In the dynamic realm of encrypted communications, traffic analysis and its classification are crucial for efficient resource utilization and network management. The prevalence of encryption technologies , The Onion Router (Tor) a globally recognized privacy-preserving network, poses a challenge for the task at hand by introducing complexity through its innovative onion routing mechanism. To overcome Tor’s limitations not only in terms of achieving better accuracy but also in performing classification in time-constrained scenarios, we propose a classification approach for Tor and non-Tor traffic classification , utilizing multiple models to enhance categorization and application identification. Leveraging the University of New Brunswick (UNB) Tor and non-Tor dataset, initially in a packet capture format, the preprocessing is done by transforming through CICFlowmeter. To expedite classification, we applied feature selection techniques like Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (tSNE). Machine learning algorithms like support vector machine (SVM), Gradient Boosting , Random Forest , and Artificial Neural Network (ANN) are applied. Our approach achieves a remarkable recall score ratio of 1.00, demonstrating high accuracy in Tor traffic identification. Notably, efficient feature selection has significantly reduced classification time. This work also contributes to effective Tor and non-Tor network traffic analysis , offering an efficient model for enhanced security and management.

The intelligent vehicles collect and distribute the data to other vehicles and Roadside Units (RSU), which ultimately strengthens the vehicular services in the Vehicular Ad-hoc Network (VANET). In order to protect against a variety of potential security threats, the VANET system needs a proper authentication mechanism, which requires more computational overheads and cannot perform better, when a cluster of vehicles sends the messages simultaneously. This paper aims to design a decentralized blockchain-based batch authentication protocol using Elliptic Curve Cryptography, where RSU authenticates the group of vehicles together. Moreover. our protocol also supports the verification of both individual messages (signature) generated by the vehicle and batch signature. We have used the Scyther security tool to verify our protocol and found that the protocol is safe and secure. A detailed comparative analysis reveals that the proposed scheme achieves more functionality and security compared to relevant schemes. The security analysis confirms that the proposed scheme is secure against all applicable attacks. Moreover, the ethereum platform simulates the proposed scheme, showing its effectiveness and confirming that it is feasible to deploy and execute transactions in real networks.

It is widely recognized that the public-key cryptosystems are playing tremendously an important role for providing the security services. In majority of the cryptosystems the crucial arithmetic operation is modular exponentiation. It is composed of a series of modular multiplications. Hence, the performance of any cryptosystem is strongly depends on the efficient implementation of these operations. This paper presents the Bit Forwarding 3-bits(BFW3) technique for efficient implementation of modular exponentiation. The modular multiplication involved in BFW3 is evaluated with the help of Montgomery method. These techniques improves the performance by reducing the frequency of modular multiplications. Results shows that the BFW3 technique is able to reduce the frequency of multiplications by 18.20% for 1024-bit exponent. This reduction resulted in increased throughput of 18.11% in comparison with MME42_C2 at the cost of 1.09% extra area. The power consumption reduced by 8.53% thereby saving the energy up to 10.10%.

It is widely recognized that the public-key cryptosystem is playing a pivotal role to provide the security services not only in electronic world but also for secured key exchanges in military applications. Modular exponentiation is the crucial, but expensive, operation in several public-key cryptostyems, which makes use of repeated modular multiplications. So, the performance of public-key cryptography is highly influenced by the competent implementation of modular exponentiation. In order to speed up the entire process, it is essential to develop the modular exponential algorithms, which reduces the frequency of modular multiplications, and the time required to implement each modular multiplication. In this paper, we present the bit forwarding (BFW) techniques to reduce the count of modular multiplications for hardware implementation of modular exponentiation. Montgomery multiplication method is customized according to the needs of BFW techniques and implemented with radix-2, named as adaptable Montgomery multiplication, and also implemented with high radix and named as adaptable high-radix Montgomery multiplication. It has been computed that it is possible to reduce 11.16%, 15.14% and 18.20% of modular multiplications by BFW1, BFW2, and BFW3 algorithms, respectively, for 1024-bit exponent in comparison with prevailing techniques. This reduction will result in increased throughput and decreased power consumption. Copyright © 2016 John Wiley & Sons, Ltd.