Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (10)
  • Open Access

    ARTICLE

    Classification of Cybersecurity Threats, Vulnerabilities and Countermeasures in Database Systems

    Mohammed Amin Almaiah1,*, Leen Mohammad Saqr1, Leen Ahmad Al-Rawwash1, Layan Ahmed Altellawi1, Romel Al-Ali2,*, Omar Almomani3

    CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3189-3220, 2024, DOI:10.32604/cmc.2024.057673 - 18 November 2024

    Abstract Database systems have consistently been prime targets for cyber-attacks and threats due to the critical nature of the data they store. Despite the increasing reliance on database management systems, this field continues to face numerous cyber-attacks. Database management systems serve as the foundation of any information system or application. Any cyber-attack can result in significant damage to the database system and loss of sensitive data. Consequently, cyber risk classifications and assessments play a crucial role in risk management and establish an essential framework for identifying and responding to cyber threats. Risk assessment aids in understanding… More >

  • Open Access

    ARTICLE

    IWTW: A Framework for IoWT Cyber Threat Analysis

    GyuHyun Jeon1, Hojun Jin1, Ju Hyeon Lee1, Seungho Jeon2, Jung Taek Seo2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1575-1622, 2024, DOI:10.32604/cmes.2024.053465 - 27 September 2024

    Abstract The Internet of Wearable Things (IoWT) or Wearable Internet of Things (WIoT) is a new paradigm that combines IoT and wearable technology. Advances in IoT technology have enabled the miniaturization of sensors embedded in wearable devices and the ability to communicate data and access real-time information over low-power mobile networks. IoWT devices are highly interdependent with mobile devices. However, due to their limited processing power and bandwidth, IoWT devices are vulnerable to cyberattacks due to their low level of security. Threat modeling and frameworks for analyzing cyber threats against existing IoT or low-power protocols have… More >

  • Open Access

    REVIEW

    A Review of Hybrid Cyber Threats Modelling and Detection Using Artificial Intelligence in IIoT

    Yifan Liu1, Shancang Li1,*, Xinheng Wang2, Li Xu3

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1233-1261, 2024, DOI:10.32604/cmes.2024.046473 - 20 May 2024

    Abstract The Industrial Internet of Things (IIoT) has brought numerous benefits, such as improved efficiency, smart analytics, and increased automation. However, it also exposes connected devices, users, applications, and data generated to cyber security threats that need to be addressed. This work investigates hybrid cyber threats (HCTs), which are now working on an entirely new level with the increasingly adopted IIoT. This work focuses on emerging methods to model, detect, and defend against hybrid cyber attacks using machine learning (ML) techniques. Specifically, a novel ML-based HCT modelling and analysis framework was proposed, in which regularisation and Random Forest were More >

  • Open Access

    ARTICLE

    Multiclass Classification for Cyber Threats Detection on Twitter

    Adnan Hussein1, Abdulwahab Ali Almazroi2,*

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3853-3866, 2023, DOI:10.32604/cmc.2023.040856 - 26 December 2023

    Abstract The advances in technology increase the number of internet systems usage. As a result, cybersecurity issues have become more common. Cyber threats are one of the main problems in the area of cybersecurity. However, detecting cybersecurity threats is not a trivial task and thus is the center of focus for many researchers due to its importance. This study aims to analyze Twitter data to detect cyber threats using a multiclass classification approach. The data is passed through different tasks to prepare it for the analysis. Term Frequency and Inverse Document Frequency (TFIDF) features are extracted… More >

  • Open Access

    ARTICLE

    Chinese Cyber Threat Intelligence Named Entity Recognition via RoBERTa-wwm-RDCNN-CRF

    Zhen Zhen1, Jian Gao1,2,*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 299-323, 2023, DOI:10.32604/cmc.2023.042090 - 31 October 2023

    Abstract In recent years, cyber attacks have been intensifying and causing great harm to individuals, companies, and countries. The mining of cyber threat intelligence (CTI) can facilitate intelligence integration and serve well in combating cyber attacks. Named Entity Recognition (NER), as a crucial component of text mining, can structure complex CTI text and aid cybersecurity professionals in effectively countering threats. However, current CTI NER research has mainly focused on studying English CTI. In the limited studies conducted on Chinese text, existing models have shown poor performance. To fully utilize the power of Chinese pre-trained language models… More >

