AI-driven drone defense system

Abstract

The generated AI analyzes enemy communication protocols and control signals in real time, providing an attack system that hijacks the communications of enemy drones and unmanned aerial vehicles (UAVs) to bring them under control. [Solution] The attack system uses generative AI and ensemble learning to analyze the communication protocols of enemy drones in real time and neutralize or mislead the drones by intercepting communication control signals. Ensemble learning allows multiple AI models to analyze enemy communication data in parallel, and the optimal attack method is selected based on the integrated results, enabling high-precision response to encrypted communications and frequency hopping. The combination of generative AI and ensemble learning surpasses conventional systems that rely on a single model, providing a more effective and flexible attack method.

Description

Technical Field

[0001] The present invention relates to a dynamic control system for physical agents utilizing generative AI, and particularly to a technology for generating real-time adaptive action instructions for physical agents such as drones. Conventionally, generative AI has mainly been applied for the purpose of generating digital content such as text, images, and music. However, in the present invention, generative AI analyzes environmental data in real time and is used to realize complex action control of physical agents. By having generative AI play a new role of "adaptation" and "control" beyond the framework of digital content generation and generating dynamic action instructions according to real-time situations, it enables advanced applications that were not possible with conventional AI.

[0002] The technology of the present invention aims to disrupt the operation of enemy drones and unmanned aircraft by intercepting their communications using advanced analysis means that utilize generative AI and ensemble learning, thereby confusing the enemy's operations. By utilizing ensemble learning, multiple AI models analyze the enemy's communication protocols and control signals in parallel in real time and integrate the results, enabling high-precision interference and control seizure that cannot be achieved by individual models. This technology plays an important role in the military and defense fields and provides a new means of attacking enemy unmanned aircraft systems.

[0003] Furthermore, different from conventional physical interference means and static defense technologies, the present invention dynamically analyzes enemy communications and uses this to control unmanned aircraft, thus providing a more flexible and effective means of attack. This technology can avoid enemy jamming attacks and encrypted communications and, conversely, can aggressively intervene in enemy systems.

[0004] The attack system of the present invention is applied in the fields of electronic warfare and cyber warfare to strengthen the attack function against enemy unmanned aircraft. Thereby, in a combat environment, it is possible to disable enemy unmanned aircraft and ensure the superiority of one's own military.

Background Art

[0005] Traditionally, unmanned aerial vehicles (UAVs) and drones have been widely used for military and defense purposes. These drones play a crucial role in a variety of operations, including reconnaissance, surveillance, and attack, but they are vulnerable to enemy electronic warfare attacks and jamming due to their reliance on communication systems. For this reason, technologies that seize control of drones by disrupting or hijacking their communications have attracted attention. This invention, in addition to conventional technologies using generative AI, employs ensemble learning technology, allowing multiple analytical models to complementarily analyze communication protocols and improving the accuracy and effectiveness of successful real-time control seizure.

[0006] Conventional drone defense systems relied primarily on defensive measures such as frequency hopping and advanced encryption, but these were merely static response methods and lacked the capability to proactively intervene against enemy attacks. They offered limited protection against powerful enemy jamming and cyberattacks, highlighting the need for further offensive means to neutralize drone communications.

[0007] In recent years, advancements in generative AI and machine learning technologies have led to a shift from traditional defensive approaches to offensive ones. Generative AI has the ability to analyze vast amounts of data in real time and rapidly analyze enemy communication protocols. By leveraging this capability, offensive systems have become possible that can neutralize the communications of enemy unmanned aerial vehicles and drones and seize control of them.

[0008] Conventional technologies have relied on physical methods such as jamming devices and drone guns to disrupt drones, but these lacked the ability to dynamically analyze and counter enemy communication systems and control protocols. Furthermore, these physical disruption methods had limited range and effectiveness, making it difficult to completely control enemy drones.

[0009] This invention provides a new technology that utilizes generative AI to analyze enemy communication protocols in real time and offensively neutralize enemy unmanned aerial vehicles and drones. By dynamically analyzing enemy communications using generative AI and seizing control of or misleading enemy targets, it becomes possible to disrupt enemy operational activities. This technology offers a more flexible and effective offensive means compared to conventional physical jamming methods and static defensive techniques.

