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  • Open Access

    ARTICLE

    Security and Privacy Frameworks for Access Control Big Data Systems

    Paolina Centonze1,*

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 361-374, 2019, DOI:10.32604/cmc.2019.06223

    Abstract In the security and privacy fields, Access Control (AC) systems are viewed as the fundamental aspects of networking security mechanisms. Enforcing AC becomes even more challenging when researchers and data analysts have to analyze complex and distributed Big Data (BD) processing cluster frameworks, which are adopted to manage yottabyte of unstructured sensitive data. For instance, Big Data systems’ privacy and security restrictions are most likely to failure due to the malformed AC policy configurations. Furthermore, BD systems were initially developed toped to take care of some of the DB issues to address BD challenges and… More >

  • Open Access

    ARTICLE

    Reversible Data Hiding in Encrypted Image Based on Block Classification Permutation

    Qun Mo1, Heng Yao1, Fang Cao2, Zheng Chang3, Chuan Qin1,*

    CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 119-133, 2019, DOI:10.32604/cmc.2019.05770

    Abstract Recently, reversible data hiding in encrypted image (RDHEI) has attracted extensive attention, which can be used in secure cloud computing and privacy protection effectively. In this paper, a novel RDHEI scheme based on block classification and permutation is proposed. Content owner first divides original image into non-overlapping blocks and then set a threshold to classify these blocks into smooth and non-smooth blocks respectively. After block classification, content owner utilizes a specific encryption method, including stream cipher encryption and block permutation to protect image content securely. For the encrypted image, data hider embeds additional secret information… More >

  • Open Access

    ARTICLE

    DPIF: A Framework for Distinguishing Unintentional Quality Problems From Potential Shilling Attacks

    Mohan Li1, Yanbin Sun1, *, Shen Su1, Zhihong Tian1, Yuhang Wang1, *, Xianzhi Wang2

    CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 331-344, 2019, DOI:10.32604/cmc.2019.05379

    Abstract Maliciously manufactured user profiles are often generated in batch for shilling attacks. These profiles may bring in a lot of quality problems but not worthy to be repaired. Since repairing data always be expensive, we need to scrutinize the data and pick out the data that really deserves to be repaired. In this paper, we focus on how to distinguish the unintentional data quality problems from the batch generated fake users for shilling attacks. A two-steps framework named DPIF is proposed for the distinguishment. Based on the framework, the metrics of homology and suspicious degree More >

  • Open Access

    ARTICLE

    Image Augmentation-Based Food Recognition with Convolutional Neural Networks

    Lili Pan1, Jiaohua Qin1,*, Hao Chen2, Xuyu Xiang1, Cong Li1, Ran Chen1

    CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 297-313, 2019, DOI:10.32604/cmc.2019.04097

    Abstract Image retrieval for food ingredients is important work, tremendously tiring, uninteresting, and expensive. Computer vision systems have extraordinary advancements in image retrieval with CNNs skills. But it is not feasible for small-size food datasets using convolutional neural networks directly. In this study, a novel image retrieval approach is presented for small and medium-scale food datasets, which both augments images utilizing image transformation techniques to enlarge the size of datasets, and promotes the average accuracy of food recognition with state-of-the-art deep learning technologies. First, typical image transformation techniques are used to augment food images. Then transfer More >

  • Open Access

    ARTICLE

    Anti-JPEG Compression Steganography Based on the High Tense Region Locating Method

    Yang Wu1, Weiping Shang2,*, Jiahao Chen3

    CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 199-214, 2019, DOI:10.32604/cmc.2019.05194

    Abstract Robust data hiding techniques attempt to construct covert communication in a lossy public channel. Nowadays, the existing robust JPEG steganographic algorithms cannot overcome the side-information missing situation. Thus, this paper proposes a new robust JPEG steganographic algorithm based on the high tense region location method which needs no side-information of lossy channel. First, a tense region locating method is proposed based on the Harris-Laplacian feature point. Then, robust cover object generating processes are described. Last, the advanced embedding cost function is proposed. A series of experiments are conducted on various JPEG image sets and the More >

