Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (225)
  • Open Access

    ARTICLE

    An Efficient Lightweight Authentication and Key Agreement Protocol for Patient Privacy

    Seyed Amin Hosseini Seno1, Mahdi Nikooghadam1, Rahmat Budiarto2,*

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3495-3512, 2021, DOI:10.32604/cmc.2021.019051

    Abstract Tele-medical information system provides an efficient and convenient way to connect patients at home with medical personnel in clinical centers. In this system, service providers consider user authentication as a critical requirement. To address this crucial requirement, various types of validation and key agreement protocols have been employed. The main problem with the two-way authentication of patients and medical servers is not built with thorough and comprehensive analysis that makes the protocol design yet has flaws. This paper analyzes carefully all aspects of security requirements including the perfect forward secrecy in order to develop an… More >

  • Open Access

    ARTICLE

    Towards Privacy-Preserving Cloud Storage: A Blockchain Approach

    Jia-Shun Zhang1, Gang Xu2,*, Xiu-Bo Chen1, Haseeb Ahmad3, Xin Liu4, Wen Liu5,6,7

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 2903-2916, 2021, DOI:10.32604/cmc.2021.017227

    Abstract With the rapid development of cloud computing technology, cloud services have now become a new business model for information services. The cloud server provides the IT resources required by customers in a self-service manner through the network, realizing business expansion and rapid innovation. However, due to the insufficient protection of data privacy, the problem of data privacy leakage in cloud storage is threatening cloud computing. To address the problem, we propose BC-PECK, a data protection scheme based on blockchain and public key searchable encryption. Firstly, all the data is protected by the encryption algorithm. The… More >

  • Open Access

    ARTICLE

    A Smart Comparative Analysis for Secure Electronic Websites

    Sobia Wassan1, Chen Xi1,*, Nz Jhanjhi2, Hassan Raza3

    Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 187-199, 2021, DOI:10.32604/iasc.2021.015859

    Abstract Online banking is an ideal method for conducting financial transactions such as e-commerce, e-banking, and e-payments. The growing popularity of online payment services and payroll systems, however, has opened new pathways for hackers to steal consumers’ information and money, a risk which poses significant danger to the users of e-commerce and e-banking websites. This study uses the selection method of the entire e-commerce and e-banking website dataset (Chi-Squared, Gini index, and main learning algorithm). The results of the analysis suggest the identification and comparison of machine learning and deep learning algorithm performance on binary category… More >

  • Open Access

    ARTICLE

    Security and Privacy in 5G Internet of Vehicles (IoV) Environment

    Benjamin Kwapong Osibo1, Chengbo Zhang1, Changsen Xia1, Guanzhe Zhao2, Zilong Jin1,3,*

    Journal on Internet of Things, Vol.3, No.2, pp. 77-86, 2021, DOI:10.32604/jiot.2021.017943

    Abstract Modern vehicles are equipped with sensors, communication, and computation units that make them capable of providing monitoring services and analysis of real-time traffic information to improve road safety. The main aim of communication in vehicular networks is to achieve an autonomous driving environment that is accident-free alongside increasing road use quality. However, the demanding specifications such as high data rate, low latency, and high reliability in vehicular networks make 5G an emerging solution for addressing the current vehicular network challenges. In the 5G IoV environment, various technologies and models are deployed, making the environment open More >

  • Open Access

    ARTICLE

    Machine Learning Based Framework for Maintaining Privacy of Healthcare Data

    Adil Hussain Seh1, Jehad F. Al-Amri2, Ahmad F. Subahi3, Alka Agrawal1, Rajeev Kumar4,*, Raees Ahmad Khan1

    Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 697-712, 2021, DOI:10.32604/iasc.2021.018048

    Abstract The Adoption of Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), cloud services, web-based software systems, and other wireless sensor devices in the healthcare infrastructure have led to phenomenal improvements and benefits in the healthcare sector. Digital healthcare has ensured early diagnosis of the diseases, greater accessibility, and mass outreach in terms of treatment. Despite this unprecedented success, the privacy and confidentiality of the healthcare data have become a major concern for all the stakeholders. Data breach reports reveal that the healthcare data industry is one of the key targets of cyber invaders.… More >

  • Open Access

    ARTICLE

    Trust Management-Based Service Recovery and Attack Prevention in MANET

    V. Nivedita1,*, N. Nandhagopal2

    Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 771-786, 2021, DOI:10.32604/iasc.2021.017547

