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p-Index From 2021 - 2026
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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI)
Hebbur Satyanarayana, Gururaja
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Computer Science & IT Electrical & Electronics Engineering Engineering

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A typical analysis of hybrid covert channel using constructive entropy analytics Krishnamurthy Koundinya, Anjan; Hebbur Satyanarayana, Gururaja
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i4.pp3820-3826

Abstract

A covert timing channel is based on modulation of the timing information in the network packets in a secured communication. The delicacy of this channel is primarily viewed as single coherent channel thwart the detection from any third-party entity or network admin. The timing covert channel is strenuous to detect under many scenarios due to the intricate complexity of the channel. The exploration of timing covert channel shed light on intrinsic design aspects which elevate understanding to an advanced level. This will effectively bring out elite literature aspects of the timing covert channel for seamless implementation. Supraliminal channels are innocuous message-based channel introduced as a trapdoor in the communication system either intentional or as vulnerability of the system. A hybrid covert channel is the existence of homogeneous or heterogeneous network covert channel variants either at same instant or at different instant of time. For instance, one of possible hybrid covert channel is the co-existence of timing covert channel in transmission control protocol (TCP) and supraliminal channel in voice over internet protocol (VoIP). This paper introduces this variant of the hybrid covert channel and their significance in network communication. The paper also refers to standard measures-entropy, covertness index to understand hybrid covert channel.
Zoneout regularization-gated recurrent unit algorithm on NIDS with class imbalance handling Kariyappa, Mala; Hanumanthappa Rangappa, Manjunath; Dasappa, Venugopal; Hebbur Satyanarayana, Gururaja; Keshava Rao, Girish; Thahniyath, Gousia
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i2.pp1505-1512

Abstract

Network intrusion detection system (NIDS) is primarily utilized tool to identify malicious threats on the network. It plays an essential role in safeguarding against an increasing variety of attacks and ensures enhanced security for the network. The existing model struggled to handle the imbalance of class issues during the process of classification due to their biased nature, which reduced the performance of the algorithm. In this paper, the zoneout regularization–gated recurrent unit (ZR-GRU) algorithm is developed to detect and classify intrusions in the network. Incorporating the ZR into GRU reduces overfitting by preventing the model from becoming overly dependent on specific features. It provides good generalization by maintaining diversity in learned representation. Synthetic minority oversampling technique (SMOTE) and Near Miss methods are utilized to balance the samples in the dataset, which helps to increase the performance of a classifier in NIDS. The ZR-GRU technique attained 99.91% accuracy on UNSW-NB15, 99.92% accuracy on CIC-IDS2018, and 99.14% accuracy on CIC-DDoS2019 when comparing with a convolutional neural network bidirectional long short-term memory (CNN-BiLSTM).
Co-Authors Dasappa, Venugopal Hanumanthappa Rangappa, Manjunath Kariyappa, Mala Keshava Rao, Girish Krishnamurthy Koundinya, Anjan Thahniyath, Gousia