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Cloud computing environment support resource sharing as cloud service over the internet. It enables the users to outsource data into the cloud server that can be accessed remotely from various devices distributed geographically. Accessing resources from the cloud causes various security issues as the attackers try to illegally access the data. The distributed denial of service (DDoS) attack is one of the security concern in the cloud server. DDoS is a kind of cyber attack which disrupt normal traffic of targeted cloud server (or any other servers). In this paper, we propose an effective fuzzy and taylor-elephant herd optimization (FT-EHO) inspired by deep belief network (DBN) classifier for detecting the DDoS attack. FT-EHO uses taylor series and elephant heard optimization algorithm along with a fuzzy classifier for rules learning. The performance of the proposed FT-EHO is evaluated through rigorous computer simulations. Three standard benckmark databases, namely, KDD cup, database1 and database2 are used during simulations. Four quality measures such as accuracy, detection accurarcy, precision and recall are considered as a performance metrics. FT-EHO's performance is compared against the state-ofthe-art methods considering the evaluation metrics. Results reveals that the proposed FT-EHO showed significantly higher value of evaluation metrics (accuracy (93.811%), detection rate (97.200%), precision (94.981%) and recall (93.833%)) as compared to other methods.

Summary Conventionally, multilevel inverter topologies require components like boost converter, voltage balancing circuits in addition to its switches and gate driver circuitry resulting in increased complexity. A new multilevel inverter topology using the concept of switched‐capacitor (SC) is proposed in this article. The basic structure capable of generating 9 level (9L) output voltage waveform with magnitude twice the input voltage at its terminals is proposed. Further, two identical structures are cascaded horizontally to attain 17 level (17L) based on structural modification is suggested. Simulation results are used to analyze the performance of the proposed 9L‐SCMLI and 17L‐SCMLI in the aspects of total harmonic distortion, R, RL, and dynamic loading conditions. The 9L‐SCMLI prototype model is developed to validate the adaptability of the proposed system.