[0010] Furthermore, by using generative AI, it is possible to analyze enemy communication protocols, even if they are highly encrypted or hopping frequencies, and select the optimal attack method in real time. Such dynamic attack techniques are particularly effective in advanced electronic warfare environments where conventional static systems have difficulty responding.

[0011] Conventional drone defense technologies only allow unmanned aerial vehicles to simply defend against enemy jamming attacks, with little to no offensive capability. This invention utilizes generative AI to bring enemy unmanned aerial vehicles and drones under control, neutralizing enemy operations. This technology provides a new offensive means to reduce the enemy's offensive capabilities in electronic warfare and support friendly operations. [Prior art documents] [Patent Documents]

[0012] [Patent Document 1] Public Relations for Patent No. 6280430 [Patent Document 2] Public Relations for Patent No. 4932908 [Overview of the Initiative] [Problems that the invention aims to solve]

[0013] Conventional defense systems against unmanned aerial vehicles (UAVs) and drones have been limited to defensive functions and lack offensive capabilities. Specifically, defense systems using frequency hopping and encryption technologies have limited effectiveness against powerful enemy jamming and cyberattacks, and lack offensive means to seize control of enemy communication systems. Therefore, there has been a need for technologies that can proactively neutralize enemy UAVs and disrupt their operational activities.

[0014] Furthermore, conventional drone and unmanned aerial vehicle (UAV) defense systems were limited to passive defense against enemy attacks, and had limitations in their ability to proactively intervene and disrupt enemy operations. Additionally, existing defense measures were unable to dynamically analyze and respond to complex and highly encrypted enemy communication protocols. Therefore, there was a need for the development of technologies that could analyze enemy communications in real time and proactively intervene. [Means for solving the problem]

[0015] To solve the aforementioned problems, this invention provides an attack system utilizing generative AI. Specifically, it provides a technology in which generative AI analyzes enemy communication protocols and control signals in real time and hijacks the communications of enemy unmanned aerial vehicles (UAVs) and drones, thereby bringing the enemy UAVs under its control. This technology makes it possible to actively disrupt enemy operations by disabling enemy communications, causing misdirection, and seizing control. Furthermore, the generative AI of this invention is a technological asset of extremely high value in the fields of national security and defense. Real-time analysis and dynamic response generation using generative AI will strengthen the defense capabilities and deterrence of one's own forces, and will be valued as a highly confidential technology in national defense.

[0016] The generative AI not only analyzes enemy communications but also has the ability to dynamically select the optimal attack method in real time. In this invention, by introducing ensemble learning, multiple analysis models simultaneously analyze enemy communication data, and the optimal attack method is selected based on the integrated results. This makes it possible to appropriately respond to the communication system even when the enemy is jamming or encrypting, and to neutralize enemy drones. Furthermore, the adoption of ensemble learning improves analysis accuracy, enabling flexible and highly accurate attacks without relying on a single model.

[0017] Furthermore, because this system dynamically responds to enemy communications, it differs from conventional static defensive systems in that it can conduct flexible and rapid attacks. This technology provides an excellent means of offensive intervention against enemy drones in combat and electronic warfare environments, supporting friendly operations. [Effects of the Invention]

[0018] The AI-generated attack system for enemy unmanned aerial vehicles (UAVs) and drones, based on the present invention, significantly enhances offensive capabilities compared to conventional defensive systems, enabling the neutralization or interception of enemy communications. This makes it possible to effectively neutralize enemy drones and actively disrupt enemy operational activities. Furthermore, this invention possesses strategic value in national defense and security, and is expected to enhance the defensive capabilities and deterrence of one's own forces, particularly through real-time analysis of generative AI and dynamic response generation. The confidentiality of this system is also valued as an important technological asset for defense, and it can contribute to a new deterrent in national security.

[0019] By using generative AI, enemy communication protocols and control signals are analyzed in real time, enabling dynamic attacks. This allows for rapid and flexible responses even when enemy systems are highly encrypted or employing frequency hopping. This dynamic response capability makes it far more effective than traditional static defenses.

