by taking advantage of a variety of known weaknesses. As a result, IT teams may find it challenging to identify an occurrence when IoT or IIoT devices are compromised before affecting systems and data.
Mitigating IoT and IIoT Security Risks
Separate IIoT and wireless devices from the SCADA or ICS network. Micro-segmentation allows only authorized device connectivity in certain circumstances.
Control network access by monitoring what connects and validating each device's security.
Demand visibility across all enterprise security networks and devices. This should be centralized so all devices, networks, risks, traffic, and policies can be handled in real-time across production and IT environments.
Use an intrusion protection system (IPS) to identify threats and patch IoT and IIoT devices virtually. Counter unexpected attacks with active protection and deception techniques.
It's crucial to check that security solutions can grow automatically to meet business requirements before using them. This entails responding to network changes, foreseeing risks and controlling them proactively, and offering real-time threat intelligence.
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Industrial IoT, Theory and Strategy
Article | May 17, 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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