The international company F5 has highlighted the key security challenges that can be addressed by artificial intelligence and machine learning.
Mohamed Abu Khater, Vice President of F5 in the Middle East, Turkey, and Africa, stated that “Artificial intelligence and machine learning technologies are becoming increasingly significant in various technology discussions these days. They consistently stand out in meetings and gatherings with customers, partners, analysts, and other stakeholders in the technology industry.”
Below are the main security challenges faced by companies, for which artificial intelligence and machine learning tools can provide effective solutions:
Countering Automated Attacks:
Automated attacks are often launched by networks of robots. These attacks expose companies to various risks, including losses resulting from fraud, inventory manipulation, reputational damage, data theft, and infrastructure damage. Detecting and effectively mitigating automated attacks require the ability to distinguish between human and automated traffic.
While this may seem straightforward in theory, it is practically a challenging task that necessitates a diverse set of technologies. One of these technologies involves using artificial intelligence and machine learning solutions, specifically applied to the challenge of differentiating unwanted automated traffic from legitimate human traffic.
Fraud Prevention and Mitigation:
Companies can suffer losses from fraud in multiple ways, but two major forms significantly impact the digital channels they use. These are Account Takeover (ATO) fraud and Account Opening (AO) fraud. ATO fraud typically involves an unauthorized party using stolen credentials or employing techniques like Man-in-the-Browser (MITB) or social engineering. On the other hand, AO fraud entails an attacker opening an account using stolen or synthetic Personally Identifiable Information (PII).
API Security:
Companies have embraced technological advancements to meet constantly evolving market demands. This includes developing and deploying applications directly used by customers and Application Programming Interfaces (APIs) to meet end-user requirements.
In some cases, these applications and APIs were released without sufficient security measures and guarantees, while in other cases, they were not properly managed, resulting in potential vulnerabilities and risks.
In this regard, AI-powered fraud detection plays a crucial role in enterprise operations. It can identify undocumented or unmanaged APIs, ensure API protection through appropriate authentication mechanisms, and verify the absence of sensitive data in requests and responses.
Mohamed Abu Khater emphasized, “Artificial intelligence and machine learning are powerful and effective tools that should be employed to tackle specific security and fraud challenges. They have demonstrated their high capabilities and efficiency in dealing with various critical issues faced by almost all companies.”
