Data transmission is one area where security should be among the biggest concerns. Overseeing data integrity is the realm of communications security (ComSec) teams, and they’re getting a lot of assistance these days from artificial intelligence (AI) via machine learning and other AI components that also prove helpful in improving accessibility.

Under the umbrella of AI, advances like assistive technologies promote accessibility while preserving data integrity and the flow of communications. In order to understand how this works, you must first understand the individual components and how they’re related.

What Does Data Accessibility Mean?

According to research, 74 percent of companies want to move toward a more data-driven model; less than 30 percent feel confident in their ability to make the transition.

The two main components of telecommunications security are maintaining privacy and integrity. These are known as the twin information assurance (IA) pillars. The trick is to make transmissions accessible to those who need the information while preventing access to those who don’t. This means at every level of an enterprise and without constraints on the ability of the people involved to access and benefit from the data.

Data access from an IT standpoint means that those who need information are able to retrieve, move, change, or store it easily and that it is clear and understandable. From a human standpoint, it also means that people are able to gain equal access and benefit regardless of visual, physical, cognitive, or hearing impairment.

You know this topic is a big deal when Microsoft issues a challenge. This one is called the AI for Accessibility initiative.

The hallmarks of a data-centric business model are to:

• Ensure that everyone is united around a core metric.
• Provide access to data by those who need it.
• Distribute data in such a way that each player gains insight from the information.

This leads to another important component of accessibility, data quality. High-quality data means more accessible data. This term can be somewhat subjective because quality can mean different things to different people. In general, data that is of poor quality increases errors, leads to bad decisions, and damages reputations.

For instance, an associate transposing numbers on a mailing address leads to packages being delivered to the wrong customer. The company ends up losing time, money and looking incompetent. According to information released by IBM, data quality issues cost about $3.1 trillion per year. To most people, that is a lot.

If Data Quality is Subjective, is There Some Metric for Evaluation?

There are two factors that go into assessing quality. The first is accuracy. How correct is the information? Next, you have to determine if the information is complete. Is there vital information missing that could change the entire meaning or relevance of the data? Using metrics like Data Quality Assessment Frameworks (DQAF), businesses can establish a baseline using information that is known to be accurate and relevant.

If you don’t put quality as a priority, are you really paying much attention to security? AI improves both by directly influencing accuracy and completeness while continually monitoring systems to protect access.

How Security is Improved Through AI

ComSec is a discipline that’s concerned with preventing access to telecommunications transmissions from unauthorized or malicious users by implementing communications security. That includes phones and internet services, as well as any written information that’s transmitted electronically. Since that’s a big tent that’s intended to cover everyone, it’s broken down into five distinct areas of concern:

1. Cryptographic security that creates a virtual private network (VPN) for internet access through the use of advanced encryption protocols. There are multiple options here, so it is important to understand the available VPN protocols and the differences between each one.
2. Emissions security, which prevents equipment emanations from being intercepted by unauthorized persons.
3. Physical security in order to protect access to data stored in databases and physical drives.
4. Transmissions security, which prevents interception of data while it’s in transit.

Artificial intelligence is modeled on the human brain’s own neural pathways. The ultimate goal is to create technologies that can act independently of human intervention or programming. Big data-enhanced apps are able to analyze and assess processes in real-time and act intuitively to redirect system response according to internal and external input as well as historical analysis. The more such systems are exposed to information, the more developed their capabilities become.

This is known as becoming “risk adaptive.” Rather than basing decisions about granting or denying access to the role a person has within the organization, a risk adaptive protocol assesses the threat level using multiple criteria and makes accessibility decisions on a case-by-case basis that can be adjusted automatically.

How AI Secures Data

As the major catalyst in the thriving cybersecurity market, AI chugs away evaluating sensory information, detecting patterns of behavior, and identifying anomalies that could indicate security breaches. The system responds by issuing live alerts or deploying security measures like shutting down access or isolating threats automatically. It can do so faster and with less opportunity for error than a squadron of security guards or an entire IT team. That means fewer false alarms and very little chance of an undetected breach occurring. Such systems then use this analysis and response to determine how it responds to similar threats in the future, each time refining its approach.

One inhibition of incorporating advanced tech into the workplace is the unfounded fear that AI replaces people. While it’s true that some workplaces are going to be more streamlined, it also allows essential workers the freedom to expand or reinvent the meaning of their job. Rather than putting ComSec professionals out of work, AI makes the job easier while improving data preservation, quality, and integrity.

Final Thoughts

With the advent of virtual office spaces and mobile workforces, protecting data at rest and in motion is imperative. Incorporating machine learning technologies and other components of artificial intelligence not only improves access to all who need it, but you’ll also enhance the security of personal and business communications. That’s a win-win all around.