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Top 7 Security Measures for IoT Systems

It is important to understand that the Internet of Things (IoT) is based on the concept of providing remote user access anywhere around the world to acquire data, operate computers, and other devices. The widespread IoT network includes computing devices along with unrelated machines that are solely responsible to transfer data excluding human-to-computer or human-to-human involvement.

The outbreak of technology and vitality smart devices in diverse sectors such as energy, finance, government, etc, makes it imperative to focus on their security standards. As per security firm, Kaspersky, close to one-third (28%) of companies managing IoT systems were threatened with attacks impacting their internet-connected devices during the year 2019. Furthermore, almost 61% of organizations are actively making use of IoT platforms; thereby, enhancing the overall scope for IoT security in the coming years.

Below mentioned are seven crucial steps for a business to uplift IoT security for preventing a data breach.

Swapping Default Passwords

The foremost step to enhance IoT security is through a sensible approach. It is recommended for businesses to enforce procedures that permit the changing of default passwords. This action should be implemented for each of their IoT devices present on the network. In addition, the updated passwords need to be changed on a timely basis. For added safety, the passwords can be simply stored in a password vault. This step can prevent unauthorized users from gaining access to valuable information.

Detach Corporate Network

 Count it as an essential step to split the corporate network from unmanaged IoT devices. This can include security cameras, HVAC systems, temperature control devices, smart televisions, electronic signage, security NVRs and DVRs, media centres, network-connected lighting and network-connected clocks. The businesses can make use of VLANs to separate and further track various IoT devices active on the network. This also allows analyzing important functions like facility operations, medical equipment, and security operations.

Limit Unnecessary Internet Admittance to IoT Devices

Many devices run on outdated operating systems. This can become a threat since any such embedded operating system can be purposely reached out to command and direct locations. In the past, there have been incidents when such systems have been compromised before they got transported from other nations. To completely wash out an IoT security threat is not possible but IoT devices can be prevented from communicating outside the organization. Such a preventive measure outstandingly reduces the dangers of a potential IoT security breach.

Impact QA - IoT Security Measures

Control Vendor Access to IoT Devices

 In order to improve IoT security, several businesses have limited the count of vendors gaining access to different IoT devices. As a smart move, you can limit access to those individuals already functioning under the careful supervision of skilled employees. In case remote access is highly necessary, keep a check that vendors make use of the same solutions similar to in-house personnel. This can include access via a corporate VPN solution. Moreover, enterprises should assign a staff member to supervise remote access solutions on a regularly. This individual should be well versed with certain aspects of software testing to manage the task with proficiency.

Incorporate Vulnerability Scanner

The use of vulnerability scanners is an effective method in detecting the different types of devices linked to a network. This can be viewed as a useful tool for businesses to improve their IoT security. Vulnerability scanner in collaboration with a regular scanning schedule is capable of spotting known vulnerabilities related to connected devices. You can easily access several affordable choices of vulnerability scanners available in the market. If not a vulnerability scanner, try accessing free scanning options such as NMAP.

Utilize Network Access Control (NAC)

An organization can successfully improve IoT security by implementing a NAC solution consisting of a proper switch and wireless assimilations. This setup can help detect most devices and recognize problematic connections within the network. A NAC solution, for example, ForeScout, Aruba ClearPass, or CISCO ISE, are efficient tools to secure your business network. If in case a NAC solution doesn’t fall within the budget, you can make use of a vulnerability scanner for fulfilling the purpose.

Manage Updated Software

Having obsolete software can directly influence IoT security for your organization. Try to manage your IoT devices by keeping them up-to-date and replacing the hardware to ensure smooth operations. Delaying the update can prove a crucial factor to safeguard data and invite serious cybersecurity breaches.

Security arrangements with IoT devices are helpful for businesses to minimize operational costs, enhance productivity, and deliver better customer experience. The above pointers can be understood and applied to sharpen IoT security directed at escalating your business’s reach. To learn more about safeguarding IoT devices, you can simply connect with professional experts at ImpactQA.

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How IoT and Machine Learning is changing the World?

  • What is Machine Learning?
  • What is the Industrial Internet of Things (IIoT)?
  • How IoT (Internet of Things) and Machine Learning affect our life?
  • Challenges- IoT and Machine Learning
  • Solution

IoT and Machine Learning are getting smarter. Companies are incorporating artificial intelligence (AI)—in specific, machine learning—into their IoT apps. From smart thermostats to wireless sensors, IoT devices are gradually but positively garnering mainstream adoption. Virtual assistants like Siri, Alexa, and Cortana are only making this technology easy to adopt.

The core purpose behind advancement in the IoT space is to help information move smoothly and seamlessly. For as much as we condemn technology, we can all recall a moment when the right message has appeared at the right time, with perfect user experience.

