An important part of based on elliptical curves cryptographic data protection is multipliers of Galois fields. For based on elliptical curves digital signatures, not only prime but also extended Galois fields GF(p^m) are used. The article provides a theoretical justification for the use of extended Galois fields GF(d^m) with characteristics d > 2, and a criterion for determining the best field is presented. With the use of the proposed criterion, the best fields, which are advisable to use in data protection, are determined.
Cores (VHDL descriptions of digital units) are considered as structural part of based on FPGA devices. In the article methods for cryptoprocessors cores creating were analyzed. The article describes the generator of VHDL descriptions of extended Galois field multipliers with big characteristic (up to 2⁹⁹⁸). The use of mathematical packages for calculations to improve the quality of information security is also considered.
The Galois field multipliers generator creates the VHDL description of multipliers schemes, describes connections of their parts and generates VHDL descriptions of these parts as result of Quine-McCluskey Boolean functions minimization method. However, the execution time of the algorithm increases with increasing amount of input data. Accordingly, generating field multipliers with large characteristic can take frерom a few seconds to several tens of seconds.
It's important to simplify the design and minimize logic gates number in a field programmable gate array (FPGA) because it will speed up the operation of multipliers. The generator creates multipliers according to the three variants.
The efficiency of using multipliers for fields with different characteristics was compared in article.
The expediency of using extended Galois fields GF(d^m) with characteristics d > 2 in data protection tools is analyzed, a criterion for comparing data protection tools based on such Galois fields is determined, and the best fields according to the selected criterion when implemented according to a certain algorithm are determined.

A Biometric Authentication Security (BAS) protocol is a method by which a person's unique physiological or behavioral characteristics are used to verify their identity. These characteristics can include fingerprints, facial features, voice patterns, and more. Biometric authentication has become increasingly popular in recent years due to its convenience and perceived security benefits. However, ensuring that the BAS protocols are secure and cannot be easily compromised. . Developing a highly secure biometric authentication protocol is challenging, and proving its correctness is another challenge. In this work, we present a modern mechanism for formally analyzing biometric authentication security protocol by taking a Aadhaar Level-0 Iris-based Authentication Protocol as a use case. The mechanism uses formal methods to formally verify the security of the Aadhaar Level-0 Iris-based Authentication protocol, and is based on the widely-used BAN logic (Buruccu, Abadi, and Needham). Using Scyther model checker we analyze the existing biometric authentication protocol and have shown its effectiveness in identifying potential security vulnerabilities. The proposed mechanism is based on a set of security requirements that must be met for the protocol to be considered secure. These requirements include the need for the protocol to be resistant to replay attacks, man-in-the-middle attacks, and impersonation attacks. The mechanism also considers the possibility of an attacker obtaining the biometric data of a legitimate user.

Over the last two years,the number of cyberattacks has grown significantly, paralleling the emergence of new attack types as intruder’s skill sets have improved. It is possible to attack other devices on a botnet and launch a man-in-the-middle attack with an IOT device that is present in the home network. As time passes, an ever-increasing number of devices are added to a network. Such devices will be destroyed completely if one or both of them are disconnected from a network. Detection of intrusions in a network becomes more difficult because of this. In most cases, manual detection and intervention is ineffective or impossible. Consequently, it's vital that numerous types of network threats can be better identified with less computational complexity and time spent on processing. Numerous studies have already taken place, and specific attacks are being examined. In order to quickly detect an attack, an IDS uses a well-trained classification model. In this study, multi-layer perceptron classifier along with random forest is used to examine the accuracy, precision, recall and f-score of IDS. IoT environment-based intrusion related benchmark datasets UNSWNB-15 and N_BaIoT are utilized in the experiment. Both of these datasets are relatively newer than other datasets, which represents the latest attack. Additionally, ensembles of different tree sizes and grid search algorithms are employed to determine the best classifier learning parameters. The research experiment's outcomes demonstrate the effectiveness of the IDS model using random forest over the multi-layer perceptron neural network model since it outperforms comparable ensembles analyzed in the literature in terms of K-fold cross validation techniques.

