Random Key Predistribution Scheme Research Articles

Enhancing the connectivity and resiliency of random key pre-distribution schemes for wireless sensor network

Enhancing the connectivity and resiliency of random key pre-distribution schemes for wireless sensor network

Data transmission system of networked digital voice room based on Internet of Things technology

In order to solve the problem of poor transmission performance caused by data congestion in network digital language lab, its data transmission system is designed based on the technology of internet of things. In the hardware part, the main control circuit and transmission interface circuit are designed to reduce the signal reflection caused by the change of line width and angle. In the software part, the data transmission compression algorithm is designed to reduce the communication overhead. The internet of things technology is used to set data transmission nodes, and the weighted fairness data transmission protocol is set to control the energy efficiency of transmission. The random key pre-distribution scheme based on the hash key chain is used to construct the data security transmission model. The experimental results show that, compared with the data transmission system based on data mining and cloud computing, the designed system achieves the lowest word error rate and sentence error rate, and has better data transmission performance.

Key Distribution Strategy of Wireless Sensor Network Based on Multi-Hash Chain

Key management is the basis of the security mechanism for wireless sensor networks and services, and random key pre-distribution is the most effective key management mechanism at present. However, there is a potential challenge to most current random key pre-distribution strategies: it is difficult to achieve both ideal network security connectivity and network survivability. In this paper, we present a novel random key pre-distribution scheme based on the hash chain. By adjusting certain system parameters, such as the hash chain length, the number of common auxiliary nodes and the number of hash chains, a sensor node only need to preload a few of keys, making it possible to establish the pairwise key with high probability among its neighboring nodes. The proposed scheme can still maintain strong network survivability even if there are many compromised nodes. The theoretical analysis and simulation experiments show that the proposed scheme is not only effective and secure, but also scalable.

On the Minimum Node Degree and k-Connectivity in Inhomogeneous Random K-Out Graphs

Inhomogeneous random K-out graphs were recently introduced to model heterogeneous sensor networks secured by random pairwise key predistribution schemes. First, each of the n nodes is classified as type-1 (respectively, type-2) with probability 0 <; μ <; 1 (respectively, 1-μ) independently from each other. Next, each type-1 (respectively, type-2) node draws 1 arc towards a node (respectively, K <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> arcs towards K <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> distinct nodes) selected uniformly at random, and then the orientation of the arcs is ignored. It was recently established that the inhomogeneous random K-out graph is 1-connected asymptotically almost surely (a.a.s.) if and only if K <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> =ω(1). In this work, we analyze the k-connectivity of inhomogeneous random K-out graphs; i.e., with k=1, 2, <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> ⋯</sub> , the property that the network remains connected despite the removal of any k-1 nodes or links. We first establish a zero-one law for the property that the minimum node degree is at least k. In particular, we present scaling conditions on μ and K <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> such that the resulting graph has minimum degree at least k with probability approaching one (respectively, zero) constituting the one-law (respectively, zero-law), as the number of nodes gets large. We show that for k=2, 3, <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">⋯</sub> , we need to set K <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> = \frac 11-μ(logn +(k-2)loglogn + ω(1)) for the network to have a minimum node degree of at least k a.a.s. Next, we prove that having K <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sub> = \frac 11-μ(logn +(k-2)loglogn + ω(1)) also ensures that the graph is k-connected a.a.s., meaning that the zero-one laws for minimum node degree and k-connectivity coincide. We present simulation results to demonstrate the usefulness of the results in the finite node regime. The results given here indicate an interesting fact about inhomogeneous random K-out graphs, i.e., that the number of additional edges needed to go from 1-connectivity to k-connectivity with k ≥ 2 is unexpectedly larger as compared to many classical random graph models studied before.

A Full Connectable and High Scalable Key Pre-distribution Scheme Based on Combinatorial Designs for Resource-Constrained Devices in IoT Network

Considering the internet of things (IoT), end nodes such as wireless sensor network, RFID and embedded systems are used in many applications. These end nodes are known as resource-constrained devices in the IoT network. These devices have limitations such as computing and communication power, memory capacity and power. Key pre-distribution schemes (KPSs) have been introduced as a lightweight solution to key distribution in these devices. Key pre-distribution is a special type of key agreement that aims to select keys called session keys in order to establish secure communication between devices. One of these design types is the using of combinatorial designs in key pre-distribution, which is a deterministic scheme in key pre-distribution and has been considered in recent years. In this paper, by introducing a key pre-distribution scheme of this type, we stated that the model introduced in the two benchmarks of KPSs comparability had full connectivity and scalability among the designs introduced in recent years. Also, in recent years, among the combinatorial design-based key pre-distribution schemes, in order to increase resiliency as another criterion for comparing KPSs, attempts were made to include changes in combinatorial designs or they combine them with random key pre-distribution schemes and hybrid schemes were introduced that would significantly reduce the design connectivity. In this paper, using theoretical analysis and maintaining full connectivity, we showed that the strength of the proposed design was better than the similar designs while maintaining higher scalability.

