AI and ML in data security act as a blessing for businesses of all sizes, ensuring information security from any external threats.
Artificial intelligence or AI is a technology that focuses on making intelligent machines that can assist and automate processes. AI tries to make software think like how a human brain thinks, with the help of algorithms. In simpler terms, AI’s mission is to implement human intelligence in machines. Machine learning is a subset of AI; it allows machines to predict outcomes accurately without having to be provided with algorithms and to learn from its users how they expect it to function. The primary mission of ML was to work on algorithms that make a machine capable of receiving information and statistically analyzing data, providing acceptable outputs. Organizations are leveraging ML on a vast scale and Gartner suggests, “By 2020, customers will manage 85% of their relationship with the enterprise without interacting with a human”. With an increase in sources of incoming data, industry pioneers are still on their toes to ensure adequate security of their information. Data is considered to be one of the most crucial assets that an organization holds, as businesses store all types of information from customer credentials to employee database to past ventures, which an organization does not want to be public. Such information when hacked can cause brutal damage to the reputation of an organization. AI and ML in data security could be technologies that can help organizations in achieving their goal of safeguarding their information.
Challenges in data security for businesses
When an organization focuses on collecting information from numerous sources and using the same to extract insights for increasing its sales, threats follow and manage to create issues that lead to hackers unearthing vulnerabilities. Some of the primary challenges faced by organizations in ensuring data security initiate from their employees. Whenever an employee visits a suspicious website or clicks on an infected link, the information stored in their system get compromised. Such a click often leads to network infection, making the company susceptible to further breaches. Apart from employees, enterprises often face the challenge of their security systems not being up to the mark and leading to opened backdoors, inviting hackers to steal their information. Even after updating their software systems, companies face the problem of inevitable information leaks; this occurs because of the organization’s inability to continually keep a check on how well their security systems are operating.
AI and ML in data security for businesses
AI and ML are technologies that are being leveraged by the likes of IBM Watson and is helping other organizations in improving data security. The technologies focus on detecting threats in the earlier stages of attack implementation. IBM QRadar, an advisor powered by Watson, assists businesses in unearthing hidden risks and availing insights. Using AI and ML, companies get notifications about how and when human interruption is required to prevent a system from getting sacrificed. AI is vital in cybersecurity because with its assistance the response time for cyber-attacks is shrinking drastically.
As modern day enterprises are accumulating data from numerous sources, securing information is of utmost importance for companies. AI and ML in data security can assist security analysts in reducing the time taken by authorities to prevent data theft. As AI and ML focus on securing information by working with algorithms provided to them, they can also learn about how specific threats are classified. With such techniques, these technologies can quickly scan through the abnormal behavior of the system and determine if those abnormalities classify as potential threats. Apart from scanning through the anomalies, these smart systems are also enabled to alert the experts to intervene and take control of the situation.
CTOs and CIOs should now focus on how they can leverage these technologies to increase data security in their organization. Apart from leveraging these technologies, authorities should also focus on how employees can be trained to ensure that they do not visit malicious websites masked as legitimate websites. Moreover, they should also search for ways in which their current systems can be updated to increase the security levels, if they are already leveraging certain types of AI and ML enabled data security measures.