Abdullah Alabdulatif¹, Syed Sajjad Hussain Rizvi^2,*

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 827-840, 2022, DOI:10.32604/iasc.2022.021879

Abstract Network intrusion detection is the pressing need of every communication network. Many network intrusion detection systems (NIDS) have been proposed in the literature to cater to this need. In recent literature, plug-and-play NIDS, Kitsune, was proposed in 2018 and greatly appreciated in the literature. The Kitsune datasets were divided into 70% training set and 30% testing set for machine learning algorithms. Our previous study referred that the variants of the Tree algorithms such as Simple Tree, Medium Tree, Coarse Tree, RUS Boosted, and Bagged Tree have reported similar effectiveness but with slight variation inefficiency. To further extend this investigation, we… More >

Arwa Mashat¹, Surbhi Bhatia^2,*, Ankit Kumar³, Pankaj Dadheech³, Aliaa Alabdali⁴

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 841-857, 2022, DOI:10.32604/iasc.2022.021636

Abstract The transmission of medical records over indiscrete and open networks has caused an increase in fraud involving stealing patients’ information, owing to a lack of security over these links. An individual’s medical documents represent confidential information that demands strict protocols and security, chiefly to protect the individual’s identity. Medical image protection is a technology intended to transmit digital data and medical images securely over public networks. This paper presents some background on the different methods used to provide authentication and protection in medical information security. This work develops a secure cryptography-based medical image reclamation algorithm based on a combination of… More >

N. Manikanda Devarajan^1,*, S. Thenmozhi², K. Jayaram³, R. Saravanakumar⁴

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1167-1178, 2022, DOI:10.32604/iasc.2022.021558

Abstract Orthogonal Frequency Division Multiplexing (OFDM) is a wireless communication technology that is used for highly reliable and high data rate communication. In a multi-user OFDM system, the interference has occurred in the receiver side between the consecutive OFDM symbols. This interference reduces the performance of the OFDM system. To achieve good quality in received symbols the interference level should be minimized. The conventional cancellation system requires higher interference reduction time and power. These limitations of the conventional interference cancellation architectures for OFDM systems are overcome by proposing efficient and low power interference cancellation architecture. Hence, this paper proposes a novel… More >

Jabeen Sultana^1,*, Anjani Kumar Singha², Shams Tabrez Siddiqui³, Guthikonda Nagalaxmi⁴, Anil Kumar Sriram⁵, Nitish Pathak⁶

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1007-1024, 2022, DOI:10.32604/iasc.2022.021507

Abstract COVID-19 is a novel virus that spreads in multiple chains from one person to the next. When a person is infected with this virus, they experience respiratory problems as well as rise in body temperature. Heavy breathlessness is the most severe sign of this COVID-19, which can lead to serious illness in some people. However, not everyone who has been infected with this virus will experience the same symptoms. Some people develop cold and cough, while others suffer from severe headaches and fatigue. This virus freezes the entire world as each country is fighting against COVID-19 and endures vaccination doses.… More >

Siyuan Liu¹, Shaoyong Guo^1,*, Ziwei Hu², Xin Xu³, Wei Bai², Ningzhe Xing⁴, Xuesong Qiu¹, Siwen Xu⁵

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 951-962, 2022, DOI:10.32604/iasc.2022.021202

Abstract Although the current Domain Name System (DNS) has been able to satisfy the use of network services, there are still many challenges in the future development of the Internet. The centralized management of traditional domain name management systems has many risks, and cannot defend against Distributed Denial of Service (DDoS) attacks and single points of failure. As a decentralized tool, blockchain provides innovative ideas for the improvement of domain name management systems. Starting from the existing network resolution system and combining the application of cross-chain communication in DNS, this paper proposes a domain name resolution service architecture model based on… More >

Erssa Arif^1,*, Syed Khuram Shahzad², Rehman Mustafa¹, Muhammad Arfan Jaffar³, Muhammad Waseem Iqbal⁴

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 909-922, 2022, DOI:10.32604/iasc.2022.021061

Abstract The conventional surveillance and control system of Closed-Circuit Television (CCTV) cameras require human resource supervision. Almost all the criminal activities take place using weapons mostly handheld gun, revolver, or pistol. Automatic gun detection is a vital requirement now-a-days. The use of real-time object detection system for the improvement of surveillance is a promising application of Convolutional Neural Networks (CNN). We are concerned about the real-time detection of weapons for the surveillance cameras, so we focused on the implementation and comparison of faster approaches such as Region (R-CNN) and Region Fully Convolutional Networks (R-FCN) with feature extractor Visual Geometry Group (VGG)… More >

Rahul Dubey^*, Jitendra Agrawal

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 747-763, 2022, DOI:10.32604/iasc.2022.020975

Abstract Extracting the features from an image is a cumbersome task. Initially, this task was performed by domain experts through a process known as handcrafted feature design. A deep embedding technique known as convolutional neural networks (CNNs) later solved this problem by introducing the feature learning concept, through which the CNN is directly provided with images. This CNN then learns the features of the image, which are subsequently given as input to the further layers for an intended task like classification. CNNs have demonstrated astonishing performance in several practicable applications in the last few years. Nevertheless, the pursuance of CNNs primarily… More >

P. Hemalatha^1,*, K. Dhanalakshmi²

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 811-825, 2022, DOI:10.32604/iasc.2022.020973

Abstract Wireless sensor networks (WSNs) develop IoT (Internet of Things) that carry out an important part and include low-cost intelligent devices to gather information. However, these modern accessories have limitations concerning calculation, time taken for processing, storage capacity, and vitality sources. In addition to such restrictions, the foremost primary challenge for sensor networks is achieving reliable data transfer with the secured transmission in a hostile ambience containing vulnerable nodes. The proposed work initially analyses the relation between deployment configuration, lifetime of the deployed network, and transmission delay with this motivation. Besides, it also introduces a new cellular automata-based scheme for improving… More >

Sivaramakrishnan Rajendar, Vishnu Kumar Kaliappan^*

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 859-875, 2022, DOI:10.32604/iasc.2022.020936

Abstract Automated Vehicles (AVs) reform the automotive industry by enabling real-time and efficient data exchange between the vehicles. While connectivity and automation of the vehicles deliver a slew of benefits, they may also introduce new safety, security, and privacy risks. Further, AVs rely entirely on the sensor data and the data from other vehicles too. On the other hand, the sensor data is susceptible to anomalies caused by cyber-attacks, errors, and faults, resulting in accidents and fatalities. Hence, it is essential to create techniques for detecting anomalies and identifying their sources before the wide adoption of AVs. This paper proposes an… More >

Yun-Kyu Lee¹, Dong-Sung Pae², Dae-Ki Hong³, Myo-Taeg Lim¹, Tae-Koo Kang^4,*

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 657-673, 2022, DOI:10.32604/iasc.2022.020849

Abstract With the advancement of human-computer interaction and artificial intelligence, emotion recognition has received significant research attention. The most commonly used technique for emotion recognition is EEG, which is directly associated with the central nervous system and contains strong emotional features. However, there are some disadvantages to using EEG signals. They require high dimensionality, diverse and complex processing procedures which make real-time computation difficult. In addition, there are problems in data acquisition and interpretation due to body movement or reduced concentration of the experimenter. In this paper, we used photoplethysmography (PPG) and electromyography (EMG) to record signals. Firstly, we segmented the… More >