[0020] Furthermore, since the generative AI can not only analyze the enemy's communication protocol but also be used for aggressive operations, it is possible to seize control of the enemy's drones and conduct misdirection and neutralization. This technology can disrupt the enemy's combat operations and reduce the enemy's attack capabilities. As a result, it is expected that the friendly forces' combat operations can be carried out safely and efficiently.

[0021] The attack system of the present invention can intervene in the enemy's drone system flexibly and promptly beyond the conventional physical interference technology and simple defense systems. Therefore, in the context of electronic warfare, it is possible to ensure tactical superiority by blocking the movement of the enemy's drones. In addition, due to the use of generative AI, it can be used in a subscription-based format, and the fact that it can be operated reasonably and efficiently is also an important effect of the present invention.

[0022] Furthermore, in order to achieve real-time attacks, this system can always adapt to the enemy's situation continuously and has overwhelming superiority compared with static attack means. In addition, due to the learning ability of generative AI, it can quickly respond to the enemy's new tactics and attack methods, so its effect can be sustained even in long-term operations. The present invention has extremely high strategic value in the national defense system, and the immediacy and flexibility provided by generative AI also play an important role as a deterrent against enemy attacks. This technology should be highly evaluated from the perspective of national security, and is particularly recognized as a highly confidential technical asset in defense agencies.

Brief Description of the Drawings

[0023] [Figure 1] It is an overall system configuration diagram of an attack system for unmanned aerial vehicles (UAVs) and drones according to the present invention. [Figure 2] It is a flowchart of the attack means using the generative AI of the present invention.

Modes for Carrying Out the Invention

[0024] This invention is an attack system against unmanned aerial vehicles (UAVs) and drones that utilizes generative AI, and is designed to analyze enemy communication protocols in real time and seize control of them. The system's main components are a processor equipped with generative AI, a communication analysis module, and a communication control unit.

[0025] The generating AI analyzes communication data transmitted from enemy drones or unmanned aerial vehicles in real time, identifying their communication protocols, frequencies, and encryption methods. This allows it to determine the optimal attack strategy to disrupt or mislead enemy drones. The analysis results are sent to the communication control unit, where an attack is executed against the enemy drones.

[0026] The communication analysis module in this system receives enemy communication signals and converts the data into a format that can be analyzed by a generating AI. This module supports a wide range of frequency bands, enabling analysis of communications even when the enemy's communication frequencies are hopping. Furthermore, encrypted communication data can be decrypted through analysis by the generating AI, thus addressing the enemy's advanced security measures.

[0027] Attack methods primarily include "jamming" to disrupt enemy drone communications, "spurious signal transmission" to mislead enemy control signals, and "control takeover" to completely seize control of enemy drones. Based on the analysis results of the generated AI, the most effective method of these attacks is selected in real time. This makes it possible to efficiently neutralize enemy drones.

[0028] Fail-safe functionality also plays a crucial role in this system. If communication is lost or an attack fails, the generating AI autonomously reconfigures the system and selects an alternative attack method. This ensures that even if an attack temporarily fails, it can continue to execute attacks and reliably disrupt the operation of enemy drones.

[0029] This invention is suitable not only for military applications but also for cybersecurity, disaster response, and other applications. In particular, it is applicable to any unmanned aerial vehicle system that relies on wireless communication systems, providing flexible attack capabilities. Furthermore, the advanced learning capabilities of the generative AI enable rapid responses to new enemy communication technologies and tactics.

[0030] Furthermore, this system can also adopt a cloud-based subscription model. This allows users to always have access to the latest AI models and attack techniques in real time, and makes system updates easy. The ability to utilize advanced attack methods while keeping operating costs down is one of the important features of this invention. [Examples]

[0031] Specific embodiments of the present invention are described below. The attack system against unmanned aerial vehicles (UAVs) and drones using the generative AI according to the present invention is applied in military operations and the operation of defense systems to neutralize enemy drones and disrupt their operational activities. The generative AI has the function of analyzing enemy communication protocols and selecting appropriate attack means in real time. Example 1: Neutralizing enemy drones on the battlefield

[0032] The attack system of the present invention is used to neutralize enemy drones on the battlefield. For example, consider a scenario in which an enemy drone flies over friendly territory, attempting to conduct surveillance or attack. In this case, the attack system, equipped with generative AI, first receives communications transmitted from the enemy drone and analyzes its communication protocol and control signals in real time.

