# A Survey on Moving Target Defense: Intelligently Affordable, Optimized and Self-Adaptive
## 1 Introduction  
### 1.1. Motive  
To use a Chinese idiom to paraphrase the idea of moving target defense (MTD), _transferring flowers to wood_ is the most appropriate one, which refers to covertly grafting the branch of a flowering tree onto another flowering tree so that no one can tell what kind of flowering tree it was before. Likewise, the method that defenders constantly and dynamically use to shift the set of attributes that can be exploited by attackers to confuse them coincides with the idea behind this idiom. In a more concise and direct manner, a target can be defined as an entity or asset that is susceptible to exploitation by malicious adversaries, such as an application, computer, or system. MTD refers to a set of techniques that involves altering the properties or configurations of a target randomly and regularly or increasing its uncertainty and unpredictability, with the primary objective of enhancing the security defenses of the target while preserving its fundamental functionality. The concept of MTD arose from the reality that traditional cyber defense strategies focus on reinforcing the defense system, but this approach inevitably exposes information to attackers once the system is fortified. To counter this disadvantage, researchers proposed MTD as a revolutionary game-changing technique to address the growing complexity and variability of cyber-attacks. Unlike traditional defense strategies, which seek to harden and create an impenetrable system, MTD focuses on increasing the system's resilience by constantly shifting the attack surface, as shown in Figure 1. This makes it more challenging and costly for attackers to exploit vulnerabilities while limiting the time that the vulnerability is exposed. By implementing MTD, organizations can reduce the likelihood of successful attacks and increase their ability of responding effectively against cyber threats. In recent years, numerous MTD techniques have been proposed in response to the shortcomings of traditional cyber defense. Notably, the field of intelligent MTD has garnered significant attention and has become a subject of considerable interest in MTD research due to the extraordinary performance of machine learning algorithms in processing complex, massive, and high-dimension data in many tasks and have shown more accurate and collegiate performance in many complex problems [1] compared to traditional decision-making methods. However, research on intelligent MTD remains incomplete and lacks systematic summary investigations. While nearly 3000 papers have been published since 2018 on proposed MTD techniques, intelligent MTD research remains relatively scattered without being firmly integrated, with each researcher focusing on their own field. This situation stands in contrast to other intelligent techniques that have undergone comprehensive research and integration. As a result, research on intelligent MTD is currently inefficient and fragmented. The main challenges for intelligent MTD can be listed as follows. * The current state of intelligent MTD has not yet achieved a unified and comprehensive system. For instance, when classifying existing intelligent MTD techniques by applying them into five layers (network layer, platform layer, runtime environment layer, software layer, and data layer), it was observed that most of these techniques were primarily focused on the network layer, with little attention paid to other layers. This lack of attention to multi-layer protection was inconsistent with the continued development of a defense system for more than ten years. * Diverse intelligent MTD techniques require a systematic organization to facilitate researchers' comprehension of the evolution and trends of intelligent MTD. Such an organization is expected to contribute significantly to the development of intelligent MTD. Specifically, after organizing these techniques, researchers can gain insights into one of the emerging trends _toward self-adaptive_ as intelligent MTD is organized.