A Systematic Literature Review and a Conceptual Framework Proposition for Advanced Persistent Threats (APT) Detection for Mobile Devices Using Artificial Intelligence Techniques
Advanced persistent threat (APT), which differs significantly from traditional network attacks, has emerged recently. Cyber attacks, or APTs, known for their ability to steal intellectual property, disrupt critical infrastructure, or cause millions of dollars in damages, are a growing concern . In contrast, traditional network attacks have been employed as cyber attacks for many years to compromise computer network security and steal sensitive information. These attacks exploit network systems and protocol vulnerabilities to gain unauthorized access to networks, steal confidential data, or disrupt normal network operations. The common types of traditional network attacks are denial-of-service (DoS), man-in-the-middle (MITM), sniffing, phishing, and structured query language (SQL) injection [2,3].
According to Powerful Growth, the global APT protection market is expected to reach USD 20,290.7 million by 2027, expanding at a 20.9% compound annual growth rate (CAGR). The global APT defense market is estimated to rise rapidly throughout the forecast period, given the exponential growth of cyber attacks globally, including malware and APTs . Read More
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