$k$ -Connectivity of Inhomogeneous Random Key Graphs With Unreliable Links

We consider secure and reliable connectivity in wireless sensor networks that utilize the heterogeneous random key predistribution scheme. We model the unreliability of wireless links by an on/off channel model that induces an Erdős-Renyi graph, while the heterogeneous scheme induces an inhomogeneous random key graph. The overall network can thus be modeled by the intersection of both graphs. We present conditions (in the form of zero-one laws) on how to scale the parameters of the intersection model, so that with high probability: i) all of its nodes are connected to at least ${k}$ other nodes, i.e., the minimum node degree of the graph is no less than $ {k}$ , and ii) the graph is $ {k}$ -connected, i.e., the graph remains connected even if any $ {k} - {1}$ nodes leave the network. These results are shown to complement and generalize several previous results in the literature. We also present numerical results to support our findings in the finite-node regime. Finally, we demonstrate via simulations that our results are also useful when the on/off channel model is replaced with the more realistic disk communication model .

A Novel Technique for Improving the Security of WSN Using Random Key PreDistribution Scheme

A Novel Technique for Improving the Security of WSN Using Random Key PreDistribution Scheme

Random Cooperative Key Pre-Distribution Scheme in Wireless Sensor Networks

To cope with the security challenges brought by the popularization of wireless sensor network (WSN), a new random key pre-distribution scheme for WSNs based on the grid deployment theory of Blom mechanism is proposed. The core idea is to divide the network area where the nodes are into different types of hexagonal grids and nodes in different grids use different ways to create keys. Theoretical analysis and simulation results show that the scheme has better connectivity, local security and global security. In view of the existing storage consumption problems, a deterministic key establishment scheme is proposed based on the irregular network model. The simulation results show that the effective coding mechanism introduced optimizes the storage consumption in the network range. It also has a higher security threshold and absolute connectivity, and the enemy's ability to resist capture attacks is stronger.

Performance Evaluation of Polynomial Pool-Based Key Pre-Distribution Protocol for Wireless Sensor Network Applications

In nowadays, wireless sensor network (WSN) has been established as a leading emerging technology in the field of remote area distributed sensing due to its diverse application areas. Key pre-distribution is an important task in WSN because after the deployment of sensor nodes, their neighbors become strange to each other. To secure the communication, neighbor nodes have to generate a secret shared key, or a key-path must exist between these nodes. In this paper, we have discussed and presented various key pre-distribution protocols, namely, the polynomial pool-based key pre-distribution which is a scheme for creating pairwise keys between sensors on the foundation of a polynomial-based key pre-distribution protocol, introducing two effective instantiations: a random subset assignment key pre-distribution scheme and a grid-based key pre-distribution scheme. Other studied key pre-distribution schemes (KPDS) are Peer Intermediaries Key for Establishment (PIKE) and Group-based key pre-distribution scheme. The performances of these schemes have been assessed through the simulation of different grids under the TinyOS environment.

Key establishment scheme for wireless sensor networks based on polynomial and random key predistribution scheme

Establishing communication keys for pairs of neighbouring sensor nodes is the foundation of the security in wireless sensor networks (WSNs). However, due to the resource constraints on nodes, this task is challenging for the constrained memory, energy, and computational capabilities of sensor nodes. This paper proposes a novel key predistribution scheme based on the polynomial pool-based key predistribution scheme and random key predistribution. In the proposed scheme, parts of the preloaded information in each sensor node are the polynomial shares and the rest of the preloaded information are the keys generated by the polynomial shares preloaded in the sensor nodes. Performance analyses and comparisons with other schemes are performed in this paper. The comparison of security results confirm that the proposed scheme has better resilience against node compromising attacks when compared to previous schemes.

$k$ -Connectivity in Random $K$ -Out Graphs Intersecting Erdős-Rényi Graphs

We investigate $k$ -connectivity in secure wireless sensor networks under the random pairwise key predistribution scheme with unreliable links. When wireless communication links are modeled as independent on-off channels, this amounts to analyzing a random graph model formed by intersecting a random $K$ -out graph and an Erdős-Renyi graph. We present conditions on how to scale the parameters of this intersection model so that the resulting graph is $k$ -connected with probability approaching to one (resp. zero) as the number of nodes gets large. The resulting zero-one law is shown to improve and sharpen the previous result on the 1-connectivity of the same model. We also provide numerical results to support our analysis.