[0033] Based on the analyzed communication data, the system selects the most effective attack method. For example, it can jam enemy drone communications, rendering them inoperable, or its AI-generated signals can send false signals to mislead enemy drones. It can also completely seize control of enemy communications and disable drone operations. This neutralizes enemy drones, allowing friendly operations to proceed safely. Example 2: Taking control of an enemy drone system in cyber warfare

[0034] In cyber warfare scenarios, enemy drones may be remotely controlled via a network. This embodiment assumes a scenario in which a cyberattack is carried out against an enemy drone system and control is seized. The generated AI analyzes the communication network used by the enemy drone system and decrypts encrypted communication protocols and control signals.

[0035] After analyzing enemy communications, the system can send false signals to enemy drones, causing them to perform actions contrary to enemy instructions. Specifically, it can alter the enemy's designated flight path or misdirect attacks. Ultimately, the generated AI can seize complete control of the drone, forcing it to land at a desired location or be neutralized. Example 3: Misguiding of drones in urban defense

[0036] In urban defense scenarios, enemy drones may attack critical facilities and urban areas. In such scenarios, the system of the present invention is used to misdirect enemy drones. The generating AI receives communication signals emitted from enemy drones and rapidly analyzes their content.

[0037] Based on the analyzed information, the system sends false control signals to enemy drones, causing them to fly in a different direction. For example, it can divert the target to a harmless location away from critical infrastructure, effectively neutralizing the enemy attack. This process is carried out in real time, preventing attacks on urban areas. Example 4: Control and capture of enemy drones in military vehicle escort operations

[0038] When military vehicles are being monitored by enemy drones, there is a risk that the vehicle's location information and operational details may be leaked. In this embodiment, we assume a scenario in which the attack system of the present invention escorts a military vehicle. The generated AI analyzes the communication signals of the enemy drone while it is monitoring the vehicle and attempts to seize control of it.

[0039] Once communications are analyzed, the system hijacks the enemy drone's control signals, keeping the drone away from the vehicle. Furthermore, once the generated AI has taken control of the enemy drone, it can disable the drone's cameras and sensors, reducing the enemy's surveillance capabilities. This allows the vehicle to safely carry out its operations. [Industrial applicability]

[0040] This invention is an attack system against unmanned aerial vehicles (UAVs) and drones using generative AI, and is particularly useful as an offensive technology for neutralizing or controlling enemy drones in the military and defense fields. This system can analyze enemy communication protocols in real time and intercept or mislead communications, thereby securing a tactical advantage in electronic warfare and cyber warfare scenarios.

[0041] First, the present invention plays a crucial role in military applications. Unmanned aerial vehicles (UAVs) are widely used in reconnaissance and attack, and their numbers and operations are rapidly expanding. However, since the operation of UAVs heavily relies on communications, technologies to disable enemy communications and seize control are extremely important. The system of the present invention goes beyond conventional static defense systems and can significantly reduce the effectiveness of enemy UAVs by intervening dynamically and offensively.

[0042] Furthermore, this invention can be applied not only to defense systems but also to urban defense and the protection of critical infrastructure. In urban defense scenarios, there is concern about attacks on critical facilities by enemy drones, but the system of this invention can prevent damage to facilities by misdirecting these attacks. In addition, in the protection of critical infrastructure, it is useful as a means of neutralizing attacks by enemy drones when they target infrastructure.

[0043] Because the system of the present invention utilizes communication analysis and generative AI, it can be applied to various wireless communication systems. For example, it can be used as a technology to neutralize hostile drones in fields where industrial drones and commercial unmanned aerial vehicles (UAVs) are widely used. From a cybersecurity perspective, the present invention is useful as a means of preventing unauthorized access and manipulation by UAVs and can be used in a wide range of fields.

