Key Pool Research Articles

A Dynamic-Routing Algorithm Based on a Virtual Quantum Key Distribution Network

Quantum key distribution (QKD) is an encrypted communication technique based on the principles of quantum mechanics that ensures communication security by exploiting the properties of quantum states. Currently, the transmission efficiency of the QKD system is low. Trusted relay technology is used to solve this problem and achieve long-distance transmission. However, trusted relaying alone cannot decrypt the issues of poor link stability and the low utilization of key resources. To further optimize the system performance, we propose a dynamic routing algorithm. One of the improvement schemes includes the following: firstly, an adjustable-size quantum key pool (QKP) is designed, which can dynamically adjust the size of the refreshing pool according to the actual demand. Secondly, the utilization of key resources is improved by using the residual quantum key model to dynamically obtain the remaining key amount in the QKP and set the key amount threshold. We calculate the link-blocking probability and track the blocking intensity and blocking entry by combining the Poisson process, thus realizing the evaluation of the link stability. Finally, the number of remaining keys in the QKP and the link-blocking probability combine with the random wandering model as the basis of the route selection for the QKD dynamic routing algorithm to achieve efficient key path selection. We validated the algorithm by comparing it with other algorithms on the Mininet simulation platform, and the algorithm proved to have a better performance in terms of congestion avoidance, delay reduction, and improved QKD efficiency. This scheme provides a novel and efficient way to solve the problems in existing QKD systems. It effectively improves the transmission efficiency and strengthens the system’s security by dynamically obtaining the critical volume, accurately evaluating the link state, and selecting the optimal critical path.

A Rubik's Cube Cryptosystem-based Authentication and Session Key Generation Model Driven in Blockchain Environment for IoT Security

Over the past decade, IoT has gained huge momentum in terms of technological exploration, integration, and its various applications even after having a resource-bound architecture. It is challenging to run any high-end security protocol(s) on Edge devices. These devices are highly vulnerable toward numerous cyber-attacks. IoT network nodes need peer-to-peer security, which is possible if there exists proper mutual authentication among network devices. A secure session key needs to be established among source and destination nodes before sending the sensitive data. To generate these session keys, a strong cryptosystem is required to share parameters securely over a wireless network. In this article, we utilize a Rubik's cube puzzle-based cryptosystem to exchange parameters among peers and generate session key(s). Blockchain technology is incorporated in the proposed model to provide anonymity of token transactions, on the basis of which the network devices exchange services. A session key pool randomizer is used to avoid network probabilistic attacks. Our hybrid model is capable of generating secure session keys that can be used for mutual authentication and reliable data transferring tasks. Cyber-attacks resistance and performance results were verified using standard tools, which gave industry level promising results in terms of efficiency, light weightiness, and practical applications.

Cost-Optimization-Based Quantum Key Distribution over Quantum Key Pool Optical Networks

The Measurement-Device-Independent-Quantum Key Distribution (MDI-QKD) has the advantage of extending the secure transmission distances. The MDI-QKD combined with the Hybrid-Trusted and Untrusted Relay (HTUR) is used to deploy large-scale QKD networks, which effectively saves deployment cost. We propose an improved scheme for the QKD network architecture and cost analysis, which simplifies the number of QKD transmitters and incorporates the quantum key pool (QKP) in the QKD network. We developed a novel Hybrid-QKD-Network-Cost (HQNC) heuristic algorithm to solve the cost optimization problem. Simulations verified that the scheme in this paper could save the cost by over 50 percent and 90 percent, respectively.

Highly Secured Hybrid Image Steganography with an Improved Key Generation and Exchange for One-Time-Pad Encryption Method

Steganography is a subject of study that has been used to hide information throughout history. In cryptology science, the information to be hidden is encrypted. Both study subjects are widely used in information security and protection. In our study, digital image steganography, which is one of the application areas of steganography, was developed and applied to hide text in the selected images. While doing this, the low bands that will hide the data using the discrete Haar wavelet transform of the images obtained first. The text to be hidden is encrypted with the one-time-pad algorithm. The key used for the encryption is transmitted to the receiver using a transmission layer based on a Highly Secured Information Exchange Algorithm. The algorithms use a randomly generated key pool maintained by both the transmitter and the receiver. A key is selected from the pool randomly by generating a random key start point for every message. The pool size and the randomness are critical factors in guaranteeing no key repetition, which is a requirement for a one-time-pad. The ciphertext and the key starting point indicator are hidden in the low bands of the pictures by utilizing the least significant bit method. The optimal pixel adjustment process was applied to the pre-stego-images, this resulted in an improvement in the results. The results obtained in this study are compared against the pre-optimal pixel adjustment process results and the results obtained through peer studies. The test results show that the proposed method outperformed all the methods in terms of peak signal-to-noise ratio, structural similarity index metric, mean absolute error, mean consequential error and the encryption key security.

