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The following article is sourced from Defense News, authored by Huan Guoyang, Guo Xiaohong, etc., and reprinted from the China Command and Control Society.
Abstract
First, this paper analyzes the numerous challenges faced in the construction of kill chains; secondly, based on this analysis, it proposes a new construction paradigm for kill chains composed of foundational paradigms, functional models, and Engagement Sequence Groups (ESG), providing theoretical support and modeling frameworks for kill chain construction. It introduces a control model based on ESG, combining three typical operational styles: “search and destroy,” “call for fire,” and “authorize strike,” and presents corresponding functional models. Subsequently, it proposes a comprehensive architecture for the kill chain system integration that combines a shared cloud service environment with distributed element nodes. It designs a functional architecture for the engagement control system with resource basemaps and battlefield variables as inputs, event bus and rule management as the engine, a three-level dispatching system as the core, and ESG as the output, describing the core functional design ideas and providing solutions for kill chain system integration. Finally, it offers forward-looking suggestions on key areas for future development and primary research directions.
0
Introduction
As the patterns of warfare evolve rapidly, the overall confrontation between systems has become mainstream. Integrated coordination, intelligent collaboration, and cross-domain fusion have become fundamental trends in the evolution of future warfare. Focusing on defeating strong opponents and winning high-end wars, accelerating the construction of kill chains that can achieve victory now and in the future is crucial for winning competition in kill chains and seizing the initiative in strikes. Currently, advancements in weapon systems, the development and refinement of multi-domain combat theories, and the practical demands for dynamic target strikes are driving the evolution of kill chains into more complex and multi-dimensional kill networks while also presenting numerous new challenges for their construction. Designing a construction paradigm for kill networks that can support multi-modal operations of new and old weapons and adapt to different operational styles, as well as designing an integrated architecture for kill chains that can unify and integrate the operational speeds, capabilities, strike methods, and rhythms across different operational domains, has become key to the construction of kill networks.
1
Analysis of Issues and Challenges
1.1 The Evolution of Operational Styles Injects Driving Force into the Concept of Kill Chains
In 1996, regarding dynamic target strikes, former US Air Force Chief of Staff Ronald Fogle proposed the concept of the kill chain—a sequential chain composed of interdependent links in the process of striking a dynamic target, dividing operations into six stages: find (Find), fix (Fix), track (Track), target (Target), engage (Engage), and assess (Assess), known as F2T2EA.
In 2018, regarding mosaic operations, the US Department of Defense’s Defense Advanced Research Projects Agency (DARPA) first introduced the concept of the kill network at the C4ISRNET conference, aiming to enable any weapon platform to access information from any sensor across domains, avoiding functional failures of the entire chain due to issues in a single link.
The kill network is a combinable integration of various operational elements, capable of executing multiple independent kill chains by associating specific elements. Essentially, the kill network is an evolution of the traditional kill chain construction method, designed for agile construction, cross-domain collaboration, and resilient resistance to destruction in precise strikes against large-scale dynamic targets. Traditional kill chains, constructed in a strictly defined manner (static routing), executed in a serial manner, and focused on connection and resource exclusivity, limited single operational resources to focus on a single kill chain at a specific time. In contrast, kill chains constructed based on the kill network feature agile software definitions (dynamic routing), parallel execution of multiple chains, and resource sharing based on networks, thereby overcoming these limitations (except for consumable resources, such as loitering munitions), maximizing the parallel scale of kill chains.
Therefore, the evolution of operational styles is the fundamental driving force behind the emergence and evolution of the kill chain concept, and supporting and adapting to operational styles is the fundamental basis for designing and testing the kill network construction paradigm.
1.2 Advances in Weapon System Technologies Bring New Changes to the Operation of Kill Chains
As technology advances, the relatively fixed traditional kill chain model (such as F2T2EA) can no longer fully apply to the rapidly developing informationized and intelligent warfare forms.
On one hand, the stage divisions of traditional kill chains are no longer distinct, with some stages now executed in parallel or overlapping. For example, the emergence of multifunctional sensors integrates communication, radar, electronic warfare, as well as intelligence, surveillance, and reconnaissance (ISR) capabilities, allowing the discovery, fixation, and tracking stages to be autonomously completed by sensors. Some equipment systems have already acquired capabilities to replace traditional combat personnel in kill chain links, such as integrated reconnaissance-strike platforms, where traditional targeting and engagement stages are completed by the weapon itself. Some operational styles have emerged with nested kill chain stages, such as reconnaissance-strike unmanned systems, which incorporate reconnaissance, control, countermeasures, and strike (reconnaissance-control-counterstrike) into a complete closed-loop kill chain process.
