Aritificial Intelligence: The Future of Cybersecurity
My article was originally published on Vocal Media.
As the world is increasingly becoming digital, cybersecurity threats continue to spike in numbers. Cybercrime is now becoming prevalent and more sophisticated in this age of connected-ness and cloud computing. Companies, on the other hand, are excessively relying on digital technologies across global industries.
The artificial intelligence in the cybersecurity market is anticipated to reach USD 38.2 billion by 2026 at the highest CAGR of 23.3%.
It goes without saying that cyber threats accelerate in a time of global crisis whether it is the economic recession of 2008 or global pandemic 2020. Cybercrimes become more cataclysmic and businesses become more vulnerable, which allows cybercriminals to exploit the system to the best of their ability.
According to studies, Scams skyrocketed by 400% during the pandemic, additionally, Google blocked almost 18 million daily malware and phishing email attacks related to Covid-19 in April 2020.
Thus, identifying Covid-19 as the massive cybersecurity threat ever.
As mentioned before, cyberattacks are becoming more diverse, therefore companies must integrate smart technologies to their business networks such as AI to defend the vulnerable systems and data from digital attacks before they happen.
According to a report by Capgemini, almost two-thirds of the companies think that AI will surely help identify critical threats and therefore is favored by industries worldwide especially because of the following reasons:
- Constantly growing number of IoT and connected devices
- Concern of network exposure towards cyber risks
- Increasing focus on consumer and company sensitive data protection, and
- Increasing vulnerabilities in Wi-Fi and cloud networks
Artificial intelligence is excessively used to detect network threats.
Through Machine/Deep learning technologies and Behavioral analysis, companies can detect and identify the anomalies in real-time through highly accurate insights before they evolve. Early detection can defend industries against malicious attacks that are intended to damage operations and reputation. This AI-based risk assessment can assist companies in identifying and prioritizing risks based on their levels such as low and high, for taking an immediate security action.
Not just detection, system administrators can train the system based on Machine learning principles to predict attacks. Through applications of behavioral analysis, companies can identify behaviors that may seem malicious which allows organizations to further take preventive measures to block such attacks.
The applications of AI can scan through a large amount of data and make predictions about the threats by identifying compromised accounts and suspicious user behavior.
Detecting and predicting possible fraud threats not only prevent financial losses but also enhances the entire customer experience.
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Speedy responses to threats are essential for organization’s security.
AI reduces the total response time by up to 12%-15% otherwise taken to detect breaches.
Which gives companies enough time to remediate a breach and implement necessary actions. AI’s real-time monitoring provides insights about power consumption, bandwidth usage, etc, to assist in optimizing the entire data center infrastructure’s efficiency and security.
Besides, real-time notifications can alert companies about their hardware failures before absolute damage takes place consequently reducing the maintenance costs in the process as failures are reported early on. All in all, network security is enhanced twofold.
It won’t be long until AI becomes a familiar part of cybersecurity solutions.
AI-powered systems may not be foolproof, since cybercriminals can, too, use automated AI to harm businesses, but still, AI is a blessing in disguise. This technology is not only able to automate tedious mundane tasks but also decreases the chances of costly human errors.
The Bottom Line
A constantly evolving digital landscape can lead to increased security challenges. Many organizations are already deploying AI-driven solutions to eliminate risks and many are still exploring the opportunities that incorporating AI into their systems can bring.
Companies should restrategize their network security policies and goals to address gaps, abnormalities, and vulnerabilities in the system which would otherwise bring deadly repercussions if not addressed appropriately. Developing a proper security roadmap can save companies from unnecessary damages and losses.
Not only cybersecurity, but businesses around the world are leveraging the applications of AI/ML to optimize their existing processes for higher ROI such as healthcare industry, eCommerce sector, travel and tourism, mobile app development, education sector, customer services and others.
Key Takeaways
- AI combined with ML, DL and Behavioral analysis detects cyber-attacks and malicious activities
- Helps in predicting endpoints for cyber threats
- Ameliorates human analysis
- Automates the company’s security procedures
- Offers a quick response time.