Microplastics alter soil enzyme activities and microbial community structure without negatively affecting plant growth in an agroecosystem

Despite the enormous benefits that plastics bring to our daily lives, plastics accumulate in the environment, especially microplastics (MPs; defined as particles <5 mm), which can cause many problems and potential loss of ecosystem services. Current research has shown the significant impact of MPs on aquatic systems, but little is known about their effect on terrestrial systems, especially within agroecosystems. Here, we investigated the effect of MPs types (PS, PE and PVC) on plant growth, soil enzyme activities, and microbial communities. MPs had a positive, type-dependent influence on plant growth affecting both above and below-ground productivity. MPs, especially PVC increased dry weights (+69.51 and + 164.62), and root length (+54.81) relative to control. Although the activity of β-glucosidase, alkaline phosphatase, cellobiohydrolase, leucine-aminopeptidase, and dehydrogenase was suppressed by MPs except urease activity which was enhanced by MPs addition. The type of MPs in soil significantly altered C flow through the soil-plant system, indicating that MPs adversely affect many C-dependent soil functions. However, MPs (especially PVC) enhanced microbial biomass carbon (+14.88%) and altered the structure and metabolic status of the microbial community. MPs addition (especially PVC) greatly enhanced soil microbial structure (+29.59%; indicated by PLFAs) compared to control. Here we provide evidence that MPs can have significant effects on key pools and fluxes within the terrestrial C cycle, with responses being MPs type-dependent. Therefore, we concluded that MPs in soil are not benign and every step should be taken to restrict their access to the soil-plant system and their potential to transfer into the food chain.

New key management scheme based on pool-hash for WSN and IoT

The Internet of Things (IoT) brings together the applications linking many devices to the Internet to make the environment more “smart”. Uses vary from the human scale, from housing (Smart Home) to that of the city (Smart Cities), transport and industry. Wireless sensor networks (WSNs), which are a sub-part of the IoT, have attracted a lot of interest over lasts years in security to ensure the integrity, the authenticity and the data confidentiality. Due to the deployment of nodes in remote areas, the solution brought to the wireless sensor network to increase the information security consists to protect the messages exchanged between nodes. In the paper, we propose a new key management protocol called the Key management scheme based on pool-hash, for the establishment of new key types. We present the modification of the proposed scheme to that of the basic scheme by detailing the different phases of key management. Modification exposes a new key pool contains original keys and other hashed admit the same identities thus new session keys transmitted between sensors nodes are defined during the discovery and path key phases. Then, we specify and formalize this protocol using a mathematical concept to model the probability of connectivity and resilience against node capture. The experimental results prove that the proposed scheme is adapted to the WSN applications in terms of connectivity and resiliency.

A secure model against mobile sink replication attacks in unattended sensor networks

Unattended wireless sensor networks (UWSNs), in which mobile sinks (MSs) are responsible for the data collection, and which are vulnerable to multiple attacks. For example, the adversaries can initiate MS replication attack after compromising a large number of sensor nodes (SNs). To resist such attacks, some scholars have proposed some schemes. In these schemes, it is assumed that MSs are equipped with tamper resistance hardware, so they are pre-distributed most of keys of a key pool for achieving authentication with SNs. However, in outdoor and even sensitive areas, tamper-resistant hardware is not always absolutely safe. Once MSs are compromised, networks become insecure. In this paper, we propose a secure model. The model contains three types of nodes, namely SNs, MSs, and a base station (BS). MSs are responsible for collecting the data encrypted by SNs and forwarding it to BS; BS is responsible for decrypting and analyzing the collected data. During the data collection process, an MS can collect an SN's data only after being authenticated by the SN using the pre-distribution key information. But it cannot decrypt the collected data. In this model, the adversaries can induce a new type of false data injection attack. In the attack, the replicated MSs impersonate uncompromised SNs to send false data to BS by using the compromised key information. If BS accepts a large amount of false data, it will make a wrong judgment. Analysis and simulation show that the proposed model has excellent resistance against MS replication attacks and false data injection attacks by setting appropriate parameter values.

