An efficient cryptographic technique using modified Diffie–Hellman in wireless sensor networks

Abstract

In wireless sensor networks, the sensors transfer data through radio signals to a remote base station. Sensor nodes are used to sense environmental conditions such as temperature, strain, humidity, sound, vibration, and position. Data security is a major issue in wireless sensor networks since data travel over the naturally exposed wireless channel where malicious attackers may get access to critical information. The sensors in wireless sensor networks are resource-constrained devices whereas the existing data security approaches have complex security mechanisms with high computational and response times affecting the network lifetime. Furthermore, existing systems, such as secure efficient encryption algorithm, use the Diffie–Hellman approach for key generation and exchange; however, Diffie–Hellman is highly vulnerable to the man-in-the-middle attack. This article introduces a data security approach with less computational and response times based on a modified version of Diffie–Hellman. The Diffie–Hellman has been modified to secure it against attacks by generating a hash of each value that is transmitted over the network. The proposed approach has been analyzed for security against various attacks. Furthermore, it has also been analyzed in terms of encryption/decryption time, computation time, and key generation time for different sizes of data. The comparative analysis with the existing approaches shows that the proposed approach performs better in most of the cases.

Formation control of non-identical multi-agent systems

“…In ( 6)-( 7), 𝑝 𝑖𝑗 (𝑡) is the entry of the Perron matrix 𝑃(𝑡). In (7), 𝑆 is the state matrix of the reference generator state 𝑤 𝑖 with the following assumption made on 𝑆: Assumption (A2). Eigenvalues of S lie on the unit circle.…”

“…where 𝛿 𝑖 ∈ ℝ 𝑝 (𝛿 𝑖 ≠ 𝛿 𝑗 ; 𝑖, 𝑗 ∈ ℤ 𝑁 ) is the desired output of agent 𝑖 defined on the local coordinate system and 𝑄 is the output matrix of 𝑤 𝑖 . Refer to [35] and [1], under (A3), the 𝑁 agents ( 6)- (7) (𝑦 𝑖 (𝑡) − 𝑦 𝑗 (𝑡)) = 𝜆 ∞ (𝛿 𝑖 − 𝛿 𝑗 ) for all 𝑖, 𝑗 ∈ ℤ 𝑁 . This implies that 𝜆 ∞ is the formation scaling factor.…”

An Efficient and Secure Session Key Management Scheme in Wireless Sensor Network

“…However, if the proposed scheme is validated using a mathematical model, it will be given a robust model. Ali et al [23] proposed a Diffie-Hellman-based cryptography scheme for WSN. e modified Diffie-Hellman approach is used for secure and efficient key generation, which prevents man-in-the-middle attacks.…”

A Lightweight Genetic Based Algorithm for Data Security in Wireless Body Area Networks

“…MQTT protocol strictly avoids the manin-middle attack, collision attack, and flows the encrypted data towards the server. The author Shahwar et al used Low energy adapted cluster-based protocol (LEACH) in the proposed study [3]. LEACH is lightweight and works with the cluster heads' sensors node.…”

“…WBAN comprise of small tiny sensors nodes that are placed in the human body to record patient's healthcare data. This data may relate to human ECG, body temperature, sugar level, or blood pressure [3]. There are two layers in WBAN, intra WBAN and beyond WBAN, Intra layer consists of nano sensors which are wearable to the human body and records health data.…”