AI for CyberSecurity: Managing Threats and Upscaling Risk Management

by August 10, 2020

Incorporating Strategies and solutions, and identifying the threat areas in cybersecurity network would help in minimizing the risk associated with using Artificial Intelligence

Any technology is a double aged sword. It has Pros and cons. And while pros are imperative in governing any organization, the cons reflect the flaws of technology which is hard to ignore. Hence Artificial Intelligence is no exception for being a threat, especially for cybersecurity.

Over the years, the threat regarding AI concerning cybersecurity has grown. Despite AI being used by Businesses and enterprises for facial recognition and to improve the business environment, its risks and threats are undeniable. With advanced AI, cybercriminals are now more rampant in attacking organizations, businesses, and political institutes. Even social media platforms are at the frontline for being abused by cyber malware.

In 2019, the Israeli Spyware Pegasus raised an alarm about the use of Artificial Intelligence in infringing cybersecurity. It exposed the most underestimated misuse of AI for privacy violations. However, Pegasus is not the only malware that reflects the flaws of AI in cybersecurity. The manipulation of political systems, threat to national security, discrimination, and misuse of customer data are amongst the listed threats of AI that threaten cybersecurity.

Hence, the organizations require being more vigilant in understanding the security threats with AI, in augmenting the data processing and identifying the necessary measures required to implement AI with cybersecurity.

In October 2019, the World Economic Forum has listed cyber attacks amongst the ten global risks of immediate concern. It is estimated that businesses worth $US 90 trillion can be lost in 10 years if necessary actions are not taken to combat cyber attacks.


Prioritizing Imperative Cybersecurity Areas 

The amount of convoluted data received by different web portals, social media, mobile devices, sensors, and the internet of things is voluminous. It becomes difficult to identify data malware, which is often veneered in the form of anonymous data.

Often the security snags within a company act like a loophole through which data can be discriminated by weaving zip code. This infringes on the privacy of users.

Hence it becomes imperative for any organizational set up to identify the areas that require utmost attention, recognize the absent risk management system, and strategizing a solution to recognize and fix the threat incorporated with cybersecurity.

This can be accomplished by automating cybersecurity with AI, to facilitate certain decisions in cyberspace. The risks and threats with the cyberspace must be categorized, listed, and rated. This segregates the vulnerable points in the cybersecurity network that requires an immediate strategic solution to block the cyber attack.


Supplementing Current Cyber Capabilities

Incorporating, an AI-driven cybersecurity model to augment current cyber capabilities aids in analyzing the potential threat within the network. It advances the quality and efficacy of cybersecurity operations, recognizes the abnormal patterns in operations, enhances detection and response, reforms the classification of data, prioritizing vulnerabilities, and deepfake detection and analysis.


Identifying ways through which AI adds value to a cybersecurity Network

The relationship between AI and cybersecurity is pivotal for any organization to function smoothly. It is a proactive approach that provides insight into the ongoing operation to anticipate a threat and respond to it. It promotes AI to make data-driven decisions. Thus protocols, policies, procedures, and stringent measures are necessary to understand the relation between AI and cybersecurity methods. This provides control over the risk management system and helps in chalking out strategies for improved cybersecurity.