Digital Twins Based on Quantum Networking

This work aims to improve the communication security of the industrial Internet of Things (IIoT) based on digital twins (DTs). The related technologies of quantum communication are introduced to improve network communication. Firstly, the key DTs technologies in the construction of IIoT are expounded. Also, the characteristics of quantum communication are analyzed. Secondly, a channel encryption scheme based on quantum communication is proposed to ensure the communication security of IIoT. The scheme uses the five-particle entanglement state and two-particle bell state as entanglement channels to realize two-particle quantum teleportation. Finally, an Adaptive Key Residue algorithm is proposed based on the quantum key distribution mechanism. The algorithm verification suggests that the success rate of service distribution decreases with the increase in network load. When the service load reaches 1000, the Adaptive Key Residue algorithm can maintain a success rate of service distribution in the network higher than 0.6. Besides, the success rate of service distribution increases with the growth of the total key generation rate V and the key pool capacity C. The research results reported here are of great significance for realizing the secure communication of IIoT systems based on digital twins to ensure the effective operation of network communication and the secure transmission of data.

Secret-Key Provisioning With Collaborative Routing in Partially-Trusted-Relay-based Quantum-Key-Distribution-Secured Optical Networks

Quantum Key Distribution (QKD) is a promising technology that provides proven unconditional security based on fundamentals of quantum physics, especially for point-to-point communications. It could be applied in large-scale optical networks for long-distance key provisioning mainly by three relaying methods: quantum-repeater-based QKD, trusted-relay-based QKD, and measurement-device-independent QKD (MDI-QKD). However, quantum-repeater-based QKD is still under study because of the immature technologies such as the preliminary quantum memory. The trusted-relay-based QKD is vulnerable since insecurity of non-ideal single-photon sources and detectors cannot be ignored in practical applications. On the other hand, for MDI-QKD, there exists a limitation on its key rate under long-distance communications. According to these limitations, embedding protocols like MDI-QKD into the existing trusted-relay-based QKD secured optical networks (QKD-ON) with usage of untrusted relays is a promising key-provisioning scheme. In this paper, we study such partially-trusted relay scenarios and focus on its routing of keys in different kinds of typical network topologies. A partially-trusted-relay-based QKD method is described, which can allow a pair of optical nodes sharing secret keys under the coexistence of trusted relays and untrusted relays. The secret-key provisioning with collaborative routing ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SKP-CR</i> ) algorithm is proposed to search for the optimal key-relay routing path. We perform the simulations with different proportion of trusted relays versus untrusted relays, initial secret keys in the quantum key pools (QKPs), and traffic load. The simulations verify that the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SKP-CR</i> algorithm can significantly outperform the conventional trusted-relay-based scheme in terms of key-distribution success rate with an improvement of up to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">62%</i> with a mesh topology.

A novel privacy-preserving multi-level aggregate signcryption and query scheme for Smart Grid via mobile fog computing

With the vigorous development of edge computing, edge devices are more and more powerful and widely deployed. Mobile fog computing-based Smart Grid emerges as the times require and attracts much attention, by combining Smart Grid and mobile fog computing. Nonetheless, user privacy is also facing new challenges, which are caused by mobility. Particularly the key management problem when multiple users apply for key frequently. For the purpose of solving this problem, this paper proposes a novel privacy-preserving multi-level aggregate signcryption and query scheme for Smart Grid with mobile fog computing and quantum key pool. Firstly, we develop a multi-level and dynamic privacy-preserving aggregate signcryption method without trusted authority, including space-based data aggregation and time-based data aggregation. To enhance the security of key management, we introduce quantum key pool to fast distribute the keys. Secondly, we implement a data query and share method based on proxy re-encryption. It not only supports users to query historical data and bills, but also realizes secure data sharing with other third parties. Ultimately, we design formal security analysis and digital simulation experiments. The analysis results show that the proposed scheme can achieve the characteristics of secure, high efficiency, lightweight and robustness. In the background of the increasingly wide application of quantum technology, we hope this work is a trigger for other scholars and institutions in the hybrid application of quantum and classical technology.