On the other hand, with the increase in automation of weapon systems and the enhancement of intelligent technologies, the traditional “pre-defined” execution process of kill chains is no longer suitable for the changes in strike styles. For instance, for semi-autonomous weapons, like space-based detection guiding carrier-based cruise missiles to engage maneuvering naval targets beyond visual range, the kill chain process involves discovery, launch, fixation, strike, and feedback, representing a typical “sensor-dominant” kill chain process. For highly intelligent autonomous weapons, such as smart loitering munitions combining autonomous identification, detection, fixation, and strike capabilities, the kill chain process includes launch, discovery, fixation, strike, and feedback, representing a typical “shooter-dominant” kill chain process. For conventional weapons, such as multiple self-propelled artillery brigades suppressing a target area according to a combat plan, the kill chain process consists of discovery, fixation, launch, completion, and feedback, representing a typical “decision-maker-dominant” kill chain process.
Therefore, designing a construction paradigm and integrated architecture for kill networks that can support multi-modal operations of new and old weapons and adapt to varying operational methods becomes crucial for joint command across multi-domain weapon platforms.
1.3 The Development of All-Domain Combat Theories Brings New Challenges to the Integration of Kill Chains
Under the all-domain combat concept, the kill network is not merely a simple superposition of kill chains across various operational domains, but needs to transition from a unidirectional, two-dimensional chain structure to a complex, multi-dimensional network structure. However, due to the unique characteristics, requirements, platforms, and weapons of each operational domain, integrating kill chains into a kill network is not an easy task.
First, although the execution processes of kill chains in various operational domains are fundamentally similar, significant differences still exist among them. For instance, the execution speeds of kill chains vary greatly, the reconnaissance targets and capabilities of sensors differ, and the attack methods, strike ranges, and damage effects of weapons are markedly different, with the kill chain in the network domain being particularly unique.
Secondly, since each specific problem has its specific solutions in designated domains, achieving cross-domain integration of kill chains necessitates overcoming inherent barriers among different military branches. This includes technical barriers to interconnectivity, as systems from different branches were not designed with future integration into a kill network in mind; it also encompasses conceptual barriers to kill chain integration, as completely breaking military branch limitations remains unrealistic. Coordinating and overlapping kill chains with different natures and rhythms may lead to contradictions rather than synergies.
Thus, designing an integrated architecture for kill chains that can unify and integrate the operational speeds, capabilities, strike methods, and rhythms across different operational domains becomes crucial.
2
Research on Kill Network Construction Paradigms
2.1 Overall Construction Ideas
The term “paradigm” was proposed by Thomas Kuhn, referring to a way of thinking or theoretical framework that can be used to explain phenomena or problems in a particular field, characterized by guidance, normative nature, and universality. Essentially, a paradigm serves as the underlying logic of a complex system.
Although traditional kill chains did not propose the concept of a paradigm, the typical F2T2EA illustrates that it is a pre-defined, static, mechanical, and linear sequence of events. The evolution from traditional kill chains to kill networks is not only a quantitative change but also a revolution in thinking. It requires elevating these two-dimensional kill chains (static linear event sequences) to six-dimensional kill networks (connecting six war domains into one dynamic network). Thus, philosophically speaking, it represents a paradigm shift, a qualitative change and leap.
The kill network features task diversity, cross-domain resource sharing, and target variability, making it challenging to find a universal construction paradigm. To this end, this paper innovatively proposes a new construction paradigm for kill networks composed of foundational paradigms, functional models, and Engagement Sequence Groups (ESG), as illustrated in Figure 1.
The foundational paradigm is a set of basic and refined rules and standards for conducting kill network research, capable of summarizing, defining, and interconnecting different examples, theories, methods, and tools existing in military confrontations, exercises, and training, also known as “theoretical paradigms” or “conceptual paradigms.”
The functional model refers to the logical process of the kill chain established by combining the basic elements of the foundational paradigm in chronological order for specific operational styles, scenarios, and categories of strike targets. Moreover, the setting of decision points is a focal point of the functional paradigm. In a sense, the functional model can also be understood as “application paradigms” or “logical paradigms.” This paper provides corresponding functional models for three typical operational actions: “search and destroy,” “call for fire,” and “authorize strike.”