The truth of IoT and Artificial Intelligence – specifically machine learning – is far less sinister. It is shaping the way we live, travel, work, and communicate. In fact, it is shaping our lives smartly and the decisions we make.

The proliferation of smart IoT devices is shaping the future and gives instant access to the information world.

Let’s have a glance at these burning IoT statistics:

  • There are about 17 billion inter-connected devices in the globe as of 2018. With more than 7 Billion of these IoT (internet of things) devices. (Source- IoT Analytics)
  • According to McKinsey Global Institute, each second, 127 new IoT devices connect to the net.
  • The global IoT market is expected to be worth $1.7T in 2019. (Source: CBI Insights)
Worldwide  Iot Active Connection Graph
Worldwide IoT Active Connection Graph

What is Machine Learning?

ML is one of the critical components of AI, where a computer is programmed with the ability to improve its performance. In short, Machine Learning is all about analyzing big data – the automatic extraction of information & using it to make predictions.

Netflix, Amazon, Google, and other E-Commerce platforms use it to bring semantic outcome. It is based on algorithms that analyze the user’s purchasing history to predict their preference. Machine learning is gradually integrating into all verticals, through automation of physical labor, we are improving the connectivity and shaping the future of AI and the IoT.

What is the Industrial Internet of Things (IIoT)?

The Industrial IoT or Industry 4.0 or the 4th industrial revolution are the terms generally used for IoT technology in a business setting. The concept is similar to the consumer IoT; to use wireless networks, a mix of sensors, big data and analytics to optimize industrial processes.

IoT devices provide information and analytics to connect the world of hardware devices and high-speed internet.

We can separate the Industrial IoT into two main categories:

  • Industrial IoT- The Industrial IoT, connects devices and machines in sectors like healthcare, transportation, power generation, etc.
  • Commercial IoT– Commercial IoT sits between industrial IoT and consumer and shares aspects of both.

How IoT (Internet of Things) and Machine Learning affect our life?

IoT and ML are improving the way we live and communicate in our lives. For instance, the AlterEgo headset easily responds to our brainwaves to control appliances and on the other hand, Alexa and Amazon’s Echo enables the voice-activated control of your high-tech smart-house.

This amalgamation of IoT and Machine Learning is changing various industries and the relationships that companies have with their clients. Businesses can easily gather and transform data into valuable information with IoT.

IoT is also transforming business models by helping companies to move from concentrating on products & services to companies that give the best outcomes. By impacting organizations’ business models, the blend of IoT-enabled devices & sensors with ML creates a collaborative world that aligns itself around results & innovation.

Challenges- IoT and Machine Learning

These days’ enterprises are flooded with data that comes from IoT devices and is seeking AI to help manage the devices. It is tough to manage and extract crucial information from these systems than we might expect.

There are aspects to IoT like data storage, connectivity, security, app development, system integration, and even processes that are changing in this space. Another layer of complexity with the Internet of Things has to do with functionality level.

Critical challenges that companies face with IoT and ML are with the application, ease of access, and analysis of IoT data. If you have a set of data from varied sources, you can run some statistical analysis with that data. However, if you want to be proactive to predict events to take future actions, a business needs to learn how to use these technologies.

Many firms are turning to the main cloud platform providers — for instance, Google, Amazon, Microsoft, Alibaba Cloud, or IBM. These companies offer a range of services to store IoT data and prepare it for data analytics, plus to train and run machine-learning models. They also assist in creating graphs, dashboards, and other simple-to-grasp layouts to visualize the information these models generate. Overall, IoT and Machine Learning are combined to provide high visibility and control of the wide range of devices connected to the Internet.

Solutions-How can we help you?

Futurists say ML (Machine Learning) and the Internet of Things (IoT) will transform business profoundly than the digital and industrial revolutions combined.

Are there some kinds of risks? Yes, as with any new technology, we have to accept both the profit and risks that come with mainstream adoption. We can do this with the confidence only when these technologies are tested against several odds.

One of the innovative solutions for seamless operation flow is IoT testing. There will be several other types of testing which require to be considered to cover the comprehensive functionality of IoT devices.

As part of ImpactQA’s Advisory Services, we also provide an implementation plan to help our clients improve time-to-market while keeping their business goals in mind. We use our assessment frameworks (like Chatbot testing framework, RPA Testing framework, etc.), based on industry best standards, focusing on processes, tools, and infrastructure.

Collaborate with our specialists to improve all QA areas – people, processes, tools, and infrastructure across the delivery life-cycle.

Learn More

How IoT and Machine Learning is changing the World?

  • What is Machine Learning?
  • What is the Industrial Internet of Things (IIoT)?
  • How IoT (Internet of Things) and Machine Learning affect our life?
  • Challenges- IoT and Machine Learning
  • Solution

IoT and Machine Learning are getting smarter. Companies are incorporating artificial intelligence (AI)—in specific, machine learning—into their IoT apps. From smart thermostats to wireless sensors, IoT devices are gradually but positively garnering mainstream adoption. Virtual assistants like Siri, Alexa, and Cortana are only making this technology easy to adopt.