    Abstract The mobile ad-hoc network (MANET) output is critically impaired by the versatility and resource constraint of nodes. Node mobility affects connection reliability, and node resource constraints can lead to congestion, which makes the design of a routing MANET protocol with quality of service (QoS) very difficult. An adaptive clustering reputation model (ACRM) method is proposed to improve energy efficiency with a cluster-based framework. The proposed framework is employed to overcome the problems of data protection, privacy, and policy. The proposed ACRM-MRT approach that includes direct and indirect node trust computation is introduced along with the… More >

  • Open Access

    ARTICLE

    Pseudonym Mutable Based Privacy for 5G User Identity

    Rashid A. Saeed1, Mamoon M. Saeed2,3, Rania A. Mokhtar1, Hesham Alhumyani1, S. Abdel-Khalek4,*

    Computer Systems Science and Engineering, Vol.39, No.1, pp. 1-14, 2021, DOI:10.32604/csse.2021.015593

    Abstract Privacy, identity preserving and integrity have become key problems for telecommunication standards. Significant privacy threats are expected in 5G networks considering the large number of devices that will be deployed. As Internet of Things (IoT) and long-term evolution for machine type (LTE-m) are growing very fast with massive data traffic the risk of privacy attacks will be greatly increase. For all the above issues standards’ bodies should ensure users’ identity and privacy in order to gain the trust of service providers and industries. Against such threats, 5G specifications require a rigid and robust privacy procedure.… More >

  • Open Access

    ARTICLE

    NVM Storage in IoT Devices: Opportunities and Challenges

    Yang Liu1, Shan Zhao1,*, Wenhan Chen1, Xuran Ge1, Fang Liu2, Shuo Li3, Nong Xiao1

    Computer Systems Science and Engineering, Vol.38, No.3, pp. 393-409, 2021, DOI:10.32604/csse.2021.017224

    Abstract Edge storage stores the data directly at the data collection point, and does not need to transmit the collected data to the storage central server through the network. It is a critical technology that supports applications such as edge computing and 5G network applications, with lower network communication overhead, lower interaction delay and lower bandwidth cost. However, with the explosion of data and higher real-time requirements, the traditional Internet of Things (IoT) storage architecture cannot meet the requirements of low latency and large capacity. Non-volatile memory (NVM) presents new possibilities regarding this aspect. This paper More >

  • Open Access

    ARTICLE

    A Secure Rotation Invariant LBP Feature Computation in Cloud Environment

    Shiqi Wang1, Mingfang Jiang2,*, Jiaohua Qin1, Hengfu Yang2, Zhichen Gao3

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2979-2993, 2021, DOI:10.32604/cmc.2021.017094

    Abstract In the era of big data, outsourcing massive data to a remote cloud server is a promising approach. Outsourcing storage and computation services can reduce storage costs and computational burdens. However, public cloud storage brings about new privacy and security concerns since the cloud servers can be shared by multiple users. Privacy-preserving feature extraction techniques are an effective solution to this issue. Because the Rotation Invariant Local Binary Pattern (RILBP) has been widely used in various image processing fields, we propose a new privacy-preserving outsourcing computation of RILBP over encrypted images in this paper (called More >

  • Open Access

    ARTICLE

    Extended Forgery Detection Framework for COVID-19 Medical Data Using Convolutional Neural Network

    Sajid Habib Gill1, Noor Ahmed Sheikh1, Samina Rajpar1, Zain ul Abidin2, N. Z. Jhanjhi3,*, Muneer Ahmad4, Mirza Abdur Razzaq1, Sultan S. Alshamrani5, Yasir Malik6, Fehmi Jaafar7

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3773-3787, 2021, DOI:10.32604/cmc.2021.016001

    Abstract Medical data tampering has become one of the main challenges in the field of secure-aware medical data processing. Forgery of normal patients’ medical data to present them as COVID-19 patients is an illegitimate action that has been carried out in different ways recently. Therefore, the integrity of these data can be questionable. Forgery detection is a method of detecting an anomaly in manipulated forged data. An appropriate number of features are needed to identify an anomaly as either forged or non-forged data in order to find distortion or tampering in the original data. Convolutional neural… More >

Displaying 151-160 on page 16 of 225. Per Page