K. Raju^*, M. Chinnadurai

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1057-1072, 2021, DOI:10.32604/cmc.2021.016068 - 04 June 2021

Abstract Security is a critical issue in cloud computing (CC) because attackers can fabricate data by creating, copying, or deleting data with no user authorization. Most of the existing techniques make use of password-based authentication for encrypting data. Password-based schemes suffer from several issues and can be easily compromised. This paper presents a new concept of hybrid metaheuristic optimization as an identity-based secure and optimal authentication (HMO-ISOA) scheme for CC environments. The HMO-ISOA technique makes use of iris and fingerprint biometrics. Initially, the HMO-ISOA technique involves a directional local ternary quantized extrema pattern–based feature extraction process… More >

Xiajiong Shen^1,3, Shuaimin Jiang^2,3, Lei Zhang^1,2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.3, pp. 1069-1085, 2021, DOI:10.32604/cmes.2021.015736 - 24 May 2021

Abstract The emergence of smart contracts has increased the attention of industry and academia to blockchain technology, which is tamper-proofing, decentralized, autonomous, and enables decentralized applications to operate in untrustworthy environments. However, these features of this technology are also easily exploited by unscrupulous individuals, a typical example of which is the Ponzi scheme in Ethereum. The negative effect of unscrupulous individuals writing Ponzi scheme-type smart contracts in Ethereum and then using these contracts to scam large amounts of money has been significant. To solve this problem, we propose a detection model for detecting Ponzi schemes in… More >

Yang Liu¹, Shan Zhao^1,*, 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 - 19 May 2021

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 >

Syeda Warda Asher¹, Sadeeq Jan^1,*, George Tsaramirsis², Fazal Qudus Khan³, Abdullah Khalil¹, Muhammad Obaidullah⁴

Computer Systems Science and Engineering, Vol.38, No.3, pp. 265-278, 2021, DOI:10.32604/csse.2021.016787 - 19 May 2021

Abstract Software reverse engineering is the process of analyzing a software system to extract the design and implementation details. Reverse engineering provides the source code of an application, the insight view of the architecture and the third-party dependencies. From a security perspective, it is mostly used for finding vulnerabilities and attacking or cracking an application. The process is carried out either by obtaining the code in plaintext or reading it through the binaries or mnemonics. Nowadays, reverse engineering is widely used for mobile applications and is considered a security risk. The Open Web Application Security Project… More >

Omer Bin Tauqeer¹, Sadeeq Jan^1,*, Alaa Omar Khadidos², Adil Omar Khadidos³, Fazal Qudus Khan³, Sana Khattak¹

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 291-306, 2021, DOI:10.32604/iasc.2021.017260 - 12 May 2021

Abstract In the past decades, a significant increase has been observed in cyber-attacks on the web-based systems used for financial purposes. Such individual systems often contain security weaknesses, called vulnerabilities that can be exploited for malicious purposes. The exploitation of such vulnerabilities can result in disclosure and manipulation of sensitive data as well as have destructive effects. To protect such systems, security testing is required on a periodic basis. Various detection and assessment techniques have been suggested by developers and researchers to address these security issues. In this paper, we survey the contributions of academia in… More >

Nojood O. Aljehane^*

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3915-3929, 2021, DOI:10.32604/cmc.2021.017905 - 06 May 2021

Abstract Cyber physical systems (CPSs) are a networked system of cyber (computation, communication) and physical (sensors, actuators) elements that interact in a feedback loop with the assistance of human interference. Generally, CPSs authorize critical infrastructures and are considered to be important in the daily lives of humans because they form the basis of future smart devices. Increased utilization of CPSs, however, poses many threats, which may be of major significance for users. Such security issues in CPSs represent a global issue; therefore, developing a robust, secure, and effective CPS is currently a hot research topic. To… More >

Thavavel Vaiyapuri^*, Adel Binbusayyis

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3271-3288, 2021, DOI:10.32604/cmc.2021.017665 - 06 May 2021

Abstract In the era of Big data, learning discriminant feature representation from network traffic is identified has as an invariably essential task for improving the detection ability of an intrusion detection system (IDS). Owing to the lack of accurately labeled network traffic data, many unsupervised feature representation learning models have been proposed with state-of-the-art performance. Yet, these models fail to consider the classification error while learning the feature representation. Intuitively, the learnt feature representation may degrade the performance of the classification task. For the first time in the field of intrusion detection, this paper proposes an… More >

Sajid Habib Gill¹, Noor Ahmed Sheikh¹, Samina Rajpar¹, Zain ul Abidin², N. Z. Jhanjhi^3,*, 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 - 06 May 2021

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 >

Le Lai^1,*,Tongqing Zhou¹, Zhiping Cai¹, Zhiyao Liang², Hao Bai¹

Journal of Cyber Security, Vol.3, No.1, pp. 29-44, 2021, DOI:10.32604/jcs.2021.016349 - 30 April 2021

Abstract Bitcoin is known as the first decentralized digital currency around the world. It uses blockchain technology to store transaction data in a distributed public ledger, is a distributed ledger that removes third-party trust institutions. Since its invention, bitcoin has achieved great success, has a market value of about $200 billion. However, while bitcoin has brought a wide and far-reaching impact in the financial field, it has also exposed some security problems, such as selfish mining attacks, Sybil attack, eclipse attacks, routing attacks, EREBUS attacks, and so on. This paper gives a comprehensive overview of various More >

Meng Wang^*

International Journal of Mental Health Promotion, Vol.23, No.2, pp. 177-187, 2021, DOI:10.32604/IJMHP.2021.016466 - 30 April 2021

Abstract Purpose: Little is known about the role of food insecurity (FIS) on depressive symptoms among adolescents. Thus, this study aimed to explore the association between FIS and depressive symptoms among adolescents aged 12–15 years from low- and middle-income countries across the world. Methods: Data from the Global school-based Student Health Survey were analyzed in 51,702 adolescents [mean (SD) age 13.8 (1.0) years; 49.3% girls). Self-reported measures assessed depressive symptoms during the past 12 months, and food insecurity. Participants reporting yes for depressive symptoms. FIS was categorized into five levels, including ‘never’, ‘rarely’, ‘sometimes’, ‘most of the… More >