A Hybrid Approach for Path Vulnerability Matrix on Random Key Predistribution for Wireless Sensor Networks

In this paper, we address the problem of physical node capture attack from an adversarial view. In this type of attack, an adversary intelligently captures the node(s) and extracts the cryptographic information to destroy the privacy, safety and reliability of the network. We propose a novel hybrid approach for constructing the path vulnerability matrix that maximizes the attacking efficiency and lowers the resource expenditure of the adversary. The main strength of the proposed matrix lies in incorporating various criteria such as the type of application running on the nodes, capturing cost, key dominance ranking, articulation point and intersecting shortest path nodes in estimating the vulnerability. The location of the data sink is considered as a major factor in estimating the vulnerability of the nodes in the network. The proposed matrix is compared with existing attacking strategies in terms of the number of attacking rounds, energy cost and fraction of compromised traffic. Although in this paper, we have considered adversarial point of view but the proposed matrix can be extended for the defender application also. The path vulnerability matrix provides vulnerability estimation that can be used to analyze system security weakness and helps to defend against them effectively and efficiently. The performance of proposed approach has been validated with respect to average path compromise ratio, average routing path length and average route successful ratio. We have also introduced an attack resistant random key predistribution scheme based on the proposed approach and the results confirm its effectiveness in decreasing node capture impact.

Zero-One Laws for Connectivity in Inhomogeneous Random Key Graphs

We introduce a new random key predistribution scheme for securing heterogeneous wireless sensor networks. Each of the n sensors in the network is classified into r classes according to some probability distribution {\mu} = {{\mu}_1 , . . . , {\mu}_r }. Before deployment, a class-i sensor is assigned K_i cryptographic keys that are selected uniformly at random from a common pool of P keys. Once deployed, a pair of sensors can communicate securely if and only if they have a key in common. We model the communication topology of this network by a newly defined inhomogeneous random key graph. We establish scaling conditions on the parameters P and {K_1 , . . . , K_r } so that this graph i) has no isolated nodes; and ii) is connected, both with high probability. The results are given in the form of zero-one laws with the number of sensors n growing unboundedly large; critical scalings are identified and shown to coincide for both graph properties. Our results are shown to complement and improve those given by Godehardt et al. and Zhao et al. for the same model, therein referred to as the general random intersection graph.

An Improved Random Key Predistribution Scheme for Wireless Sensor Networks Using Deployment Knowledge

Key management is the basis of many security mechanisms and services in wireless sensor networks (WSN). Random key predistribution scheme is widely considered as the most practical for WSN. However, this scheme faces the challenge that it cannot achieve the ideal security connectivity and strong resilience against node capture simultaneously. To address this limitation, an improved random key predistribution scheme using deployment knowledge is proposed in this paper. Firstly, sensor nodes are divided into different groups according to their location expected. And the key pool is grouped into key pool subsets accordingly. To realize the communication between adjacent groups, the corresponding key pool subsets have a certain degree of overlapping. For all keys, there is no limitation on key reuse. Neighboring nodes sharing q common keys will establish secure link with high probability. Moreover, our scheme inherits the advantage of qcomposite random key predistribution scheme that it can maintain security even if some nodes are captured. Theoretical analysis and simulation experiments show that the improved scheme performs well on network connectivity and resilience.

An Empirical Study on Key Management Schemes of Wireless Sensor Network

The ample use of Wireless Sensor Network demands highly effective security mechanism for its sound operation in any hostile environment. The security of encrypted information greatly dependents on the rigidity of underlying Key Management techniques. Hence, key management becomes the most significant issue in case of security of Wireless Sensor Networks. The purpose of this paper is to assess most significant key management schemes of wireless sensor networks e.g. single network-wide key scheme, pairwise key establishment scheme, random key pre-distribution and Qcomposite random key pre-distribution scheme. The overall analysis is performed based on a number of criteria such as: loaded key utilization, resource consumption and rigidity against node capture. Besides, to identify the best one, a result based comparison among the schemes is also presented.

Secure Trust Based Key Management Routing Framework for Wireless Sensor Networks

Security is always a major concern in wireless sensor networks (WSNs). Several trust based routing protocols are designed that play an important role in enhancing the performance of a wireless network. However they still have some disadvantages like limited energy resources, susceptibility to physical capture, and little protection against various attacks due to insecure wireless communication channels. This paper presents a secure trust based key management (STKF) routing framework that establishes a secure trustworthy route depending upon the present and past node to node interactions. This route is then updated by isolating the malicious or compromised nodes from the route, if any, and a dedicated link is created between every pair of nodes in the selected route with the help of “q” composite random key predistribution scheme (RKPS) to ensure data delivery from source to destination. The performance of trust aware secure routing framework (TSRF) is compared with the proposed routing scheme. The results indicate that STKF provides an effective mechanism for finding out a secure route with better trustworthiness than TSRF which avoids the data dropping, thereby increasing the data delivery ratio. Also the distance required to reach the destination in the proposed protocol is less hence effectively utilizing the resources.

