A Survey on Advanced Persistent Threats: Techniques, Solutions, Challenges, and Research Opportunities

Threats that have been primarily targeting nation states and their associated entities have expanded the target zone to include the private and corporate sectors. This class of threats, well known as advanced persistent threats (APTs), are those that every nation and well-established organization fears and wants to protect itself against. While nation-sponsored APT attacks will always be marked by their sophistication, APT attacks that have become prominent in corporate sectors do not make it any less challenging for the organizations. The rate at which the attack tools and techniques are evolving is making any existing security measures inadequate. As defenders strive to secure every endpoint and every link within their networks, attackers are finding new ways to penetrate into their target systems. With each day bringing new forms of malware, having new signatures and behavior that is close to normal, a single threat detection system would not suffice. While it requires time and patience to perform APT, solutions that adapt to the changing behavior of APT attacker(s) are required. Several works have been published on detecting an APT attack at one or two of its stages, but very limited research exists in detecting APT as a whole from reconnaissance to cleanup, as such a solution demands complex correlation and fine-grained behavior analysis of users and systems within and across networks. Through this survey paper, we intend to bring all those methods and techniques that could be used to detect different stages of APT attacks, learning methods that need to be applied and where to make your threat detection framework smart and undecipherable for those adapting APT attackers. We also present different case studies of APT attacks, different monitoring methods, and mitigation methods to be employed for fine-grained control of security of a networked system. We conclude this paper with different challenges in defending against APT and opportunities for further research, ending with a note on what we learned during our writing of this paper.