ESG is a physical process of a kill chain established by the various components of the kill network targeting specific strike objectives at specific moments, forming task cards for operational elements and driving the execution of kill chains, serving as the core to ensure the implementation of kill chains.
In terms of positioning and function, the foundational paradigm resembles the “Dao,” addressing issues of guiding ideology and essential laws, belonging to the metaphysical level; the functional model resembles the “Fa,” addressing principles and rules, belonging to the methodological level; ESG resembles the “Shu,” addressing practical applications and operational levels; while the components of the kill network perform the function of “Qi,” belonging to the material, energy, and information levels, which also includes the engagement control system, the core function of kill network capability integration.
2.2 Design of the Foundational Paradigm
This paper proposes the CF5 foundational paradigm or “meta-paradigm.” CF5 refers to the six major links in the closed kill network for dynamic target strikes, namely engagement control (Control), reconnaissance discovery (Find), target indication (Fix), weapon launch (Fire), flight strike (Finish), and closed-loop assessment (Feedback), covering the necessary links and human-machine collaboration mechanisms required for the operation of the kill network. The CF5 foundational paradigm composition is illustrated in Figure 2.
1) Reconnaissance discovery: Refers to discovering and dynamically generating targets from massive unformatted information, including various detection data, intelligence data, and public opinion data gathered from multi-source approaches under complex battlefield confrontation conditions, while continuously tracking dynamic targets, specifically including target attributes, locations, operational speeds, and electronic characteristics.
2) Target indication: Refers to matching various weapons in the kill chain resource pool based on target data, generating the necessary target indication information for weapon strikes in real-time, or matching fire control radar channels for strike weapons.
3) Weapon launch: Refers to the launch of strike weapons driven by command or target indication information.
4) Flight strike: Refers to the process where strike weapons, after being launched, autonomously navigate or guide to the intersection of the target and the projectile based on pre-launch parameters or online target guidance information, autonomously seeking and striking the target.
5) Closed-loop assessment: Refers to real-time evaluation of strike effects, including physical damage and functional damage assessments, providing inputs for the conclusion or re-initiation of the kill chain.
6) Engagement control: Refers to the core link for constructing, operating, and adjusting the kill network, essentially acting as the kill network controller, achieving integration and adaptation of kill chains through ESG generation; it serves as the connection point for human-machine interaction in the kill chain, providing various control modes such as pre-authorized control, command control within the loop, and status monitoring on the loop by setting decision points at different stages of the kill chain, capable of adapting to different target strike requirements.
2.3 ESG Design
2.3.1 Controller Models
The control cycles of various levels of controllers differ, with the control cycle’s action point being the decision point. The system-level controller’s control cycle primarily conducts control adjustments “human-centric,” with magnitudes ranging from minutes to days; the system-level controller’s control cycle matches different operational scenario modes, conducting control adjustments “rule-centric,” with magnitudes ranging from minutes to hours; the platform-level controller’s control cycle conducts control with a “machine autonomy” fixed period, generally on the order of seconds.
2.3.2 System-Level Controller Model
From the perspective of control models, the system-level controller model exerts differential adjustment control over the kill network, forming the basis for achieving the optimal solution for multiple kill chain collections, addressing the flexibility and empowerment issues of the system. Its control model parameters determine the overall structure of the kill network, subsequently influencing its scale and resilience core indicators, acting on the derivatives of deviations (changes in battlefield situations), primarily aimed at enhancing the stability of kill network operations and the proactive response to potential scenarios.
From an operational perspective, the output of the system-level controller model is a first-order ESG, conducting “formation-style” dispatching aimed at operational effects, matching combat plans, scheduling resources such as reconnaissance, command, firepower, and support across land, sea, air, space, and network domains, and conducting a relatively long operational cycle (from minutes to days) of the all-domain kill network system operation. The output clearly specifies the types, ranges, rules of engagement, and resource compositions, roles, and responsibilities of the engagement resources, with weak associations and loose coupling among resources.
2.3.3 System-Level Controller Model
From the perspective of control models, the system-level controller model provides proportional adjustment control for the kill network, enabling rapid responses based on current actual situations, conducting executable dispatching for specific targets within specific timeframes, directly affecting the deviations themselves (the current target set to be struck), with its core being to solve specific kill chain execution control parameters, determining the closure speed of the kill chain.
From an operational perspective, the output of the system-level controller model is a second-order ESG, conducting “execution-style” dispatching aimed at the engagement process, matching combat plans, and scheduling available resources within authority, constructing links from sensors to the best shooters that meet conditions, determining resource compositions, launch positions, detonation timings, and coordination timings across different engagement timelines, with strong associations among resources in temporal and spatial relationships and loose coupling among various kill chains in resource occupation.
