The Internet of Things (IoT) has the power to change the way we live and the way we work. Nowadays, the cost of accessing the Internet is very low compared to the beginning of the technology age. Mobile devices are becoming more adept and more devices are built with network connectivity and built-in wi-fi. All these conditions create the ideal scenario for the Internet of Things and for its action in the business world. In a very simplified way, Internet of Things aims to connect any device to the Internet. According to Gartner, by the year 2020 there will be more than 26 billion devices connected to the network. At home, this concept aims to make life easier for people, but its application will also have an impact on the business world. In a world so connected and everything is connected to everything, the security challenges are immense. In this article we will analyze the main security challenges that the Internet of Things brings us!
Things Internet devices need to be very well configured, otherwise they can be a real problem for businesses that need to keep their data private. You can not neglect the good rules in these devices (such as creating complex passwords, for example) as these can be incoming ports for improper access to the internal network.
With so many devices connected simultaneously, it is essential that there is real-time monitoring to verify that there are no threats entering the network. Do not just sporadically check the network security. With the Internet of Things you need to be always aware of everything that goes on the network to anticipate security problems and prevent data loss!
A hidden wi-fi network should only be created for IoT equipment. This ensures that even if one of these devices is attacked, the rest of the organization and its data are not endangered. IoT equipment is much more vulnerable than the rest of a company’s equipment, so it needs extra attention.
Masking the data has the main purpose of protecting confidential data against unauthorized access. In practice, data masking tools create a version similar to the original data in terms of structure but without revealing its true information. In fact, its original format remains unchanged but the data presented is fictitious. Masked data can be used in test and auditing environments, not compromising the result of the analysis, but always ensuring the confidentiality of sensitive information. A manual process to protect data consumes a lot of time and human resources so the best option is to resort to tools that do the process automatically, such as Datapeers.