Artificial Intelligence (AI) cites the bonding of machines with human intelligence mimicking the actions which confers to the achievement of specified tasks, outperforming human cognition and aiding to the repetitiveness.

In-line with such, Machine Learning (ML) enables a machine to attain structured or unstructured data training through which it analyses patterns and predicts further while developing self-cognition through experience. AI and ML signifies the importance of cognition that can mutilate the general conduct of responsibilities to a much efficient & quality driven performance.

Artificial Intelligence defines Machine Learning through a complete defined structure or a model which enables it to experience varieties. Similar to a child learning new things as it goes on experiencing varied nooks of life, machine learning enables a machine to learn through artificial intelligence, having neural networks in enhancing the performance of completing tasks on a real-time basis. As quoted by a computer scientist from Germany, Sebastian Thrun,

Nobody phrases it this way, but I think that artificial intelligence is almost a humanities discipline. It's really an attempt to understand human intelligence and human cognition.

Cyber Threats of AI and ML

The Fourth Industrial Revolution in 2020 marked a substantial change to the overview of technology, leading to the Worldwide Digitalization of services and Corporate Transformations, sectoring the vitality of machine learning in re-modelling the management structure. It is through AI and ML that the repetitiveness of tasks can be optimized through automation as the human resource can further be utilized in accomplishing other demanding tasks, in-line with their skills.

However, concerning such technological upheaval, cyber threat poses a serious concern to industries and governments. Few of the threats, as they are variably common in the present scenario of advancements, are

Financial Threats

As digitalization enforces elevated usage of digital mobile applications for various financial tasks, the threat of data theft as well as interruption to a transaction always puts forth major concern.

An application if not verified can serve as a tool to collect sensitive information which can be utilized to affect the financial condition of an individual. Apart from such, even at the latest, device cloning methods are often practiced by the fraudsters to manipulate an individual onto clicking a link sent via mail or messaging, which further adds to the security concern of sharing confidential data to a third party.

Data Confidentiality

Far beyond the conventional methods of assembling data through questionnaires or surveys, Artificial Intelligence has revolutionized the importance as well as the mode of data collection.

Sharing data has been made more easy as the technology advances to great achievements in AI and ML. A common instance of data being shared and utilized is, customization and personalization of user experiences by various e-commerce application like Amazon, Google or others. Creating dark patterns to lure in customers are often common in the online shopping platforms followed.

Brand Image

On contrary to the enhanced performance boost provided by AI, as cyber threat raises concern to data confidentiality, a corporate image may be hampered due to improper data handling techniques. As cloud technologies are highly suggested in the wake of digitalization, often data are not properly stored in cloud servers complying with all the specified directions of security.

Enhancing Cyber Security with AI and ML

Cloud computing has been the major catalyst in digitalization of sectors amid the COVID pandemic, in 2020. Modifying such with advancements to AI and ML, edge computing further showcases potential for real-time data transfer and communications enabling user experience to a marvel.

AI and ML not only enhances the technological advancements for digitalization of industries, but also improves performance in cyber security detection and other applications. Actively monitoring to making robust changes to security, which is also known as threat intelligence, AI provides support in securing data breaches and other cyber risks involved.

Security Information and Event Management

Security Information and Event Management (SIEM) is a cyber-security management tool used by businesses to secure data from the unwanted access, through real-time information on alerts generated by applications or network hardware.

One of the major drawbacks of SIEM in the present scenario of technological advancement is the required human intervention in the process of securing threats which were identified and logged in. Event Management involved in SIEM are categorized mainly as,

Data Aggregation involving collection of various data in one place
Data Normalization involving the process of correlating the unrelated data as per analysis and comparison
Data Analysis stating the potential breaches of data and identifying security threats involved.

Security Orchestration, Automation and Response

Filling out the gaps left by SIEM, Security Orchestration, Automation and Response (SOAR) implements machine learning at core, involving full automation in securing access and detecting future possible threats by analyzing all previous threat data.

Automation not only creates real-time environment, but also provides an integrated system wherein Artificial Intelligence takes over the tasks of performing better analysis and implementation of forecasts to drive business performance. Such enables further protection of cyber security through automatic adaptation to the threats and changes involved, thereby effectively combatting disparities by removing human interferences from threat management.

Thus, as AI and ML enhances capabilities of a machine to provide better cognitive solutions, it also adds to cyber concerns on security. However, noting down such differences, AI is more of a Boon to cyber security rather being a Bane to it.