2.3.4 Platform-Level Controller Model
From the perspective of control models, the platform-level controller model has integral adjustment functions, aiming to eliminate cumulative deviations (resolving all residual errors from previous links as much as possible to ensure final hits), solving collaborative control parameters among platforms under constraints of weapon unit flight speeds, target escape speeds, targeting accuracy, and target distances, determining the final probability of successful intersection between the projectile and target.
From an operational perspective, the output of the platform-level controller model is a third-order ESG, conducting platform-level “autonomous” dispatching aimed at projectile-target intersection, matching control command parameters, rapidly adjusting the link combinations and task sequencing of various weapon units (such as drone swarms and munition clusters) during the engagement process, achieving autonomous perception, autonomous decision-making, and autonomous strikes, with strong associations among weapon units in information flow relationships and tight coupling in resource occupation.
2.4 Functional Model Design
2.4.1 “Search and Destroy”
“Search and destroy” is suitable for targets whose activity areas are roughly determined but not yet discovered through reconnaissance. It requires pre-deployment of forces and mobilization of various reconnaissance resources. Once targets are identified and located, launch commands are quickly generated, and strike tasks are swiftly executed.
The functional model is “CF2CF3,” which constructs the initial kill network (Control), discovers (Find), fixes (Fix), dynamically constructs the kill chain (Control), launches (Fire), strikes (Finish), and assesses (Feedback), as illustrated in Figure 4.
This model sets two decision points: 1) Confirming the kill network plan when generating the first-order ESG after receiving the target list; 2) Confirming the firepower plan and launch commands when generating the second-order ESG after locking onto the target.
2.4.2 “Call for Fire”
“Call for fire” is suitable for rapidly responding to emergent targets (such as unplanned high-value targets) driven by targeting, quickly planning, generating launch commands, and executing strike tasks.
The functional model is “FCF3,” which includes fixation (Fix), rapid construction of the kill chain (Control), launch (Fire), strike (Finish), and assessment (Feedback), as illustrated in Figure 5.
This model sets one decision point, confirming the firepower plan and launch commands when generating the second-order ESG after receiving targeting information.
2.4.3 “Authorize Strike”
“Authorize strike” applies to scenarios where specific strike targets are continuously tracked and aimed (tracking and aiming) for timely or command-driven strikes. Commanders pre-authorize reconnaissance systems and weapon platforms to operate autonomously according to engagement control directives, tracking and locking onto targets before guiding weapon systems to strike.
The functional model is “CF2CFCF2,” which constructs the initial kill network (Control), discovers (Find), fixes (Fix), dynamically generates the kill chain (Control), launches (Fire), pushes targeting information online and generates collaborative strategies (Control), strikes (Finish), and assesses (Feedback), as illustrated in Figure 6.
This model sets three decision points: 1) Confirming the kill network plan when generating the first-order ESG after receiving the target list and confirming authorization for autonomous collaborative nodes within the kill network; 2) Confirming adjustments to control parameters for each node element of the kill chain when generating the second-order ESG driven by battlefield event changes; 3) During collaborative strikes by multiple weapon platforms, generating the third-order ESG by the autonomous engagement control system and issuing parameters for collaborative strike control.
2.5 Main Characteristics of the Construction Paradigm
Compared to the traditional F2T2EA kill chain paradigm, the CF5 paradigm has the following characteristics:
1) Optimized link composition. The tracking and targeting stages are removed, replaced by the discovery and fixation stages. Once the target is located, the attack phase begins, streamlining the process and facilitating compatibility across various operational domains. Under this process, once intelligence, surveillance, and reconnaissance networks are established and operational, connected to each weapon system, any target entering the network will be detected by one or multiple ISR systems, which is the “discovery” part of CF5. Subsequently, these ISR systems will locate the target and form “fixation” information shared among all weapons in the network. After this, attacks on the target can be executed.
2) Flexible execution order. No longer emphasizing sequential execution, stages can even be nested, satisfying the adaptability and extensibility requirements of the kill network. Traditional kill chains, such as F2T2EA, follow a sequential execution process, while in CF5, only the discovery-fixation-strike-assessment four stages maintain a fixed order, with the launch stage dynamically forming different closure modes based on various engagement control modes. Moreover, for medium-to-long-range precision strikes, both pre-launch and post-launch stages can embed corresponding CF5 stages, effectively addressing the unification and connection of kill chain closure control models before and after weapon launches.
