How to Build Random Key Pre-distribution Schemes with Self-Healing for Multiphase WSNs

Miyaji, Atsuko; Omote, Kazumasa

doi:10.1109/aina.2013.68

Cited by 10 publications

(13 citation statements)

References 11 publications

(18 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We can easily confirm that Equation is the extended form of P R o K by . Figure shows a comparison of the analytical result ( P S − R K P ) with simulation result ( R S ) in S‐RKP. We found that the resiliency (1 − P S − R K P ) = 82.3 % by Figure holds when δ = 100.…”

Section: Security Evaluation By Analytical Modelsupporting

confidence: 61%

“…We evaluate this scheme employing the modeling method of RoK, that is, we estimate a constant value and replace it by j . Then, the ratio P S ‐ R K P in is defined by

P_{S - RKP} = \sum_{i = 1}^{m} {((), 1 - \prod_{r = 1}^{E_{c}^{′′}} ((), 1 - \frac{m}{P + (r - 1) δ}))}^{i} \frac{p_{i, S - RKP}}{1 - p_{0, S - RKP}},

where

E_{c}^{′′} = P / 2 δ

. We can easily confirm that Equation is the extended form of P R o K by .…”

Section: Security Evaluation By Analytical Modelmentioning

confidence: 77%

“…We found that the resiliency (1 − R R P o K ) = 99.4 % by Figure holds, where

E_{c}^{'} = 3

and c = 10. We see that the resiliency is much higher than other two schemes by Table . S‐RKP : We can measure the resiliency by the following analytical model in . The idea of modeling the RoK scheme is to replace the generation j by the constant value.…”

Section: Security Evaluation By Analytical Modelmentioning

confidence: 99%

“…A private sub‐key is not directly stored in each sensor node by applying the polynomial‐based scheme to the RoK scheme . As a result, RPoK is suitable in situations where higher resiliency is required such as a more hostile area. S‐RKP is a simple RKP scheme with self‐healing for WSNs, without lightweight operations such as a hash function. S‐RKP can enhance the RKP with self‐healing property, without changing the functions of sensors.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Self‐healing wireless sensor networks

Miyaji

Omote

2015

Concurrency and Computation

View full text Add to dashboard Cite

SUMMARYAvailability is very important for long-term use of wireless sensor networks (WSNs), assuming the presence of an attacker. It is thus important to achieve secure communication among WSNs even if some sensor nodes are compromised. Self-healing WSNs possess the feature that a network automatically self-heals after nodecapture attacks in order to achieve availability. The self-healing means that the ratio of compromised links decreases with time, even if the attacker corrupts sensor nodes of the network. In this paper, three kinds of self-healing schemes for WSNs are described, a polynomial-based self-healing scheme, a simple random key pre-distribution scheme with self-healing, and a proactive co-operative link self-healing scheme. Our contributions are the self-healing schemes with security evaluation, in which we conduct analytical evaluation and a simulation experiment of our schemes, and results obtained from both analysis and simulations indicate that our schemes are effective in self-healing. Furthermore, comparing three schemes, we clarify each difference and discuss optimal scheme under each different environments.

show abstract

Section: Security Evaluation By Analytical Modelsupporting

confidence: 61%

“…We evaluate this scheme employing the modeling method of RoK, that is, we estimate a constant value and replace it by j . Then, the ratio P S ‐ R K P in is defined by

P_{S - RKP} = \sum_{i = 1}^{m} {((), 1 - \prod_{r = 1}^{E_{c}^{′′}} ((), 1 - \frac{m}{P + (r - 1) δ}))}^{i} \frac{p_{i, S - RKP}}{1 - p_{0, S - RKP}},

where

E_{c}^{′′} = P / 2 δ

. We can easily confirm that Equation is the extended form of P R o K by .…”

Section: Security Evaluation By Analytical Modelmentioning

confidence: 77%

“…We found that the resiliency (1 − R R P o K ) = 99.4 % by Figure holds, where

E_{c}^{'} = 3

Section: Security Evaluation By Analytical Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Self‐healing wireless sensor networks

Miyaji

Omote

2015

Concurrency and Computation

View full text Add to dashboard Cite

show abstract

“…The proposed key scheme improves the network's ability to spring back to normal operation. Also, round synchronisation is eliminated in the network (Miyaji and Omote, 2013).…”

Section: Related Workmentioning

confidence: 99%

Malicious node detection through run time self-healing algorithm in WSN

Bapu¹,

Gowd

2019

IJAIP

View full text Add to dashboard Cite

Wireless sensor network possess a large number of randomly deployed nodes. These nodes configure themselves to form a network. WSNs' major role is to monitor the environment, collect the data and communicate the data to the base node. The originality of the data communicated by the WSN nodes is an important criterion to avoid failure in the network. So, self-healing techniques are implemented to overcome the losses of data in routing due to misbehaving nodes. However, major protocols designed for self-healing are not energy constrained and not suitable for battery powered network. In this paper, we propose a new run-time self-healing algorithm which possesses individual monitoring node capable of scanning the data and evaluate the stability of the nodes to ensure proper communication in the network. The proposed method is compared with self-healing hybrid sensor network architecture (SASHA) and error correction code (ECC) algorithm to validate the proposed system efficiency. The simulation results show that the proposed algorithm improves efficiency by 86%.

show abstract

AdaPtive and rObust Key pre‐distribution for multi‐phase IoT networks

Messai

2024

Int J Communication

View full text Add to dashboard Cite

SummaryInternet of Things (IoT) networks continue to be deployed and play a crucial role in our daily life. Thus, ensuring their security is of utmost importance. This necessitates the use of cryptographic materials to maintain the confidentiality of exchanged data between IoT devices (or sensor nodes). The key component of these cryptographic materials is the encryption and decryption keys. In resource‐constrained networks like sensor and IoT networks, employing symmetric pairwise keys offers a trade‐off between resource saving and security. However, symmetric cryptosystems suffer from node compromising attacks. In addition, such networks often require the post‐deployment of new IoT devices either periodically or based on specific use cases leading to a multi‐phase IoT networks. So, key establishment is required to secure newly added node communications. This paper presents an adaPtive and rObust Key pre‐distribution (POK) that enables key establishment between deployed nodes. POK enhances the generation and pre‐loading of keys in sensor nodes. The fundamental concept of POK involves pre‐loading newly added IoT or sensor nodes with pairwise keys computed using a hash function and taking into account the expected number of future post‐deployments. Through a comparative analysis with related works, POK minimizes communication overhead, eliminates the need for time synchronization, and offers an energy‐efficient scheme. Furthermore, POK offers a resilience to node compromising attack by the self‐healing property, where compromised nodes have a limited effect on the network, and newly deployed nodes remain unaffected.

show abstract

How to Build Random Key Pre-distribution Schemes with Self-Healing for Multiphase WSNs

Cited by 10 publications

References 11 publications

Self‐healing wireless sensor networks

Self‐healing wireless sensor networks

Malicious node detection through run time self-healing algorithm in WSN

AdaPtive and rObust Key pre‐distribution for multi‐phase IoT networks

Contact Info

Product

Resources

About