Nature-inspired adaptive decision support system for secured clustering in cyber networks

Qureshi, Shahana Gajala; Shandilya, Shishir Kumar

doi:10.1007/s11042-022-13336-7

Cited by 3 publications

(5 citation statements)

References 34 publications

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“…In addition to that, the author in Reference 36 has proposed a method based on monitoring and securing petroleum product distribution records in a database of decentralized ledgers using blockchain technology. In the domain of cybersecurity, researchers contributed their study and implementation of various proactive methods that improve the security of data from attackers 37–41 . The main motivation of the technique has been implemented for securing the transaction of the various database records provided in the ledger.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In the domain of cybersecurity, researchers contributed their study and implementation of various proactive methods that improve the security of data from attackers. [37][38][39][40][41] The main motivation of the technique has been implemented for securing the transaction of the various database records provided in the ledger. This helped in protecting the records from fraudulent activity, tampering, and corruption by chain participants.…”

Section: Blockchainmentioning

confidence: 99%

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Maximizing blockchain security: Merkle tree hash values generated through advanced vectorized elliptic curve cryptography mechanisms

Sharma

Shandilya

Satapathy

2023

Concurrency and Computation

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SummaryCloud computing is considered as the most fabulous paradigm to accommodate various kinds of user information. However, the privacy conflicts integrated with computational complexities need more hybridized resource efficiency for hassle‐free accession. For this purpose, this article presents a cloud assisted, secured and privacy preserved protocol based on the elliptical curve cryptography (ECC) and blockchain consortium. Blockchain provides an innovative approach for storing information, establishing trust, and various other transactions in an open platform. There exists no single technology as a panacea to obtain optimum privacy and security in the complex cloud environment that needs several desired characteristics. Hence, an elite integration of multiple cryptographic methods by carefully analyzing the potential harms and pitfalls has to be framed to balance the trade‐off between privacy and security. The proposed technique highlights the user privacy preservation through guaranteeing that user information is safeguarded from unauthorized use or access. In accordance with that the present study enrolled the advantages of the ECC algorithm, vectorization, and blockchain methods to rule out the limitations of state of art methods. This article attempts to provide the most required privacy with optimum key generation, encryption, and decryption time. The present study has obtained optimal outcomes and the maximum percentage reduction w.r.t the existing method in key generation time, encryption time, and decryption time is given as 14.89%, 16.67%, and 12.5%, respectively.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Blockchainmentioning

confidence: 99%

Maximizing blockchain security: Merkle tree hash values generated through advanced vectorized elliptic curve cryptography mechanisms

Sharma

Shandilya

Satapathy

2023

Concurrency and Computation

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“…When two WSN nodes are within one hop distance, the direct trust of x i is calculated by x j at time t. Each cyclic trust evaluation round includes WSN node x j observing WSN node x i directly. Since aggressive users are primarily concerned with packet loss and fake acknowledgment, the packet of transmission behavior (TB) parameter allows for accurate estimation of the WSN node through x-rate estimation [40].…”

Section: Packet Of Transmission Behaviormentioning

confidence: 99%

“…Weight parameters represent the Trust-coefficient between the nodes. The PF is calculated as shown in Equation ( 2) [40].…”

Section: Packet Of Transmission Behaviormentioning

confidence: 99%

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Adaptive Trust-Based Framework for Securing and Reducing Cost in Low-Cost 6LoWPAN Wireless Sensor Networks

et al. 2022

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Wireless Sensor Networks (WSNs) are the core of the Internet of Things (IoT) technology, as they will be used in various applications in the near future. The issue of security and power consumption is still one of the most important challenges facing this type of network. 6LoWPAN protocol was developed to meet these challenges in networks with limited power and resources. The 6LoWPAN uses a hierarchical topology and the traditional method of encryption and key management, keeping power consumption levels high. Therefore, in this paper, a technique has been developed that helps in balancing security and energy consumption by exploiting the Trust technique between low-cost WSN nodes called Trust-Cluster Head (Trust-CH). Trust between nodes is built by monitoring the behavior of packet transmission, the number of repetitions and the level of security. The Trust-CH model provides a dynamic multi-level encryption system that depends on the level of Trust between WSN nodes. It also proposes a dynamic clustering system based on the absolute-trust level in the mobile node environment to minimize power consumption. Along with a set of performance metrics (i.e., power consumption and network lifetime), the Cooja simulator was used to evaluate the Trust-CH model. The results were compared to a static symmetric encryption model together with various models from previous studies. It has been proven that the proposed model increases the network lifetime by 40% compared to previous studies, as well as saves as much as 28% power consumption in the case of using a static encryption model. While maintaining the proposed model’s resistance to many malicious attacks on the network.

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An adaptive operation planning and EBO-BPNN optimization method for decision support systems

Liu,

Wang,

et al. 2024

Sci Rep

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Formulating a course of action (COA) before a combat is crucial for operational command. Research in command and control (C2) artificial intelligence is currently focused on using intelligent auxiliary decision-making methods to implement COA. This paper proposes a COA planning method based on line of operation (LOO) and uses planning domain definition language (PDDL) to describe combat scenarios and COA. Following the effect-based optimization (EBO) principle, an effect evaluation model for COA was constructed, and dynamic bayesian networks (DBNs) was used to determine the reasoning and calculate the results of the effect evaluation network. To further improve the execution efficiency of the effect evaluation model in practical applications, the network was optimized through a back propagation neural network (BPNN). Relevant experiments based on the coordinated distributed air defense and anti-missile scenario were carried out using the LOO model to complete the planning of COA. A BPNN evaluation model based on the DBNs evaluation model was built. After training and fine-tuning, it achieved similar evaluation results, with a mean absolute percentage error (MAPE) of less than 0.02%. Compared with the DBNs model, the BPNN model achieved an efficiency improvement of no less than 65%, effectively reducing the consumption of computing resources. This research is the first time to realize the modeled description of COA planning, automatic evaluation, and calculation optimization of COA effects. It can support the development of decision support systems (DSS) and has the potential for practical application.

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Nature-inspired adaptive decision support system for secured clustering in cyber networks

Cited by 3 publications

References 34 publications

Maximizing blockchain security: Merkle tree hash values generated through advanced vectorized elliptic curve cryptography mechanisms

Maximizing blockchain security: Merkle tree hash values generated through advanced vectorized elliptic curve cryptography mechanisms

Adaptive Trust-Based Framework for Securing and Reducing Cost in Low-Cost 6LoWPAN Wireless Sensor Networks

An adaptive operation planning and EBO-BPNN optimization method for decision support systems

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