3) Emphasis on engagement control. A new engagement control stage C is added, introducing the concept of decision control points, allowing various decision control points to be inserted at different positions within the F5 cycle. This can provide pre-authorized control, command control within the loop, and status monitoring on the loop among various control modes, emphasizing machine autonomy while acknowledging the need for human intervention in kill chain closure when necessary. This addresses the challenges of integrating multi-modal operations of new and old weapons, as well as how human authority can intervene, achieving efficient human-machine collaboration and improving the accuracy and efficiency of kill chain closure.
4) Focus on practical implementation. Building on the foundational paradigm, functional models are introduced for typical strike styles, ensuring stronger guidance while maintaining flexibility; the concept of three-order ESG is introduced to ensure practical implementation across strategic, operational, tactical, and combat levels, and across system, platform, and layer levels.
3
Design of Kill Network Integration Architecture
3.1 Overall Architecture of System Integration
Essentially, the kill network is a typical application supported by network information systems, which serve as the nurturing ground for the operational concept of kill networks. The integration of kill networks represents an integration of system capabilities, fully decoupling and widely distributing operational resources and element nodes on the basis of traditional interconnectivity, and conducting full coupling based on an open system architecture to form overall capabilities.
The integration of the kill network system can adopt an overall architecture of shared cloud service environment + distributed element nodes. The overall architecture of the kill network system integration is illustrated in Figure 7. Here, the shared cloud service environment provides ubiquitous interconnectivity and resilient resistance to destruction, a flat network entry, and a battlefield resource pool that is shared across domains, enabling real-time optimization of resources and on-demand construction of system capabilities, as well as core functional applications combining human-machine interaction and cloud-edge collaboration; sensor, weapon, platform, and business element systems serve as distributed element nodes, deployed in a decentralized manner and digitally integrated into the network, with resource cross-domain collaboration and efficient flexible organization conducted by the engagement control system.
In the construction of the kill network system integration, the engagement control system is the core that leads, governs, and organizes the establishment and execution of kill chains, acting as the “brain” and “central hub” of kill network operations. Engagement control is omnipresent within the kill network, serving as the “invisible hand” in the construction and operation of the kill network: Where is information processed? Where is knowledge obtained? What role does the human play in the loop? In the rapidly changing battlefield, where and how are core decisions made? The engagement control system is essentially the operating system of the kill network.
This architecture has the following characteristics: 1) It adopts an open system architecture, changing the previous binding architectures of weapon platforms and systems, command levels and systems, software and hardware, allowing for more flexible access to resource nodes and enabling agile and low-cost upgrades of applications; 2) The engagement control system applications are integrated into a cloud-based system, allowing commanders to access and generate ESG from anywhere, supporting distributed execution of reconnaissance or firepower plans; 3) Through the engagement control app, traditional intelligence, command control, and planning applications are integrated, enhancing the automation of system operations, reducing the human collaboration costs required to generate ESG, and improving the speed of kill chain closure.
3.2 Architecture of the Engagement Control System
The engagement control system is based on the platform supported by system capabilities, with resource basemaps and battlefield variables as inputs, event bus and artificial intelligence (AI) management as the engine, a three-level dispatching system as the core, and engagement sequence groups as outputs, employing a human-machine combination approach to orderly mobilize sensor nodes, communication nodes, command control nodes, and firepower strike nodes, achieving dynamic construction of the kill network, optimal organization of kill chains, and rapid adjustments.
3.3 Core Functions of Engagement Control
The core of the engagement control system includes the following five functions:
1) Combat resource management. This function is responsible for providing combat resource data for three-level dispatching, forming the basis for developing kill network plans and generating accurate ESG. It mainly includes: a) Standardized entry of resources into the network. Integrating sensor, firepower, and other resource nodes into the network unit module as IoT gateways for accessing the shared cloud service environment, aggregating, standardizing, and forwarding real-time data generated by resource nodes. b) Digital capability modeling of resources. In the shared cloud service environment, associating and organizing corresponding entity resource capability attributes, real-time statuses, and task sequence data to construct digital twins of various operational resources. c) Resource status sharing and control, allowing commanders to safely view and manage available combat resources, including resource status subscription queries and manual settings for resource access permissions, providing a capability basemap for three-level dispatching.
