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Advanced Achievements of Intelligent and Secure Systems for the Next Generation Computing

Submission Deadline: 31 March 2023 (closed)

Guest Editors

Dr. Ilsun You, Kookmin University, South Korea.
Dr. Nik Bessis, Edge Hill University, United Kingdom.
Dr. Gokhan Kul, University of Massachusetts Dartmouth, United States.
Dr. Sang-Woong Lee, Gachon University, South Korea.

Summary

Computers and ICT technologies have changed most aspects of our daily lives. The current pace of the digital transformation and its acceleration have caused the constantly growing need for effective, efficient, and secure computing systems. Hence, computer scientists and engineers currently put more effort than ever for improving the performance and security of computing systems, thereby going beyond traditional limits to support the digital transformation evolution. In order to maintain the momentum and enhance the current computing environment, we need innovative scientific developments in the wide range of topics of artificial intelligent systems, neural networks, cybersecurity, etc. This special issue seeks high-quality papers on the vast computing field which introduce advanced approaches that can contribute to improving the current computing environment, tackling various and difficult technical challenges. We welcome the recent advances and theoretical progress in various topics which include but are not limited to the following:

 

Topics

- Innovative AI powered applications in 5G/6G network environments

- Cyber security and privacy for digital transformation

- Intelligent and trustworthy high performance computing

- Advanced graph networks, deep neural networks and machine learning

- Applications of neural networks in data analytic

- Cryptography and network security

- AI security and forensics technologies

- Smart cities, secure applications and smart buildings

- Power energy, power management and smart analytics

- Smart mobility, intelligent transportation and logistics

- Big data, systems automation, IoT analytics

- Dashboards, visual computing and disruptive technologies

- Distributed AI systems and architectures

- Smart healthcare and medical information analysis

- AI-based bioinformatics

Keywords

Next generation computing, AI powered applications, Cybersecurity, Digital transformation

Published Papers

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  • Open Access

    ARTICLE

    Wake-Up Security: Effective Security Improvement Mechanism for Low Power Internet of Things

    Sun-Woo Yun, Na-Eun Park, Il-Gu Lee
    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2897-2917, 2023, DOI:10.32604/iasc.2023.039940
    （This article belongs to this Special Issue: Advanced Achievements of Intelligent and Secure Systems for the Next Generation Computing)
    Abstract As time and space constraints decrease due to the development of wireless communication network technology, the scale and scope of cyberattacks targeting the Internet of Things (IoT) are increasing. However, it is difficult to apply high-performance security modules to the IoT owing to the limited battery, memory capacity, and data transmission performance depending on the size of the device. Conventional research has mainly reduced power consumption by lightening encryption algorithms. However, it is difficult to defend large-scale information systems and networks against advanced and intelligent attacks because of the problem of deteriorating security performance. In this study, we propose wake-up… More >

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    497

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    188

  • Open Access

    ARTICLE

    Dynamic Security SFC Branching Path Selection Using Deep Reinforcement Learning

    Shuangxing Deng, Man Li, Huachun Zhou
    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2919-2939, 2023, DOI:10.32604/iasc.2023.039985
    （This article belongs to this Special Issue: Advanced Achievements of Intelligent and Secure Systems for the Next Generation Computing)
    Abstract Security service function chaining (SFC) based on software-defined networking (SDN) and network function virtualization (NFV) technology allows traffic to be forwarded sequentially among different security service functions to achieve a combination of security functions. Security SFC can be deployed according to requirements, but the current SFC is not flexible enough and lacks an effective feedback mechanism. The SFC is not traffic aware and the changes of traffic may cause the previously deployed security SFC to be invalid. How to establish a closed-loop mechanism to enhance the adaptive capability of the security SFC to malicious traffic has become an important issue.… More >

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    513

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    179

  • Open Access

    ARTICLE

    FIDS: Filtering-Based Intrusion Detection System for In-Vehicle CAN

    Seungmin Lee, Hyunghoon Kim, Haehyun Cho, Hyo Jin Jo
    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2941-2954, 2023, DOI:10.32604/iasc.2023.039992
    （This article belongs to this Special Issue: Advanced Achievements of Intelligent and Secure Systems for the Next Generation Computing)
    Abstract Modern vehicles are equipped with multiple Electronic Control Units (ECUs) that support various convenient driving functions, such as the Advanced Driver Assistance System (ADAS). To enable communication between these ECUs, the Controller Area Network (CAN) protocol is widely used. However, since CAN lacks any security technologies, it is vulnerable to cyber attacks. To address this, researchers have conducted studies on machine learning-based intrusion detection systems (IDSs) for CAN. However, most existing IDSs still have non-negligible detection errors. In this paper, we propose a new filtering-based intrusion detection system (FIDS) to minimize the detection errors of machine learning-based IDSs. FIDS uses… More >

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    661

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    227

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    1

  • Open Access

    ARTICLE

    Multi-Domain Malicious Behavior Knowledge Base Framework for Multi-Type DDoS Behavior Detection

    Ouyang Liu, Kun Li, Ziwei Yin, Deyun Gao, Huachun Zhou
    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2955-2977, 2023, DOI:10.32604/iasc.2023.039995
    （This article belongs to this Special Issue: Advanced Achievements of Intelligent and Secure Systems for the Next Generation Computing)
    Abstract Due to the many types of distributed denial-of-service attacks (DDoS) attacks and the large amount of data generated, it becomes a challenge to manage and apply the malicious behavior knowledge generated by DDoS attacks. We propose a malicious behavior knowledge base framework for DDoS attacks, which completes the construction and application of a multi-domain malicious behavior knowledge base. First, we collected malicious behavior traffic generated by five mainstream DDoS attacks. At the same time, we completed the knowledge collection mechanism through data pre-processing and dataset design. Then, we designed a malicious behavior category graph and malicious behavior structure graph for… More >

