Overseas Technology Center
Businesses have been built or optimized using IoT devices and their data capabilities, ushering in a new era of business and consumer technology. Now the next wave is upon us as advances in AI and machine learning unleash the possibilities of IoT devices utilizing “artificial intelligence of things,” or AIoT.
AI IoT allows devices to communicate with each other and act on those insights. These devices are only as good as the data they provide. To be useful for decision-making, the data needs to be collected, stored, processed, and analyzed.
This is due to two problems: the cloud and data transport. The cloud can’t scale proportionately to handle all the data that comes from IoT devices, and transporting data from the IoT devices to the cloud is bandwidth-limited. No matter the size and sophistication of the communications network, the sheer volume of data collected by IoT devices leads to latency and congestion. Several IoT applications rely on rapid, real-time decision-making such as autonomous cars. To be effective and safe, autonomous cars need to process data and make instantaneous decisions (just like a human being). They can’t be limited by latency, unreliable connectivity, and low bandwidth.
Autonomous cars are far from the only IoT applications that rely on this rapid decision making. Manufacturing already incorporates IoT devices, and delays or latency could impact the processes or limit capabilities in the event of an emergency.
In security, biometrics are often used to restrict or allow access to specific areas. Without rapid data processing, there could be delays that impact speed and performance, not to mention the risks in emergent situations. These applications require ultra-low latency and high security. Hence the processing must be done at the edge. Transferring data to the cloud and back simply isn’t viable.
Every day, IoT devices generate around one billion gigabytes of data. By 2027, the projection for IoT-connected devices globally is 42 billion. As the networks grow, the data does too. As demands and expectations change, IoT is not enough. Data is increasing, creating more challenges than opportunities. The obstacles are limiting the insights and possibilities of all that data, but intelligent devices can change that and allow organizations to unlock the true potential of their organizational data. With AI, IoT networks and devices can learn from past decisions, predict future activity, and continuously improve performance and decision-making capabilities. AI allows the devices to “think for themselves,” interpreting data and making real-time decisions without the delays and congestion that occur from data transfers. AIoT has a wide range of benefits for organizations and offers a powerful solution to intelligent automation.
Risk management is necessary to adapt to a rapidly changing market landscape. AI with IoT can use data to predict risks and prioritize the ideal response, improving employee safety, mitigating cyber threats, and minimizing financial losses.
Some industries are hampered by downtime, such as the offshore oil and gas industry. Unexpected equipment breakdown can cost a fortune in downtime. To prevent that, AIoT can predict equipment failures in advance and schedule maintenance before the equipment experiences severe issues.
AI and IoT is the perfect marriage of capabilities. AI enhances IoT through smart decision making, and IoT facilitates AI capability through data exchange. Ultimately, the two combined will pave the way to a new era of solutions and experiences that transform businesses across numerous industries, creating new opportunities altogether.
IoT combined with AI has numerous benefits for these hurdles, including improving diagnostic accuracy, enabling telemedicine and remote patient care, and reducing the administrative burden of tracking patient health in the facility. And perhaps most importantly, AIoT can identify critical patients faster than humans by processing patient information, ensuring that patients are triaged effectively.
The benefits of a zero-trust network include: Greater security. Attacks usually originate far from the intended target, such as a corporate network. Attackers also frequently piggyback on approved users' access before moving laterally within a network to gain access to targeted assets. Ability to manage dispersed infrastructure. Network infrastructure has become more complex and dispersed, with data, applications, and assets spread across many cloud and hybrid environments. Users are working from many locations as well, making it more difficult to define a defensible perimeter. In fact, simply securing a perimeter is an outdated approach to a complex challenge that varies widely from company to company. Simpler approach to security. Historically, organizations have layered security solutions to block attackers.
Over time, this can create security gaps for attackers to compromise. With zero-trust networking, security is seamless and more well integrated throughout networks. How does a zero-trust network operate? The zero-trust philosophy is "never trust, always verify." Traditionally, network perimeters were secured by verifying user identity only the first time a user or device entered an environment. With zero trust, networks are built around "microperimeters," each with its own authentication requirements. Microperimeters surround specific assets, such as data, applications, and services. Through segmentation gateways, authentication is defined not just by user identity but also by parameters such as device, location, time stamp, recent activity, and description of the request.
These complex authentications are more secure and can occur passively in the background. Narrowly defined authentication rules protect networks from unauthorized users. They also grant approved users only the specific privileges for which they have an immediate need. This workflow helps ensure that even if attackers gain entry, they can't move freely in the network environment.
Why is ZNTA needed?
Zero trust application access hides apps and services from discovery and authorizes access only to specific applications. By not allowing access to an entire network, ZTNA lowers the impact of a breach, reduces business visibility on the public internet, and minimizes security risk. What are the benefits of zero trust network security? Zero trust network security helps protect data, reduce risk, and build resilience by providing: Adaptive, context-aware access policies Continual user and device behavior monitoring Fast, secure access to cloud and network applications Unified management Scalable, simple adoption