Random Key Pre-Distribution Scheme Based On Key Updating

Abstract A random key pre-distribution scheme based on key updating (RKKU) was proposed, which is effective in wireless sensor networks. Firstly, the base station will randomly distribute some keys, a hash function and some code slices to each node. Furthermore, the RKKU scheme compares with the information of some random key to find the same key, and computes the communication key between two sensor nodes with one-way hash function. Since the one-way hash function can ensure that the attacker cannot use the obtained communication key to decipher the source key, it affects only two nodes communicate with each other. To assure the communication security, the key updating was designed based on code segment. The analysis shows that the proposed scheme can meet the security requirement of key management, and it also has less computation cost and storage cost than the existing schemes

Toward &lt;inline-formula&gt; &lt;tex-math notation="LaTeX"&gt;$k$ &lt;/tex-math&gt;&lt;/inline-formula&gt;-Connectivity of the Random Graph Induced by a Pairwise Key Predistribution Scheme With Unreliable Links

We study the secure and reliable connectivity of wireless sensor networks. Security is assumed to be ensured by the random pairwise key predistribution scheme of Chan, Perrig, and Song, and unreliable wireless links are represented by independent on/off channels. Modeling the network by an intersection of a random $K$-out graph and an Erd\H{o}s-R\'enyi graph, we present scaling conditions (on the number of nodes, the scheme parameter $K$, and the probability of a wireless channel being on) such that the resulting graph contains no nodes with degree less than $k$ with high probability, when the number of nodes gets large. Results are given in the form of zero-one laws and are shown to improve the previous results by Ya\u{g}an and Makowski on the absence of isolated nodes (i.e., absence of nodes with degree zero). Via simulations, the established zero-one laws are shown to hold also for the property of $k$-connectivity; i.e., the property that graph remains connected despite the deletion of any $k-1$ nodes or edges.

&lt;inline-formula&gt; &lt;tex-math notation="LaTeX"&gt;$k$ &lt;/tex-math&gt;&lt;/inline-formula&gt;-Connectivity in Random Key Graphs With Unreliable Links

Random key graphs form a class of random intersection graphs and are naturally induced by the random key predistribution scheme of Eschenauer and Gligor for securing wireless sensor network (WSN) communications. Random key graphs have received much interest recently, owing in part to their wide applicability in various domains including recommender systems, social networks, secure sensor networks, clustering and classification analysis, and cryptanalysis to name a few. In this paper, we study connectivity properties of random key graphs in the presence of unreliable links. Unreliability of the edges are captured by independent Bernoulli random variables, rendering edges of the graph to be on or off independently from each other. The resulting model is an intersection of a random key graph and an Erdos-Renyi graph, and is expected to be useful in capturing various real-world networks; e.g., with secure WSN applications in mind, link unreliability can be attributed to harsh environmental conditions severely impairing transmissions. We present conditions on how to scale this model's parameters so that i) the minimum node degree in the graph is at least k, and ii) the graph is k-connected, both with high probability as the number of nodes becomes large. The results are given in the form of zeroone laws with critical thresholds identified and shown to coincide for both graph properties. These findings improve the previous results by Rybarczyk on the k-connectivity of random key graphs (with reliable links), as well as the zero-one laws by Yagan on the 1-connectivity of random key graphs with unreliable links.

Maximizing destructiveness of node capture attack in wireless sensor networks

As a special kind of attack, node capture attack in wireless sensor networks destroys the confidentiality and integrity of network traffic by physically capturing sensor nodes and extracting the cryptographic keys for eavesdropping the communications. However, previous researches pay little attention to the attacking efficiency, which leads to big attacking times and long execution time. In this paper, we propose a graph-based method for modeling the node capture attack on random key pre-distribution scheme. A full graph is constructed to specialize the compromising relationships between nodes and paths, and then the way of evaluating the destructiveness is introduced. The full graph attack (FGA) is designed to ensure the maximum destructiveness of each captured node so as to reduce the attacking times and shorten the execution time, simultaneously. To promote the performance of FGA in attacking efficiency, two optimal attacking algorithms, namely opti-graph attack (OGA) and path covering attack (PCA), are developed. Simulation results show that FGA, OGA and PCA reduce 38, 10 and 51 % attacking times, and enhance 39, 11 and 40 % attacking efficiency than traditional node capture attack methods. Moreover, they save 39, 11 and 50 % energy in compromising the networks.