What’s the best cybersecurity SaaS for a small company with a fair number of IoT-enabled devices?

A cybersecurity posture is essentially the total procedures, policies, and services that an organization uses to defend itself from cyber attack. Companies evaluate their security risk then develop policies, employee training procedures, and, if they have the resources, malware, virus, and other threat detection services, focusing on their most vulnerable assets. In short, a cybersecurity posture describes an organization’s cyber threat readiness and identifies areas where this readiness can be improved.

A large proportion of data breaches come from authorized network users. Since they have network privileges, however, this type of cybersecurity threat is extremely difficult to address. Insider threat detection comprises the methods and technologies that organizations use to identify and mitigate these insider threats. There are various types of insider threats, not all intentional or malicious. Pawns, for example, are simply victims of phishing or other social engineering traps while Goofs lost confidential data due to ignorant or arrogant flaunting of security policies. The malicious types of insider threats come from Collaborators and Lone Wolves, who are rarely encountered.

MFA stands for multi-factor authentication. It refers to the use of more than one means of identification to access a secure software system. Usually, MFA security uses a combination of traditional security measures, like keycards and passwords, and biometric measures, like retinal scans. A subset of MFA security, which uses two, three, or more authentication measures, 2FA security uses two.

As organizations continue to adopt IoT technology, ensuring secure access to a private network becomes particularly difficult. Network access control systems, however, protect network data by requiring user authentication and authorization before every request. These systems also proactively address security breaches, though many also integrate with anti-virus or malware systems that organizations already use.

Network segmentation refers to the act of dividing different parts of a network into separate segments or subnets. This is done either physically or technologically, usually as part of a network access control system that limits who can access what parts of the network. Once organizations have identified subnetworks, they establish virtual fences around them using a variety of techniques, including VLANs, SDNs, and firewalls.

A predictive maintenance model uses sensors and IoT technology to monitor the condition of equipment and predict when it will need repairs or replacements. This equipment may be anything from personal cars to large factory machines. The machine learning programs used to run these models tend to take either the regression approach or the classification approach. Regression produces more accurate results but relies on more data; classification best predicts equipment failure within a set time period.

Whether for vehicles, industrial equipment, or mental health conditions, diagnosis is crucial to resolving problems but very difficult to do remotely. Thankfully, however, new advances in technology and artificial intelligence have made remote diagnostics possible.

Remote employee management refers to the methods of managing remote workers. Whether they are seasoned in-field professionals or office workers newly adjusting to working from home, the approaches may be different but the data collection and analysis will be similar. In these fraught times, especially, managers must take special care to account for their employees’ mental states.

Smart factory technology allows factory sensors to communicate with each other, with employee mobile devices, and with management's software platform. This enables employees to monitor equipment 24/7 and receive immediate alerts whenever there is a problem. The technology also enables the equipment itself to automatically adjust operations in order to keep the factory running smoothly.

Warehouse management systems run machine learning software to maintain a warehouse or distribution center (or a fleet of them).