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    448

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    255

  • Open Access

    ARTICLE

    Design the IoT Botnet Defense Process for Cybersecurity in Smart City

    Donghyun Kim, Seungho Jeon, Jiho Shin, Jung Taek Seo
    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2979-2997, 2023, DOI:10.32604/iasc.2023.040019
    （This article belongs to this Special Issue: Advanced Achievements of Intelligent and Secure Systems for the Next Generation Computing)
    Abstract The smart city comprises various infrastructures, including healthcare, transportation, manufacturing, and energy. A smart city’s Internet of Things (IoT) environment constitutes a massive IoT environment encompassing numerous devices. As many devices are installed, managing security for the entire IoT device ecosystem becomes challenging, and attack vectors accessible to attackers increase. However, these devices often have low power and specifications, lacking the same security features as general Information Technology (IT) systems, making them susceptible to cyberattacks. This vulnerability is particularly concerning in smart cities, where IoT devices are connected to essential support systems such as healthcare and transportation. Disruptions can lead… More >

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    732

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    232

    Like

    3

  • Open Access

    ARTICLE

    Anomaly Detection and Access Control for Cloud-Edge Collaboration Networks

    Bingcheng Jiang, Qian He, Zhongyi Zhai, Hang Su
    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2335-2353, 2023, DOI:10.32604/iasc.2023.039989
    （This article belongs to this Special Issue: Advanced Achievements of Intelligent and Secure Systems for the Next Generation Computing)
    Abstract Software-defined networking (SDN) enables the separation of control and data planes, allowing for centralized control and management of the network. Without adequate access control methods, the risk of unauthorized access to the network and its resources increases significantly. This can result in various security breaches. In addition, if authorized devices are attacked or controlled by hackers, they may turn into malicious devices, which can cause severe damage to the network if their abnormal behaviour goes undetected and their access privileges are not promptly restricted. To solve those problems, an anomaly detection and access control mechanism based on SDN and neural… More >

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    460

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    299

  • Open Access

    ARTICLE

    Machine Learning-Based Efficient Discovery of Software Vulnerability for Internet of Things

    So-Eun Jeon, Sun-Jin Lee, Il-Gu Lee
    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2407-2419, 2023, DOI:10.32604/iasc.2023.039937
    （This article belongs to this Special Issue: Advanced Achievements of Intelligent and Secure Systems for the Next Generation Computing)
    Abstract With the development of the 5th generation of mobile communication (5G) networks and artificial intelligence (AI) technologies, the use of the Internet of Things (IoT) has expanded throughout industry. Although IoT networks have improved industrial productivity and convenience, they are highly dependent on nonstandard protocol stacks and open-source-based, poorly validated software, resulting in several security vulnerabilities. However, conventional AI-based software vulnerability discovery technologies cannot be applied to IoT because they require excessive memory and computing power. This study developed a technique for optimizing training data size to detect software vulnerabilities rapidly while maintaining learning accuracy. Experimental results using a software… More >

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    587

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    287

  • Open Access

    ARTICLE

    Unmanned Aerial Vehicle Multi-Access Edge Computing as Security Enabler for Next-Gen 5G Security Frameworks

    Jaime Ortiz Córdoba, Alejandro Molina Zarca, Antonio Skármeta
    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2307-2333, 2023, DOI:10.32604/iasc.2023.039607
    （This article belongs to this Special Issue: Advanced Achievements of Intelligent and Secure Systems for the Next Generation Computing)
    Abstract 5G/Beyond 5G (B5G) networks provide connectivity to many heterogeneous devices, raising significant security and operational issues and making traditional infrastructure management increasingly complex. In this regard, new frameworks such as Anastacia-H2020 or INSPIRE-5GPlus automate the management of next-generation infrastructures, especially regarding policy-based security, abstraction, flexibility, and extensibility. This paper presents the design, workflow, and implementation of a security solution based on Unmanned Aerial Vehicles (UAVs), able to extend 5G/B5G security framework capabilities with UAV features like dynamic service provisioning in specific geographic areas. The proposed solution allows enforcing UAV security policies in proactive and reactive ways to automate UAV dynamic… More >

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    457

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    282

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    1

  • Open Access

    ARTICLE

    Container Instrumentation and Enforcement System for Runtime Security of Kubernetes Platform with eBPF

    Songi Gwak, Thien-Phuc Doan, Souhwan Jung
    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1773-1786, 2023, DOI:10.32604/iasc.2023.039565
    （This article belongs to this Special Issue: Advanced Achievements of Intelligent and Secure Systems for the Next Generation Computing)
    Abstract Containerization is a fundamental component of modern cloud-native infrastructure, and Kubernetes is a prominent platform of container orchestration systems. However, containerization raises significant security concerns due to the nature of sharing a kernel among multiple containers, which can lead to container breakout or privilege escalation. Kubernetes cannot avoid it as well. While various tools, such as container image scanning and configuration checking, can mitigate container workload vulnerabilities, these are not foolproof and cannot guarantee perfect isolation or prevent every active threat in runtime. As such, a policy enforcement solution is required to tackle the problem, and existing solutions based on… More >

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    670

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    472

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