The core purpose behind advancement in the IoT space is to help information move smoothly and seamlessly. For as much as we condemn technology, we can all recall a moment when the right message has appeared at the right time, with perfect user experience.

The truth of IoT and Artificial Intelligence – specifically machine learning – is far less sinister. It is shaping the way we live, travel, work, and communicate. In fact, it is shaping our lives smartly and the decisions we make.

The proliferation of smart IoT devices is shaping the future and gives instant access to the information world.

Let’s have a glance at these burning IoT statistics:

  • There are about 17 billion inter-connected devices in the globe as of 2018. With more than 7 Billion of these IoT (internet of things) devices. (Source- IoT Analytics)
  • According to McKinsey Global Institute, each second, 127 new IoT devices connect to the net.
  • The global IoT market is expected to be worth $1.7T in 2019. (Source: CBI Insights)
Worldwide  Iot Active Connection Graph
Worldwide IoT Active Connection Graph

What is Machine Learning?

ML is one of the critical components of AI, where a computer is programmed with the ability to improve its performance. In short, Machine Learning is all about analyzing big data – the automatic extraction of information & using it to make predictions.

Netflix, Amazon, Google, and other E-Commerce platforms use it to bring semantic outcome. It is based on algorithms that analyze the user’s purchasing history to predict their preference. Machine learning is gradually integrating into all verticals, through automation of physical labor, we are improving the connectivity and shaping the future of AI and the IoT.

What is the Industrial Internet of Things (IIoT)?

The Industrial IoT or Industry 4.0 or the 4th industrial revolution are the terms generally used for IoT technology in a business setting. The concept is similar to the consumer IoT; to use wireless networks, a mix of sensors, big data and analytics to optimize industrial processes.

IoT devices provide information and analytics to connect the world of hardware devices and high-speed internet.

We can separate the Industrial IoT into two main categories:

  • Industrial IoT- The Industrial IoT, connects devices and machines in sectors like healthcare, transportation, power generation, etc.
  • Commercial IoT– Commercial IoT sits between industrial IoT and consumer and shares aspects of both.

How IoT (Internet of Things) and Machine Learning affect our life?

IoT and ML are improving the way we live and communicate in our lives. For instance, the AlterEgo headset easily responds to our brainwaves to control appliances and on the other hand, Alexa and Amazon’s Echo enables the voice-activated control of your high-tech smart-house.

This amalgamation of IoT and Machine Learning is changing various industries and the relationships that companies have with their clients. Businesses can easily gather and transform data into valuable information with IoT.

IoT is also transforming business models by helping companies to move from concentrating on products & services to companies that give the best outcomes. By impacting organizations’ business models, the blend of IoT-enabled devices & sensors with ML creates a collaborative world that aligns itself around results & innovation.

Challenges- IoT and Machine Learning

These days’ enterprises are flooded with data that comes from IoT devices and is seeking AI to help manage the devices. It is tough to manage and extract crucial information from these systems than we might expect.

There are aspects to IoT like data storage, connectivity, security, app development, system integration, and even processes that are changing in this space. Another layer of complexity with the Internet of Things has to do with functionality level.

Critical challenges that companies face with IoT and ML are with the application, ease of access, and analysis of IoT data. If you have a set of data from varied sources, you can run some statistical analysis with that data. However, if you want to be proactive to predict events to take future actions, a business needs to learn how to use these technologies.

Many firms are turning to the main cloud platform providers — for instance, Google, Amazon, Microsoft, Alibaba Cloud, or IBM. These companies offer a range of services to store IoT data and prepare it for data analytics, plus to train and run machine-learning models. They also assist in creating graphs, dashboards, and other simple-to-grasp layouts to visualize the information these models generate. Overall, IoT and Machine Learning are combined to provide high visibility and control of the wide range of devices connected to the Internet.Top 5 Mobile Application Testing Tools

Solutions-How can we help you?

Futurists say ML (Machine Learning) and the Internet of Things (IoT) will transform business profoundly than the digital and industrial revolutions combined.

Are there some kinds of risks? Yes, as with any new technology, we have to accept both the profit and risks that come with mainstream adoption. We can do this with the confidence only when these technologies are tested against several odds.

One of the innovative solutions for seamless operation flow is IoT testing. There will be several other types of testing which require to be considered to cover the comprehensive functionality of IoT devices.

As part of ImpactQA’s Advisory Services, we also provide an implementation plan to help our clients improve time-to-market while keeping their business goals in mind. We use our assessment frameworks (like Chatbot testing framework, RPA Testing framework, etc.), based on industry best standards, focusing on processes, tools, and infrastructure.

Collaborate with our specialists to improve all QA areas – people, processes, tools, and infrastructure across the delivery life-cycle.

Learn More