[0044] Furthermore, the technology of this invention can also be applied to disaster response and rescue operations. When hostile drones interfere with rescue operations, this system, using generated AI, can ensure the safety of rescue operations by misdirecting or taking control of the enemy drones. In particular, as drones become indispensable in rescue operations, quickly neutralizing the disruptive actions of enemy drones will greatly improve efficiency on the ground.

[0045] Furthermore, the present invention is also applicable to cloud-based subscription models. Since the generation AI models and algorithms are updated via the cloud, users can always utilize the latest attack techniques in real time. This allows for the use of cutting-edge technology while keeping operational costs down, which is a significant advantage, especially in the defense sector and civilian drone management.

[0046] Overall, the AI-powered attack system of the present invention has industrial applications in a variety of fields that rely on unmanned aerial vehicles, and its flexibility and responsiveness are expected to contribute to a wide range of uses, including military, civilian, defense, cybersecurity, urban defense, and disaster response.

Claims

1. An attack system characterized by using generative AI to analyze the communication protocols of enemy unmanned aerial vehicles (UAVs) or drones in real time, and intercepting enemy communication control signals to neutralize or mislead enemy UAVs.

2. An attack system according to claim 1, characterized in that the generating AI analyzes encrypted communications in real time and decodes the communication control signals of an enemy unmanned aircraft or drone.

3. An attack system according to claim 1 or 2, characterized in that, when the enemy is performing communication frequency hopping, the generated AI analyzes the frequency hopping pattern and responds dynamically to disrupt or intercept the enemy's communication control signals.

4. An attack system according to any one of claims 1 to 3, characterized in that the generating AI transmits a false control signal based on the results of analyzing the enemy's communication protocol, thereby misleading the enemy's drone.

5. An attack system according to any one of claims 1 to 4, characterized in that, after the generating AI intercepts the communication control signals of an enemy drone, it causes the drone to land at an arbitrary location or to cease its operation.

6. An attack system according to any one of claims 1 to 5, characterized in that the generating AI analyzes the sensor data of the enemy drone and transmits a signal that disables its sensor function, thereby reducing the surveillance capability of the enemy drone.

7. An attack system according to any one of claims 1 to 6, characterized in that the generating AI simultaneously analyzes multiple communication signals and transmits individual control signals to each enemy drone in order to simultaneously control multiple enemy drones.

8. An attack system according to any one of claims 1 to 7, characterized in that the generating AI automatically reconfigures the attack means when communication is interrupted or the attack fails, selects an alternative attack means and retries.

9. An attack system according to any one of claims 1 to 8, characterized in that the generating AI is operated on a cloud-based system and the system is kept up-to-date by utilizing the latest communication analysis algorithms and attack techniques provided on a subscription basis.

10. An attack system according to any one of claims 1 to 9, characterized in that the generating AI learns the operation patterns of enemy drones and automatically selects an attack means optimized for future attacks.

11. An attack system according to any one of claims 1 to 10, characterized in that the generated AI disables control signals from cameras and surveillance devices mounted on enemy drones, thereby hindering the acquisition of images and data.

12. An attack system according to any one of claims 1 to 11, characterized in that the generating AI analyzes the automatic flight path performed by the enemy drone and transmits a false signal that causes the path to be altered, thereby disrupting the enemy's operational actions.

13. An attack system according to any one of claims 1 to 12, characterized in that the generating AI analyzes enemy swarm control performed in cooperation by multiple drones, and neutralizes the enemy drone swarm by blocking communication between the drones.

14. An attack system according to claims 1 to 13, characterized in that the generating AI analyzes the enemy's communication protocol in real time based on ensemble learning of multiple analysis models and intercepts the enemy's communication control signals with high accuracy.

15. An attack system according to claims 1 to 14, characterized in that the generating AI selects the most effective attack means based on the result of integrating multiple models through ensemble learning, and interferes with or misleads the communication of enemy drones.

16. An attack system according to claims 1 to 15, characterized in that the generating AI dynamically responds to the enemy's frequency hopping and encryption based on the analysis results of multiple models by ensemble learning, and interferes with communication control signals in real time.

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