  • Open Access

    ARTICLE

    Solar Power Plant Network Packet-Based Anomaly Detection System for Cybersecurity

    Ju Hyeon Lee1, Jiho Shin2, Jung Taek Seo3,*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 757-779, 2023, DOI:10.32604/cmc.2023.039461 - 31 October 2023

    Abstract As energy-related problems continue to emerge, the need for stable energy supplies and issues regarding both environmental and safety require urgent consideration. Renewable energy is becoming increasingly important, with solar power accounting for the most significant proportion of renewables. As the scale and importance of solar energy have increased, cyber threats against solar power plants have also increased. So, we need an anomaly detection system that effectively detects cyber threats to solar power plants. However, as mentioned earlier, the existing solar power plant anomaly detection system monitors only operating information such as power generation, making… More >

  • Open Access

    ARTICLE

    Attack Behavior Extraction Based on Heterogeneous Cyberthreat Intelligence and Graph Convolutional Networks

    Binhui Tang1,3, Junfeng Wang2,*, Huanran Qiu3, Jian Yu2, Zhongkun Yu2, Shijia Liu2,4

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 235-252, 2023, DOI:10.32604/cmc.2023.029135 - 22 September 2022

    Abstract The continuous improvement of the cyber threat intelligence sharing mechanism provides new ideas to deal with Advanced Persistent Threats (APT). Extracting attack behaviors, i.e., Tactics, Techniques, Procedures (TTP) from Cyber Threat Intelligence (CTI) can facilitate APT actors’ profiling for an immediate response. However, it is difficult for traditional manual methods to analyze attack behaviors from cyber threat intelligence due to its heterogeneous nature. Based on the Adversarial Tactics, Techniques and Common Knowledge (ATT&CK) of threat behavior description, this paper proposes a threat behavioral knowledge extraction framework that integrates Heterogeneous Text Network (HTN) and Graph Convolutional… More >

  • Open Access

    ARTICLE

    Generic Attribute Scoring for Information Decay in Threat Information Sharing Platform

    Mohammed Alshehri*

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 917-931, 2021, DOI:10.32604/cmc.2021.014848 - 12 January 2021

    Abstract Cyber Threat Intelligence (CTI) has gained massive attention to collect hidden knowledge for a better understanding of the various cyber-attacks and eventually paving the way for predicting the future of such attacks. The information exchange and collaborative sharing through different platforms have a significant contribution towards a global solution. While CTI and the information exchange can help a lot in focusing and prioritizing on the use of the large volume of complex information among different organizations, there exists a great challenge ineffective processing of large count of different Indicators of Threat (IoT) which appear regularly,… More >

  • Open Access

    ARTICLE

    Multilayer Self-Defense System to Protect Enterprise Cloud

    Shailendra Mishra, Sunil Kumar Sharma*, Majed A. Alowaidi

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 71-85, 2021, DOI:10.32604/cmc.2020.012475 - 30 October 2020

    Abstract A data breach can seriously impact organizational intellectual property, resources, time, and product value. The risk of system intrusion is augmented by the intrinsic openness of commonly utilized technologies like TCP/IP protocols. As TCP relies on IP addresses, an attacker may easily trace the IP address of the organization. Given that many organizations run the risk of data breach and cyber-attacks at a certain point, a repeatable and well-developed incident response framework is critical to shield them. Enterprise cloud possesses the challenges of security, lack of transparency, trust and loss of controls. Technology eases quickens… More >

  • Open Access

    ARTICLE

    Network Security Situation Awareness Framework based on Threat Intelligence

    Hongbin Zhang1, 2, Yuzi Yi1, *, Junshe Wang1, Ning Cao3, *, Qiang Duan4

    CMC-Computers, Materials & Continua, Vol.56, No.3, pp. 381-399, 2018, DOI:10.3970/cmc.2018.03787

    Abstract Network security situation awareness is an important foundation for network security management, which presents the target system security status by analyzing existing or potential cyber threats in the target system. In network offense and defense, the network security state of the target system will be affected by both offensive and defensive strategies. According to this feature, this paper proposes a network security situation awareness method using stochastic game in cloud computing environment, uses the utility of both sides of the game to quantify the network security situation value. This method analyzes the nodes based on… More >

Displaying 1-10 on page 1 of 10. Per Page