  • Open Access

    ARTICLE

    On Hiding Secret Information in Medium Frequency DCT Components Using Least Significant Bits Steganography

    Sahib Khan1,*, M A Irfan1, Arslan Arif1, Syed Tahir Hussain Rizvi2, Asma Gul3, Muhammad Naeem4, Nasir Ahmad5

    CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.3, pp. 529-546, 2019, DOI:10.31614/cmes.2019.06179

    Abstract This work presents a new method of data hiding in digital images, in discrete cosine transform domain. The proposed method uses the least significant bits of the medium frequency components of the cover image for hiding the secret information, while the low and high frequency coefficients are kept unaltered. The unaltered low frequency DCT coefficients preserves the quality of the smooth region of the cover image, while no changes in the high DCT coefficient preserve the quality of the edges. As the medium frequency components have less contribution towards energy and image details, so the… More >

  • Open Access

    ARTICLE

    A Heterogeneous Virtual Machines Resource Allocation Scheme in Slices Architecture of 5G Edge Datacenter

    Changming Zhao1,2,*, Tiejun Wang2, Alan Yang3

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 423-437, 2019, DOI:10.32604/cmc.2019.07501

    Abstract In the paper, we investigate the heterogeneous resource allocation scheme for virtual machines with slicing technology in the 5G/B5G edge computing environment. In general, the different slices for different task scenarios exist in the same edge layer synchronously. A lot of researches reveal that the virtual machines of different slices indicate strong heterogeneity with different reserved resource granularity. In the condition, the allocation process is a NP hard problem and difficult for the actual demand of the tasks in the strongly heterogeneous environment. Based on the slicing and container concept, we propose the resource allocation… More >

  • Open Access

    ARTICLE

    Application of Self-Organizing Feature Map Neural Network Based on K-means Clustering in Network Intrusion Detection

    Ling Tan1,*, Chong Li2, Jingming Xia2, Jun Cao3

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 275-288, 2019, DOI:10.32604/cmc.2019.03735

    Abstract Due to the widespread use of the Internet, customer information is vulnerable to computer systems attack, which brings urgent need for the intrusion detection technology. Recently, network intrusion detection has been one of the most important technologies in network security detection. The accuracy of network intrusion detection has reached higher accuracy so far. However, these methods have very low efficiency in network intrusion detection, even the most popular SOM neural network method. In this paper, an efficient and fast network intrusion detection method was proposed. Firstly, the fundamental of the two different methods are introduced More >

  • Open Access

    ARTICLE

    Semantics Analytics of Origin-Destination Flows from Crowd Sensed Big Data

    Ning Cao1,2, Shengfang Li1, Keyong Shen1, Sheng Bin3, Gengxin Sun3,*, Dongjie Zhu4, Xiuli Han5, Guangsheng Cao5, Abraham Campbell6

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 227-241, 2019, DOI:10.32604/cmc.2019.06125

    Abstract Monitoring, understanding and predicting Origin-destination (OD) flows in a city is an important problem for city planning and human activity. Taxi-GPS traces, acted as one kind of typical crowd sensed data, it can be used to mine the semantics of OD flows. In this paper, we firstly construct and analyze a complex network of OD flows based on large-scale GPS taxi traces of a city in China. The spatiotemporal analysis for the OD flows complex network showed that there were distinctive patterns in OD flows. Then based on a novel complex network model, a semantics More >

  • Open Access

    ARTICLE

    Credit Card Fraud Detection Based on Machine Learning

    Yong Fang1, Yunyun Zhang2, Cheng Huang1,*

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 185-195, 2019, DOI:10.32604/cmc.2019.06144

    Abstract In recent years, the rapid development of e-commerce exposes great vulnerabilities in online transactions for fraudsters to exploit. Credit card transactions take a salient role in nowadays’ online transactions for its obvious advantages including discounts and earning credit card points. So credit card fraudulence has become a target of concern. In order to deal with the situation, credit card fraud detection based on machine learning is been studied recently. Yet, it is difficult to detect fraudulent transactions due to data imbalance (normal and fraudulent transactions), for which Smote algorithm is proposed in order to resolve… More >

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