Connectivity invariant lightweight resiliency improvement strategies for CRT-subset scheme

It has been found in the literature of key management for IoT devices that most of the schemes do not consider the attacking behavior of the adversary. Considering the effect of adversarial attacks on system nodes, we observe that when an adversary captures a node, it can read all the secret information from the memory of the node, resulting a partial disclosure of key pool and exposes a part of other node’s keyrings. Thereby, usage of these links that are made secure by these keys is no longer permitted. The situation worsens with the compromise of more nodes. So, it becomes important to study the robustness of a system against such attacks. In this regard, it is important to define a parameter that measures the security of sensor networks in an adversarial situation. Resiliency is one of such important parameters. Keeping the connectivity property intact, this paper presents a black-box approach to improve the resiliency of a class of lightweight combinatorial subset schemes, known as CRT-Subset schemes. We have developed unidirectional hash chains for CRT-Subset (HC(CRT-Subset)) by using key doublets through the use of a hash chaining mechanism. The idea extends to a key triplet to manufacture the bidirectional hash chains for CRT-Subset (2HC(CRT-Subset)) scheme. These ideas are explained through four Algorithms. Given the number of nodes required for a system to be implemented for practical purposes, our algorithms are capable of finding suitable parameters to efficiently construct the key rings for future cryptographic communications. They also provide efficient mechanisms to find common keys between two nodes. Furthermore, we have shown that both of our proposed methods are more resilient than the vast majority of existing schemes. Schematic analyses and comparisons exhibit the improvement achieved and thus ensure the practicality in (distributed) deployment for large (low-cost) networks. We observe that in a multi-key scenario, like our proposed resiliency improved variants of CRT-Subset schemes, the standard resiliency measure, fail(s), does not cover the full picture. So, we additionally introduce a new security parameter Ts to measure the robustness of a network. It is mathematically a challenging problem to calculate the exact values of Ts as well as fail(s). We compute a bound of Ts for CRT-Subset and find the exact mathematical expression of fail(s) and Ts for the CRT-KPS scheme. In addition, we come up with a compact expression of T1 for the CRT-Subset Scheme.

Episode of Dual Neural Genetic Firefly (DNGF) Transmission Key Generation in New Normal Mode of COVID-19 Second Wave Telepsychiatry

The volume of E-commerce transactions had accelerated on huge scale due to COVID-19. Telemedicine comes under the segment of E-commerce, where the patients can get their treatments from isolates. Patients’ information security is a basic challenge in this COVID-19 telemedicine segment. The majority of the non-obtrusive and non-emergency patients are encouraged and treated distantly from their secludes without the inclusion of COVID-19 transmission. Anxiety, depressive disorders, stress, dementia, mood disorder, OCD, aggression, etc. are the critical mental challenges that have abruptly occurred during this COVID period. The present work focused on “New Normal Mode” of COVID-19 telepsychiatry so that the patients’ mental illness can be treated remotely in a secure way. An episode of dual neural-genetic firefly (DNGF) has been proposed on COVID-19 "New Normal Mode" 2nd wave telepsychiatry. The pool of transmission keys was generated with the help of firefly algorithm, neural perceptron, and genetic operations. Besides these, the proposed DNGF keys are effective to be used for different online psychiatric transactions. The objectivity of this paper is to generate a robust pool of transmission keys in order to nullify different types of intruding. It has effectively cleared Avalanche test and Strict Avalanche test. The outcome of parameterized functional security test has been recorded with adequacy. These were: 0.327933, 0.350467, 0.332533, 0.317867, and 0.350267 on the generated pool of DNGF. The correlation coefficient between the key generation time and parameterized functional security has been found to be r_{GT,FS} = - 0.53404. Distinctive mathematical arranged examinations were directed on the proposed key pool. It has shown better reasonability on the part of the COVID-19 2nd wave telepsychiatry, which is a component of E-commerce.

DDKA-QKDN: Dynamic On-Demand Key Allocation Scheme for Quantum Internet of Things Secured by QKD Network.