2) Battlefield variable management. This function is responsible for providing real-time data on changes such as “enemy and friendly situation” and “task adjustments/plan execution,” serving as inputs for online real-time adjustments of the kill network. It mainly includes: a) Task management, used to receive, process, and generate tasks, mainly producing variables for task generation, changes, and terminations; b) Target management, used to manage dynamic targets, including the full cycle of discovery, identification, fixation, and effect assessment of potential and strike targets, supporting automatic analysis of target threats and completing priority sorting for target strikes, automatically extracting points that constitute locked states to generate target indication information, mainly producing target status change variables; c) Resource management, used to manage resource statuses, triggering events for changes in resource availability; d) Battlefield management, associating real-time environmental data such as battlefield weather, electromagnetic conditions, navigation, and airspace, mainly producing variables for battlefield environmental threats, airspace conflicts, and electromagnetic suppression; e) Monitoring of kill chain operations, used to manage ESG sequence group data, monitoring the operation of each kill chain under CF5, providing task monitoring and execution status tracking, producing variables for deviations in ESG program execution.
3) Event bus engine. This function is responsible for processing changes in events across the all-domain battlefield space, providing event registration, distribution, association, integration, management, and handling, which are key to achieving data sharing within the engagement control system and integrating various applications. It mainly includes: a) Event generation, calculating the matching situation of variables with constraints based on various battlefield variables, triggering the generation of corresponding events when variables constitute conditions for pending processing; b) Event flow, providing event registration, subscription, and distribution functions, supporting three-level dispatching and other applications to subscribe to needed event sources on demand; c) Event handling, invoking event handling rules, matching the timing with applications that handle the event, and transferring event information to the respective applications for processing.
4) Rule management engine. This function is responsible for providing and maintaining all-domain battlefield engagement rules, which are core to determining the performance of the kill network. The formation of rules can arise from various avenues: a) The system employs machine learning techniques to extensively learn various international warfare regulations and operational directives, forming structured rule descriptions; b) Operational personnel manually input based on experience and knowledge; c) The system continually learns from historical cases, optimizing algorithms for target system sorting, troop allocation, event alert handling recommendations, etc. The rules include two categories: a) Event handling rules, including rules for handling task changes, target changes, resource statuses, and battlefield environmental changes; b) Business rules, including rules for setting decision points, intelligence processing rules, rapid planning rules, command generation rules, and weapon usage rules. From a broad perspective, the content of rules encompasses knowledge, data, and regulatory directives, such as weapon damage knowledge, target knowledge, and historical case data.
5) Key technologies for three-level dispatching. a) The challenge of system-level dispatching lies in predicting and responding to changes in engagement situations. In practical applications, accurately estimating the scale of targets in a confrontation process and the enemy-friendly force consumption ratio is challenging, necessitating breakthroughs in task decomposition analysis technology oriented towards command intent understanding, time-sensitive situation cognition prediction technology based on data mining, and kill network construction technology based on neural networks; b) The challenge of system-level dispatching lies in real-time responses to high-concurrency targeting, aiming to generate multiple strike paths for the same target and seek optimal path solutions within limited time, necessitating breakthroughs in resource twin modeling technology based on operational capabilities and kill chain planning technology based on integrated firepower; c) The challenge of platform-level dispatching lies in controlling parameters and issuing commands to flying platforms within extremely short control cycles, ensuring control outputs effectively address current measurement errors rather than exceeding adjustment ranges, necessitating breakthroughs in real-time threat assessment technology for aerial engagements and high-speed platform collaborative control guidance technology.
4
Conclusion
The concept of the kill chain and its paradigm shift originated from the evolution of warfare forms, rooted in the development of information technology, while simultaneously driving profound changes and transformations in the infrastructure of the electronic information field. With the widespread application of emerging technologies represented by real-time sensor-weapon connections, drones, long-range precision weapons, sensor networks, and data processing, the methods, scopes, and scales of modern warfare are undergoing significant changes. The construction of larger-scale kill networks (increasing the number of kill chains that can be closed simultaneously), faster (shortening response times to dynamic target strikes), and more resilient (enhancing survival capabilities under strong adversarial conditions) is an important direction for future development. Furthermore, driven by technologies such as big data and artificial intelligence, the traditional command, control, communication, computer, intelligence, surveillance, and reconnaissance (C4ISR) architecture is gradually evolving into a sensor, network, and artificial intelligence (SNAI) architecture. Therefore, strengthening research on the “AI + kill chain” technology path and promoting the rapid closure and resilient reconstruction of kill chains in intelligent spaces is not only an important research direction for constructing kill networks but also a crucial lever for driving the intelligent transformation of the cyber information system in the future.
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