Cyberattacks have become common to the point of being considered one of the strategic risks that businesses across all industries face today.
In recent years, there’s been an upsurge in hacking incidents targeting organizations both large and small. Typically, attackers are driven by the intention to steal or manipulate data. Moreover, the level of sophistication of these threats has also grown. No one today can claim to be immune to cyberattack.
The impressive evolution of artificial intelligence has touched off a raging debate about whether or not it’s a good thing. The role of AI in encouraging or abating various types of cyberthreats has also been highlighted. It has been argued that, depending on how it’s used, AI can be either a blessing or a curse to customers, cybercriminals, and businesses. It’s therefore pertinent to evaluate the impacts of AI in the field of cybersecurity.
The recent spate of cyberattacks has led many to argue that the future of security looks bleak. In the face of this anxiety, AI has emerged as a game-changer. Multiple tools and techniques supported by AI and machine learning have been developed. AI today is more than a buzzword; it’s a technological advance used in multiple industries. In the event, it’s playing a significant role in warding off cyberthreats.
Thanks to progress in AI and machine learning, organizations can detect cyberattacks in advance. They can analyze data and identify threats before they become vulnerabilities. This is a departure from traditional cybersecurity tools, which rely excessively on past data.
AI can be used in password protection and authentication. Passwords are a notoriously fragile means of control, yet are often the only barrier between data and cybercriminals. Many users, however, are lazy with their passwords, using the same one for multiple accounts. In such cases, data across many applications is in danger of being exposed if a cybercriminal gets wind of the password.
Cybersecurity systems relying on AI come in handy in situations where two-factor authentication is required to gain access to a system. To make biometric authentication watertight, developers are relying on AI to eliminate imperfections. For example, the recently debuted Face ID facial recognition technology on iPhone X devices can help to prevent hacking incidents.
Phishing is currently the most common method of cyberattack. According to experts, 1% of all emails are sent out by cybercriminals. AI can detect and monitor more than 10,000 active phishing sources, and remediate faster than humans. It allows for the differentiation of fake websites from legitimate ones, thus protecting against attacks.
To secure your network, you need to figure out its topography, in addition to creating a security policy. Such activities are not only cumbersome but also time-consuming. However, you can expedite the processes by using AI to observe and learn network traffic patterns. In the process, network security policies will be suggested to you.
Despite the virtually limitless ways that AI can help to secure networks, there are concerns that cybercriminals can use it as a mainstream tool for perpetrating attacks. For instance, threat actors could deploy AI to maintain a long-term presence in the target environment without being detected. AI-driven attacks are more likely to be tailored to target specific networks, and thus harder to detect. AI can also be used as a springboard for faster, more effective, and more complicated cyberattacks.
Critics have raised concerns over the development of adversarial AI. Hackers could use it to manipulate machine learning systems to misidentify and misreport potential breaches. One of the less talked about risks of AI is human complacency. Having adopting the technology as part of your cybersecurity strategy, you face the possibility of employees lowering their guard. The lack of awareness in an organization can lead to costly cyberattacks.
It’s an undeniable fact that AI has a major role to play in cybersecurity. An increasing number of companies are adopting the technology to meet their cybersecurity needs. Developers should be taking advantage of this trend to create cybersecurity solutions based on an AI framework.
The main challenge in implementing AI in the cybersecurity sphere is that it requires more resources than traditional cybersecurity efforts. With advances in security-as-a-service, there’s optimism over a widespread uptake of AI in cybersecurity.
Ken Lynch is founder and CEO of Reciprocity Labs.
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