In the era of the interconnection of all things, the security of the Internet of Things (IoT) has become a new challenge. The theoretical basis of unconditional security can be guaranteed by using quantum keys, which can form a QKD network-based security protection system of quantum Internet of Things (Q-IoT). However, due to the low generation rate of the quantum keys, the lack of a reasonable key allocation scheme can reduce the overall service quality. Therefore, this paper proposes a dynamic on-demand key allocation scheme, named DDKA-QKDN, to better meet the requirements of lightweight in the application scenario of Q-IoT and make efficient use of quantum key resources. Taking the two processes of the quantum key pool (QKP) key allocation and the QKP key supplement into account, the scheme dynamically allocates quantum keys and supplements the QKP on demand, which quantitatively weighs the quantum key quantity and security requirements of key requests in proportion. The simulation results show that the system efficiency and the ability of QKP to provide key request services are significantly improved by this scheme.

Lightweight Key Management Scheme Using Fuzzy Extractor for Wireless Mobile Sensor Network

The mature design of wireless mobile sensor network makes it to be used in vast verities of applications including from home used to the security surveillance. All such types of applications based on wireless mobile sensor network are generally using real time data, most of them are interested in real time communication directly from cluster head of cluster instead of a base station in cluster network. This would be possible if an external user allows to directly access real time data from the cluster head in cluster wireless mobile sensor network instead of accessing data from base station. But this leads to a serious security breach and degrades the performance of any security protocol available in this domain. Most existing schemes for authentication and cluster key management for external users, exchange a number of messages between cluster head and base station to allow external to access real time data from the base station instead of cluster head. This increase communication cost and delay in such real time access information. To handle this critical issue in cluster wireless mobile sensor network, we propose a lightweight authentication and key management scheme using a fuzzy extractor. In this scheme, any external user can access data directly from the cluster head of any cluster without the involvement of the base station. The proposed scheme only uses the one-way hash functions and bitwise XOR operations, apart from the fuzzy extractor method for the user biometric verification at the login phase. The presented scheme supports scalability for an increasing number of nodes using polynomials. The proposed scheme increases the life-time of the network by decreasing the key pool size.

Fatty acid dysregulation in the anterior cingulate cortex of depressed suicides with a history of child abuse

Child abuse (CA) strongly increases the lifetime risk of suffering from major depression and predicts an unfavorable course for the illness. Severe CA has been associated with a specific dysregulation of oligodendrocyte function and thinner myelin sheaths in the human anterior cingulate cortex (ACC) white matter. Given that myelin is extremely lipid-rich, it is plausible that these findings may be accompanied by a disruption of the lipid profile that composes the myelin sheath. This is important to explore since the composition of fatty acids (FA) in myelin phospholipids can influence its stability, permeability, and compactness. Therefore, the objective of this study was to quantify and compare FA concentrations in postmortem ACC white matter in the choline glycerophospholipid pool (ChoGpl), a key myelin phospholipid pool, between adult depressed suicides with a history of CA (DS-CA) matched depressed suicides without CA (DS) and healthy non-psychiatric controls (CTRL). Total lipids were extracted from 101 subjects according to the Folch method and separated into respective classes using thin-layer chromatography. FA methyl esters from the ChoGpl fraction were quantified using gas chromatography. Our analysis revealed specific effects of CA in FAs from the arachidonic acid synthesis pathway, which was further validated with RNA-sequencing data. Furthermore, the concentration of most FAs was found to decrease with age. By extending the previous molecular level findings linking CA with altered myelination in the ACC, these results provide further insights regarding white matter alterations associated with early-life adversity.

Application of CSK Encryption Algorithm in Video Synergic Command Systems

Video command and dispatch systems have become essential communication safeguard measures in circumstances of emergency rescue, epidemic prevention, and control command as, data security has become especially important. After meeting the requirements of voice and video dispatch, this paper proposes an end-to-end encryption method of multimedia information that introduces a multiple protection mechanism including selective encryption and selective integrity protection. The method has a network access authentication and service encryption workflow, which implants startup authentication and key distribution into the information control signaling procedure. This method constitutes a key pool with the three-dimensional Lorenz System, the four-dimensional Cellular Neural Network (CNN) System and the four-dimensional Chen System where the key source system and initial conditions are decided by the plaintext video frame itself. Then, this method optimizes the chaotic sequences to further enhance system security.

Multi-path-based quasi-real-time key provisioning in quantum-key-distribution enabled optical networks (QKD-ON).

