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Brett Clawson
Brett Clawson

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Data Security Becoming Tighter than Ever with A.I

The information age has come with its own set of advantages and top on that list is that you can store data in the cloud and access it from any corner of the globe. Organizations had left behind the days when if any documentation was to be filed, it had to be the paper way. However, these new and efficient data storage methods have also created their own set of challenges. For instance, while it was previously easy to track documents and make sure that no one tampered with them, it is currently not hard for data systems to be hacked, compromising data security. Fortunately, the nature of IT is that it morphs to respond to the upcoming challenges in the market, which is why AI and ML applications are shifting their focus to data security.

What is AI and ML in data security
Everyone understands that artificial intelligence and machine learning is what has made it possible for computer software to be fed a set of instructions and use them to make intelligent analyses, recommendations and even predictions about situations. In security, AI and ML systems are predefined in such a manner that they figure out when an action takes place contrary to the set standards, which leads to a set reaction. A simple example of AI use for cybersecurity is when you try to log onto an account or system, and the system tells you to enter a password or repeat a captcha code. When you are unable to provide the correct password for a number of times, the system locks and instructs you to try using your email or phone to regain access.

Accelerating incidence detection and response
Ai software has been developed to meet a large number of functions which improve cybersecurity. The first frontier has been to make sure that the rates of incidence detection improved. To this end, the AI software is configured in such a way that as soon as it detects something happening contrary to the norm, an email is sent to the person who owns the application in question. A simple example would be attempting to log onto an email account from a new device. AI detects new IP addresses, IMEI numbers and other device unique features and automatically sends an alert to the user. These alerts will allow the user to either reset their password or check the source of the threat and act accordingly. These applications are becoming essential across the board, and auditing has not been left out. AI can help you reach the recognized SAS 70 standards in auditing by detecting cyber-crime before it even happens.

Speech recognition and other biometric software
Mobile technology has been growing rapidly, and this has brought along the tendency for people to store and share data and even personal information on these devices. Hackers take advantage of the low security to access systems and steal money or access important personal data. As a response, there is now AI software which uses fingerprints and speech recognition only to allow people access to mobile apps, email accounts, and mobile banking applications. This makes it harder for hackers to access personal data, which is still doable when the only level of security is passwords.

These are some of the ways in which AI has transformed cybersecurity. As information technology morphs, AI is getting replaced by ML, which is more brain-like that AI. With Machine learning, the systems not only learn the predefined rules but know how to apply them to new situations and make informed system decisions. For instance, AI will lock you out of your own account if you forget or mistype a part of the password, but ML will look into factors such as the device being used, your IP address and others to decide whether to offer you alternative ways to access your system. These are the developments which could make cybersecurity a reality in the future.

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