To achieve security with efficiency in wireless mesh networks (WMNs) is an important issue due to its distributed nature and absence of centralised authority. Due to the absence of central authority, the authentication becomes a challenging task in WMNs. Several attacks could be easily launched in WMNs such as replay attack and impersonation attack. These types of attacks could be launched by an intruders by injecting malicious packets throughout the network among mesh entities. Therefore to overcome from such attacks, we had proposed an efficient multi-hop packet authentication protocol known as 'efficient packet authentication through Diffie-Hellman approach (EPADH)'. Through experimental results, our proposed protocol ensures packet authentication which resists the mentioned attacks and offers efficiency in terms of latency, throughput, packet delivery ratio, and memory utilisation.

Intrusion detection systems were developed to detect any suspicious traffic in the network. Conventional intrusion detection comes with its sets of limitations. The authors aimed to improve anomaly-based intrusion detection using an ensemble approach of machine learning. In this article, CICIDS2017 and CICIDS 2018 datasets have been used for implementing the proposed method. Random forest regressor is used for feature selection. Three machine learning algorithms (i.e., naïve bayes, QDA, and ID3) are selected and combined (ensembled) for their low computational cost. The ensemble algorithm results are compared with the standalone algorithms. With the ensembled method, classification accuracy of 98.3% and 95.1%, with FAR of 2% and 6.9% were achieved on CICIDS 2017 and CICIDS 2018 datasets respectively. Naïve bayes, QDA, and ID3 have classification accuracies of 82%, 84.7%, and 95.8% respectively on CICIDS 2017; 68.3%, 68.4%, and 94.4% respectively on CICIDS 2018; false alarm rates of 54.9%, 55.5%, and 20.6% respectively on CICIDS 2017; and 3.6%, 3.7%, and 7.1% respectively on CICIDS 2018.

Wireless mesh networks (WMNs) upraised as superior technology offering all aspects of services as compared to conventional networks. Due to the absence of centralised authority, WMNs suffers from both external and internal attacks, which decrease the overall performance of WMNs. In this study, the authors proposed an efficient handoff authentication protocol with privacy preservation of nonce and transfer ticket against external attacks during handoff and proposed round trip time (RTT)‐based detection protocol to resist against internal attacks in WMNs. For privacy preservation of nonce and transfer ticket, encryption of the nonce and transfer ticket during handoff authentication process was considered. For detection, the calculation of RTT and processing time to identify the malicious nodes forming wormhole link were considered. The proposed work prevents the AODV routing protocol against the wormhole attack in WMNs. The simulation of the proposed work was done using NS‐3 simulator, and the experimental results show that the performance of the proposed method prevents WMNs from both external and internal attacks.

Blinding has been one of the most effective approaches to resist power analysis attacks on asymmetric cryptosystems like RSA. Blinding is similar to masking in symmetric cryptosystems, but masking can be implemented in various ways like Boolean, affine, polynomial masking, etc. However, for asymmetric cryptosystems with modular exponentiation as a fundamental operation, arithmetic masking or simply blinding has been extremely popular. In this paper, we have presented a secured approach for modular exponentiation in RSA and CRT-RSA cryptosystems with dual blinding. Through dual blinding, we have masked both secret exponent and message twice before executing the fundamental operations. We have also injected two ineffectual instructions between the fundamental operations and blinded the intermediate results to felicitate hiding and resist simple power analysis. The implementation results shows that with a nominal penalty, RSA and CRT-RSA with dual blinding can effectively resist some popular simple power analysis and differential power analysis attacks to a significant extent.

This study presents an approach to compute randomised modular exponentiation through non‐uniform exponent partitioning. The exponent has been first partitioned into multiple parts and then shuffled by Fisher Yates method. Thereafter, every partition randomly computes modular exponentiation followed by a final modulo operation to generate the desired result. The shuffling has been introduced to randomise the execution order of individual modular exponentiation. This work is implemented in Rivest‐Shamir‐Adleman (RSA) and Chinese remainder theorem RSA as they are modular exponentiation based public key cryptosystems. The results have been analysed during decryption with different key sizes. The results indicate that the proposed work can generate non‐uniform partitions of the exponent which could not be easily anticipated even in multiple iterations. Also, the shuffling method could completely randomise the execution order of modular exponentiation operations. With non‐uniform exponent partitions and randomised modular exponentiation, the proposed work could challenge all the variances of power analysis attacks.

This article describes how differential power analysis has laid the foundations of such an attack that has challenged the security of almost all cryptosystems like DES, AES, and RSA. This non-invasive attack first extracts the power consumption details from devices embedded with cryptographic techniques and then uses these details to mount attacks on the cryptosystems to reveal the secret key. However, at times there appears multiple similar power peaks at the same points. This raises confusion in distinguishing the actual and the fake peaks named “ghost peaks.” This ghost peak problem affects the efficiency of power analysis attacks as it increases the number of power traces to be evaluated to identify the actual peak. In this article, the authors present an approach which uses the Canberra distance with Euclidean similarity to address this ghost peak problem. The proposed solution diminishes the values of all these ghost peaks, leaving only the actual peak behind that could reveal the secret key.