AI is Not Stealing Jobs, Not at least in Cybersecurity

Artificial Intelligence

The landscape of Cybersecurity is ever-changing with developing trends and situations. Cybercriminals are a threat to all kinds of businesses, organizations, and the clients and consumers who use them, alike. The breaches are an economic burden for the users. These costs include notification costs, expenses associated with investigation, damage control, government-issued penalties, rapid investment in shoring up security, and repairs. According to an IBM study, such costs have increased by 12% over the past five years. And with personal data about hundreds of thousands of individuals being leaked, each one is potentially a new victim of fraud and other cybercrime. Besides, public disclosure of a data breach can lead to the average share price of a company falling by 7.27 percent along with low share value and growth underperformance a reality for years afterward.

A typical cyber-attack attempt is when adversaries or cyber criminals try to gain access, alter, or damage a targeted computer system or network in for malicious purposes. It is systematic, intended, and calculated exploitation of technology to affect computer networks and systems to disrupt organizations and operations reliant on them.

However, technologies like Artificial Intelligence and machine learning (ML) are also critical new tools in the global fight against cybercrime. AI techniques can transform the current asymmetric defender-versus-adversary balance in Cybersecurity. The speed and accuracy of these advances can enable systems to act autonomously, to react and defend at wire speed, and to detect overt and covert adversarial reconnaissance and attacks. Even Machine learning-based software employing techniques such as statistical analysis, keyword matching, and anomaly detection can help this cause by identifying if a given packet of data is different enough from the baseline of data packets used in the training dataset. AI systems can also be used in situations of multi-factor authentication to provide access to their users. So AI and ML are an indispensable tool to prevent cybercrimes. As per a report, 61 percent of enterprises say they cannot detect breach attempts today without the use of AI technologies.

Unlike the reputation of RPA to replace humans in jobs, AI in Cybersecurity instead helps to improve the lives of humans and enterprises. In an article posted on SearchSecurity AI helps Cybersecurity by

Augmenting the threat triage and prioritize threats: This is achieved by automating repetitive tasks, such as tedious data enrichment tasks or triaging low-risk alerts. By relegating lower-risk tedium frees human analysts’ time for higher-value decision-making, which is not only beneficial from a risk mitigation perspective but essential given the growing scope and complexity of today’s continually recalibrating threat landscape.

Minimize the Talent Gap: With rising no of threats, the need for skilled security analysts grows too. While the AI-powered tools are not capable of closing this gap by themselves, its tools can help reduce the dependency on humans. This is possible since AI extends the reach of individual analysts where less time is spent to understand what is going on and more time is spent mitigating and addressing risks. It further boosts productivity and helps in creating threat analysis.

Extension of data-democratized security protection: Under this with a security-minded workforce, every employee is trained, equipped, and empowered to deal with attacks with external assistance. Here, the supply side is coming up with tools that possess multi-language support, the ability to integrate with other software suites, have Automation and Response platforms, etc. And on the adoption side, there is an increase in emerging employee interfaces and safety investments to ensure proper defense.

Both AI and ML have proved to be extremely useful when it comes to detecting cyber threats based on analyzing data and identifying a risk before it exploits a vulnerability in your information systems. Besides, traditional technologies fail to keep up with the new mechanisms and tricks of hackers the way AI can. Although it is still in the infancy stage, major investments have to be made to resolve persistent cybersecurity challenges. Businesses need to ensure that their systems are being trained with inputs from cybersecurity experts that shall make the software better at identifying true cyber-attacks with far more accuracy than traditional cybersecurity systems.

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