With its information-theoretic security, quantum-key-distribution-enabled optical networks (QKD-ON) have become a promising candidate for future optical networks. The concept of quantum key pool (QKP) was introduced to offer an effective strategy for storing quantum keys. However, with the loss on its theoretical security due to storing these keys, balancing the storage of quantum keys and the security requirements of QKD-ONs poses a major challenge in their practical deployments. Hence, in this paper a concept of quasi-real-time key provisioning (QRT-KP) is introduced to address the tradeoff between quantum key storage and the degree of security. To satisfy the practical deployment of QRT-KP and the requirement of high-traffic flow, we propose a multi-path based QRT-KP (MP-QRT-KP) algorithm. Simulation results show that the MP-QRT-KP effectively enhances the performance of QKD-ONs in different scenarios, and it turns out that the algorithm performs better than single-path based QRT-KP (SP-QRT-KP) in terms of the success probability of key-allocation requests and key-resources utilization.

Cascading attack on trusted-relay quantum key distribution networks

Trusted relays are the main state-of-the-art way to realize quantum key distribution networks. However, it is hard to require that all nodes in the network are fully trusted. In a multipath key-transmission mechanism, the nodes can be weakly trusted because the secret key can be split into many parts and each part is transmitted to the receiver through a different path. However, if the capacity of a node’s quantum key pool is poorly designed, an attacker, Eve may eavesdrop on the communicating parties’ secret message by initiating a redirection attack. In this paper, we show that Eve can trigger a cascading collapse effect by collapsing one of the edges in the network and forcing the communication parties to transmit the message through the nodes controlled by Eve. The influence of the traffic transfer ratio and the control parameters of the edge load on the breakdown probability of the edge are analyzed using a simulation. In order to effectively defend against the cascading attack, it is important for the designer to handle the relationship between the traffic and the capacity of the quantum key pool of each node in the network.

Key-Size-Driven Wavelength Resource Sharing Scheme for QKD and the Time-Varying Data Services

Integrating quantum key distribution (QKD) into the optical network through wavelength division multiplex (WDM) is promising for establishing large-scale QKD networks. However, the existing wavelength assignment schemes for WDM-QKD network all require to reserve a dedicate waveband for quantum signals, which influences the provisioning of data services, especially when the resource is tight. In this article, considering the quantum key pool (QKP) technology in the current QKD network, we propose a flexible key-size-driven wavelength assignment (KSD-WA) scheme to recycle the wavelength fragment to transmit quantum signals. Additionally, considering the noise impacts and the limited reconfiguration operations, we propose a heuristic algorithm to optimize the fragment selection with the objective of maximizing the secure key rate in the dynamic scenario. We also design a deep reinforcement learning (DeepRL) based algorithm to automatically learn the optimization policy under different environments. The simulation results verify that comparing with the conventional fixed-band (FB) scheme, the KSD-WA scheme assisted by the proposed optimization algorithms can provide adequate keys for encryption without affecting the provisioning of coexisting data services, which improves the compatibility of QKD with the real-life optical networks.

KEYLINK: towards a more integrative soil representation for inclusion in ecosystem scale models-II: model description, implementation and testing.

New knowledge on soil structure highlights its importance for hydrology and soil organic matter (SOM) stabilization, which however remains neglected in many wide used models. We present here a new model, KEYLINK, in which soil structure is integrated with the existing concepts on SOM pools, and elements from food web models, that is, those from direct trophic interactions among soil organisms. KEYLINK is, therefore, an attempt to integrate soil functional diversity and food webs in predictions of soil carbon (C) and soil water balances. We present a selection of equations that can be used for most models as well as basic parameter intervals, for example, key pools, functional groups’ biomasses and growth rates. Parameter distributions can be determined with Bayesian calibration, and here an example is presented for food web growth rate parameters for a pine forest in Belgium. We show how these added equations can improve the functioning of the model in describing known phenomena. For this, five test cases are given as simulation examples: changing the input litter quality (recalcitrance and carbon to nitrogen ratio), excluding predators, increasing pH and changing initial soil porosity. These results overall show how KEYLINK is able to simulate the known effects of these parameters and can simulate the linked effects of biopore formation, hydrology and aggregation on soil functioning. Furthermore, the results show an important trophic cascade effect of predation on the complete C cycle with repercussions on the soil structure as ecosystem engineers are predated, and on SOM turnover when predation on fungivore and bacterivore populations are reduced. In summary, KEYLINK shows how soil functional diversity and trophic organization and their role in C and water cycling in soils should be considered in order to improve our predictions on C sequestration and C emissions from soils.