XML and JSON are commonly used data exchange formats that are widely in use in wireless networking environments. The verbose and redundant nature of XML documents incurs huge transportation overheads in data communications. JSON is a data format that reduces the document size; but its scope is confined to text and numeric data. Also due to the reasons such as lack of schema and limited interoperability features, JSON is more suitable for web based applications, compared to wireless or mobile environments. Since the literature reports serious concerns about the performance of existing data exchange formats in resource constraint networks, there is scope for a lightweight data exchange mechanism. This paper introduces a new lightweight, schema aware data exchange format for data representation and interchange. The proposed format, called LXML, is schema aware and non-binary format based on the XML standards and has the potential to be an alternative format for XML and JSON in a wireless environment. Experimental findings indicate that LXML is a less verbose and efficient data exchange format and its performance is found to be better than the existing non binary data exchange formats.

For starters, in UASN, distance between nodes as they move with water current, improved network's energy usage. The second problem with UASNs is void hole occurrence, which affects network performance. Nodes are unable to deliver data to the destination because there are no forwarder nodes (FNs) in the network. As a result, routing in UASNs aims to solve the previously mentioned issues in order to increase the network's lifespan. This research proposed novel technique in Void avoidance in underwater acoustic sensor network (UASN) with improving the energy efficiency of the network and analysing depth with security. In this proposed model, secure opportunistic energy efficient void avoidance protocol (Se_Opp_EE_VA) is used and the depth of the network has been analysed. By avoiding the vacuum zone and balancing network energy with depth analysis and security, the suggested effort extends the network lifetime. Routing techniques must be comprehensive enough to overcome all of these constraints as well as provide an energy-efficient routing that avoids empty zones while also extending network lifetime. The depth factor is used in depth-based algorithms proposed in recent decades to assess the path from sender to sink. They reduce information replication by using the holding time calculation. 81% of QoS, 92% of PDR, 96% of energy efficiency, Network lifetime attained by Proposed Se_Opp_EE_VA is 94%, and 50% of end to end delay have all improved as a result of the simulation.

Because of the mobility of its nodes, MANET plays a significant role in mobile communication. As a result, network infrastructure is frequently changed, resulting in data loss and communication overheads. Despite this, the large packet size causes network congestion or traffic. The difficult task is efficient routing through a dynamic network. For node generation and energy management, the proposed approach in this paper employs GAODM (Geography-based Ad-hoc On Demand disjoint multipath) and E-AODM (Energy Ad-hoc On Demand Vector routing). The proposed GAODM routing protocol reduces congestion using Spider Monkey (SM) Optimization. The E- AODM protocol assesses the energy management solution based on parameters such as delay, energy consumption, routing overhead, and node energy. By choosing the best path through the network, the proposed protocol's effectiveness is increased. The proposed protocol reduces routing overload, delay, and congestion. The simulated results show that increasing the number of packets transmitted in the network using the proposed GAODM and E-AODM routing protocols over the existing protocols on NS 2 reduces node energy and, as a result, overload and delay.

Vehicle ad hoc networks, or VANETs, are highly mobile wireless networks created to help with traffic monitoring and vehicular safety. Security risks are the main problems in VANET. To handle the security threats and to increase the performance of VANETs, this paper proposes an enhanced trust based aggregate model. In the proposed system, a novel adaptive nodal attack detection approach - entropy-based SVM with linear regression addresses the trust factor with kernel density estimation generating the trustiness value thereby classifying the malicious nodes against the trusted nodes in VANETs. Defending the VANETs is through a novel reliance node estimation approach - Bayesian self-healing AIS with Pearson correlation coefficient aggregate model isolating the malicious node thereby the RSU cluster communication getting secure. Furthermore, even a reliable node may be exploited to deliver harmful messages and requires the authority of both the data and the source node to be carried out by the onboard units of the vehicles getting the reports of incident. DoS attacks (Denial of Service) disrupting the usual functioning of the network leads to inaccessible network to its intended users thereby endangering human lives. The proposed system is explicitly defending the VANET against DoS attacks as it predicts the attack without compromising the performance of the VANET handling nodes with various features and functions based on evaluating the maliciousness of attacking nodes accurately and isolating the intrusion. Furthermore, the performance evaluations prove the effectiveness of the proposed work with increased detection rate by 97%, reduced energy consumption by 39% and reduced latency by 25% compared to the existing studies.