Hybridization of the Flower Pollination Algorithm—A Case Study in the Problem of Generating Healthy Nutritional Meals for Older Adults

Pop, Cristina Bianca; Chifu, Viorica Rozina; Salomie, Ioan; Racz, Dalma Szonja; Bonta, Razvan Mircea

doi:10.1007/978-3-319-50920-4_7

Cited by 11 publications

(1 citation statement)

References 14 publications

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“…FPA Contains two operators: local and global and outperforms other metaheuristic algorithms in real-world optimisation challenges due to its adaptability and scalability. In addition, FPA has many examples of optimization challenges such as wireless sensor networking [23], electrical and power systems [24,25], signal and image processing [26,27], clustering and classification [28,29], computer gaming, structural and mechanical engineering optimisation [30,31], global function optimisation [32], and various variants [33,34]. In some studies, FPA is used in hybridised, modification, with parameter-tuning to resolve complex problems related to optimisation [35].…”

Section: Flower Pollination Algorithm (Fpa)mentioning

confidence: 99%

Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary Flower Pollination Algorithm

Hasan Bdair Aighuraibawi,

Manickam,

Abdullah

et al. 2023

Computer Systems Science and Engineering

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Internet Protocol version 6 (IPv6) is the latest version of IP that goal to host 3.4 × 10 38 unique IP addresses of devices in the network. IPv6 has introduced new features like Neighbour Discovery Protocol (NDP) and Address Auto-configuration Scheme. IPv6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol (ICMPv6). IPv6 is vulnerable to numerous attacks like Denial of Service (DoS) and Distributed Denial of Service (DDoS) which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial implications. Therefore, an Intrusion Detection System (IDS) is a monitoring system of the security of a network that detects suspicious activities and deals with a massive amount of data comprised of repetitive and inappropriate features which affect the detection rate. A feature selection (FS) technique helps to reduce the computation time and complexity by selecting the optimum subset of features. This paper proposes a method for detecting DDoS flooding attacks (FA) based on ICMPv6 messages using a Binary Flower Pollination Algorithm (BFPA-FA). The proposed method (BFPA-FA) employs FS technology with a support vector machine (SVM) to identify the most relevant, influential features. Moreover, The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack scenarios. The results show that the proposed method BFPA-FA achieved the best accuracy rate (97.96%) for the ICMPv6 DDoS detection with a reduced number of features (9) to half the total (19) features. The proven proposed method BFPA-FA is effective in the ICMPv6 DDoS attacks via IDS.

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