###### Abstract
Finally, Knifefish of the US Navy fleet can detect and classify mines in large depths of the underwater environment with high clutter [3]. NATO is integrating UUVs in their fleet gradually, trying to counter several challenges. An important, still open, issue in this domain of research is interoperability. Most of the systems/platforms that NATO is using, as well as the ones developed by research institutes, follow their own standards and protocols for command, communication, and control, creating the obvious need for interoperability via a cross-platform approach. In addition, the water, as an environment for data transmission between UUVs, raises another prominent issue, i.e., the security of underwater networks. More specifically, cybersecurity assessment and security updates should be a continuous concern, along with the data sender/receiver authentication. In the era of big data and the Internet of Things (IoT), the volume (sensor) data that is created and exchanged in a communication network is, at least, voluminous. Moreover, the data exchanged in this context have more characteristics, referred to as the four Vs, i.e., volume, variety, velocity, and veracity [4]. Considering that the exchange of big data between various heterogeneous underwater/surface/air systems/platforms should be performed in real-time, this process, when performed in a medium of transmission with extremely low bitrate (i.e., in the water) and with several physical phenomena influencing the quality of transmission, is considered highly unsafe. The principal concern of latency in safe communications, is the delay in (re)distributing a vast number of data packets, to evaluate alerts from cyber-incidents and consequently to counter them. Moreover, due to the volume of exchanging information, recurrence of the same data is another deterrent issue which is encountered, along with \"sieving\" these data, decongesting the underwater network and accelerating the quality of the transmitted information. Let us assume the following SAR scenario (Figure 1). A swarm of UUVs must travel to the location of a plane crash at sea, safely and quickly, while interoperating in an underwater sensor network (UWSN), exchanging information/data in real-time, utilizingadaptive path-planning. During the execution of their assigned tasks, an unusual delay in communication between them and with the underwater nodes is identified, affecting the robustness of the network architecture, resulting in the inability to receive information from the commander. An automated analysis of the incident issues an alert for huge numbers of packets, overwhelming the network, thus, an incoming DoS (denial of service) attack is flagged. Consequently, an automated process of various counter-measures methods and protocols is initiated, such as honeypots, encryption algorithms, security rules, etc. For training and anticipation optimization, such a scenario must be simulated for commanders, developing a simulation tool always available for consulting and training, validating, and updating security protocols, as well as learning to anticipate such critical situations quickly and effectively by testing alternative topologies, and so on, minimizing handling costs and life losses. Based on our experience, it must be stated that we do not consider SAR scenarios to be different from other IoUT scenarios (e.g., military ones) in terms of cybersecurity. In the era of long-lasting 'cold wars' between numerous nations, SAR operations, for instance, are targeted by the provocative ones as an opportunity to show off power. The aim of this research is the study of related works, open issues, and challenges, towards the proposal of a novel simulation tool-supported approach to support commanders of military/search-and-rescue operations to effectively make critical and life-saving decisions.