Cloud Computing is, simply, a technology that enables data storage and processing take place outside of mobile devices. When combined with the Internet of Things (IoT) it achieves a much better environment for the use of Big Data.

While the integration of these technologies can bring about several advancements, there are security concerns that need to be addressed. Recently, an algorithm has been proposed to put some of these security concerns to rest.

Integration of IoT and Cloud Computing

IoT can be defined as a network of physical items that are capable of being connected to a network. These interconnected items can both gather and store data, whether the items are devices, vehicles, or buildings. The data collected and used across these devices is large, complex, and needs to be analyzed. This is where Big Data comes into play. To operate, Big Data uses Cloud Computing as a base technology. As this base technology, Cloud Computing then works to get the maximum capacity and performance out of the existing infrastructure.

While the combination of the IoT, Cloud Computing, and Big Data can offer access to information and data at any time in any location, there is still the potential issue of personal data security.

Initial Privacy Problems

IoT technology can consist of cyber-physical systems like automatic sensors, actuators, and embedded systems that will interact with humans for real-time support, security, personality, and high-level support. 

The greatest asset of IoT also doubles as the biggest weakness. The ability for devices to connect and transmit data through networks is great until a cyberattack threatens the security of the device and your data. If a single device is affected by malware, it can trigger a domino effect, negatively impacting every piece of technology on the network.

This often happens due to vulnerabilities in the communication software of devices connected to much more important devices in the network. These vulnerabilities can arise in anything from security cameras to vending machines.

For these issues to be rectified, an IoT device that needs to be directly accessed through the Internet should be portioned into its own network.  The device is separated from others in its vicinity and placed on its own wireless network. While the device would still have internet access, it would be on a separate virtual local area network or VLAN. This makes it easier to be regularly monitored to identify any signs of abnormal traffic.

Additionally, Cloud Computing offers storage, applications, and service functionality over the internet. Thus, because internet security vulnerabilities are constantly changing, Cloud Computing must also evolve to protect personal information, data, and applications.  When we use applications such as Microsoft, Adobe, or Slack, we trust that our data is safe.

Unfortunately, the answer to whether or not to share your personal data in the cloud isn't as straightforward as we would like. While cloud services do take precautions for the information that is uploaded, it is ultimately all pooled in the same cloud.

Big Data that is stored in the cloud is especially at risk to hackers. The problem is, once data is uploaded to the cloud, it can't be encrypted by the users. It needs to be decrypted for the cloud to perform operations with the data.

Security issues were also found during the use and development of Big Data technology. Technologies that specialize in securing data often run slower when applied to large amounts of data. This created a need for security technology to both protect and process these large amounts of data effectively.

Possible Security Issues of Cloud Computing and IoT Integration

Combining the technologies of Cloud Computing and IoT can result in a symbiotic relationship. Cloud Computing can make up where IoT is lacking in limited storage or applications over the internet. On the other hand, without IoT, the Cloud would have nowhere to pull its data from.

When critical IoT applications move to merge with Cloud Computing technology, additional concerns arise. For example, there is a level of concern about the lack of trust in internet service providers. The knowledge of service level agreements and the lack of understanding about the physical locations of data also leaves much to be desired.

For example, a large amount of data needs to be stored and managed at a data center.  However, the user whose data is being stored has no idea where this location is. We don't know who is storing this information or what they could be doing with it.

One of the biggest challenges in the integration of these two technologies relates to the heterogeneity of devices and systems. These systems operate very differently, with a wide variety of communication methods, protocols, and network connectivity options.

So, with all these problems, is a solution possible?

The AES Algorithm

The solution could be encryption, but not just any type of encryption will work to protect data.

The Advanced Encryption Standard (AES) algorithm may help to resolve many of the aforementioned security concerns. It's fast, flexible, and can be implemented across different platforms. As a bonus, it performs consistently well across both hardware and software in various environments.

Put simply, the AES algorithm is a type of encryption that keeps your information out of the wrong hands. It works by changing plain text into cipher text, which appears as random characters. To decrypt this text, a special key is needed by both the sender and receiver of the information. 

AES uses symmetric key encryption. This means that you need the same keys for the encryption of plain text and the decryption of cipher text. Read more on that here. Without this encryption, data is much easier to intercept and access. In this way, only those who are authorized to have this information will have access to it.

There are no serious weak keys in AES, and it has speedy key setup time and good key agility.

This makes it a great candidate to handle large amounts of data in the cloud without being subjected to sluggish processing.

This collected information can then be transmitted between machines that are supported by IoT technology. Then, the information can be safely and securely processed and computed through the support of different Cloud Computing services.

What Does the Algorithm Accomplish?

Experiments suggested that the AES algorithm helps achieve secure Cloud Computing and IoT integration. Through this integration, and utilization of AES, the Cloud-based IoT system would not only be able to connect sensors but to also allow them to share their readings with other sensors.

Sensors being able to connect and share information securely to the cloud would give companies real-time reports and data; it increases efficiency and protects sensitive data at the same time.  With the support of IoT technologies, this makes it possible for both hardware manufacturing resources and software manufacturing to be intelligently perceived and connected to wider networks. 

The proposed algorithm model combines Cloud Computing and IoT technologies while improving the security of data usage. Through encryption and the added security of symmetrical keys of the AES algorithm, users can feel confident that their data is safe. This may be the first of many steps towards further improving the integration of Cloud Computing and IoT technologies.

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About the Author

Daniel Browning is the Business Development Coordinator at Automation Webstore. In his spare time, he writes about automation, AI, technology, and the IoT.