Amir Haider¹, Muhammad Adnan Khan², Abdur Rehman³, Muhib Ur Rahman⁴, Hyung Seok Kim^1,*

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1785-1798, 2021, DOI:10.32604/cmc.2020.013910

Abstract In recent years, cybersecurity has attracted significant interest due to the rapid growth of the Internet of Things (IoT) and the widespread development of computer infrastructure and systems. It is thus becoming particularly necessary to identify cyber-attacks or irregularities in the system and develop an efficient intrusion detection framework that is integral to security. Researchers have worked on developing intrusion detection models that depend on machine learning (ML) methods to address these security problems. An intelligent intrusion detection device powered by data can exploit artificial intelligence (AI), and especially ML, techniques. Accordingly, we propose in this article an intrusion detection… More >

Abdulaziz Attaallah¹, Abdullah Algarni¹, Raees Ahmad Khan^2,*

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1849-1865, 2021, DOI:10.32604/cmc.2020.013854

Abstract The advanced technological need, exacerbated by the flexible time constraints, leads to several more design level unexplored vulnerabilities. Security is an extremely vital component in software development; we must take charge of security and therefore analysis of software security risk assumes utmost significance. In order to handle the cyber-security risk of the web application and protect individuals, information and properties effectively, one must consider what needs to be secured, what are the perceived threats and the protection of assets. Security preparation plans, implements, tracks, updates and consistently develops safety risk management activities. Risk management must be interpreted as the major… More >

Eunmok Yang¹, Gyanendra Prasad Joshi², Changho Seo^3,*

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1647-1663, 2021, DOI:10.32604/cmc.2020.013210

Abstract In network-based intrusion detection practices, there are more regular instances than intrusion instances. Because there is always a statistical imbalance in the instances, it is difficult to train the intrusion detection system effectively. In this work, we compare intrusion detection performance by increasing the rarely appearing instances rather than by eliminating the frequently appearing duplicate instances. Our technique mitigates the statistical imbalance in these instances. We also carried out an experiment on the training model by increasing the instances, thereby increasing the attack instances step by step up to 13 levels. The experiments included not only known attacks, but also… More >

Rosilah Hassan¹, Selver Pepic², Muzafer Saracevic³, Khaleel Ahmad^4,*, Milan Tasic⁵

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1139-1153, 2021, DOI:10.32604/cmc.2020.013104

Abstract In this paper, we provide a new approach to data encryption using generalized inverses. Encryption is based on the implementation of weighted Moore–Penrose inverse A^†_MN(nxm) over the nx8 constant matrix. The square Hermitian positive definite matrix N_8x8 p is the key. The proposed solution represents a very strong key since the number of different variants of positive definite matrices of order 8 is huge. We have provided NIST (National Institute of Standards and Technology) quality assurance tests for a random generated Hermitian matrix (a total of 10 different tests and additional analysis with approximate entropy and random digression). In the… More >

Naveed Ul Mushtaq¹, Seerat Saleem¹, Aadil Rasool¹, Wasifa Hafiz Shah¹, Khalid Rehman Hakeem^2,*, Reiaz Ul Rehman^1,*

Phyton-International Journal of Experimental Botany, Vol.90, No.1, pp. 51-64, 2021, DOI:10.32604/phyton.2020.012163

Abstract

Millets hold an immense assurance for food safety and nourishment amid ever-rising agricultural expenses and climate alterations. They are healthful, have supplementary wellbeing profit and need remarkably fewer effort overheads for crop growing. These characters draw attention to millets as a plant of preference for the humankind in the course of emergent alarm about environmental changes. Millets have the prospect to provide biomass and thus bioenergy, reduced carbon emission, carbon footprint and sustainable modern agriculture. As the rate of expansion in budding countries is increasing day by day, the scarcity of energy is a big panic and there is a… More >

Sivaranjani Balakrishnan^1,∗, D. Surendran^2,†

Computer Systems Science and Engineering, Vol.35, No.5, pp. 357-366, 2020, DOI:10.32604/csse.2020.35.357

Abstract With the arrival of on-demand computing, data centre requirements are extensive, with fluid boundaries. Loaded Internet applications, service-oriented architectures, virtualization and security provisioning are the major operations of a data centre. Security is an absolute necessity of any network architecture, and the virtual IT data centre is no exception. At the boundary, security is focused on securing the terminals of the data centre from external threats and providing a secure gateway to the Internet. The paradigm shift towards a new computing environment makes communications more complicated for Infrastructure Providers (InP). This complexity includes the security of the data centre’s components… More >

Sadeeq Jan^1,*, Omer Bin Tauqeer¹, Fazal Qudus Khan², George Tsaramirsis², Awais Ahmad³, Iftikhar Ahmad⁴, Imran Maqsood⁵, Niamat Ullah⁶

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 631-645, 2021, DOI:10.32604/cmc.2020.012831

Abstract Over the last decade, a significant increase has been observed in the use of web-based Information systems that process sensitive information, e.g., personal, financial, medical. With this increased use, the security of such systems became a crucial aspect to ensure safety, integrity and authenticity of the data. To achieve the objectives of data safety, security testing is performed. However, with growth and diversity of information systems, it is challenging to apply security testing for each and every system. Therefore, it is important to classify the assets based on their required level of security using an appropriate technique. In this paper,… More >

Gia Nhu Nguyen^1,2, Nin Ho Le Viet^1,2, Gyanendra Prasad Joshi³, Bhanu Shrestha^4,*

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 551-562, 2021, DOI:10.32604/cmc.2020.012441

Abstract Fog computing in the Internet of Health Things (IoHT) is promising owing to the increasing need for energy- and latency-optimized health sector provisioning. Additionally, clinical data (particularly, medical image data) are a delicate, highly protected resource that should be utilized in an effective and responsible manner to fulfil consumer needs. Herein, we propose an energy-effi- cient fog-based IoHT with a tunicate swarm-optimization-(TSO)-based lightweight Simon cipher to enhance the energy efficiency at the fog layer and the security of data stored at the cloud server. The proposed Simon cipher uses the TSO algorithm to select the optimal keys that will minimize… More >

Muhammad Adnan Khan^1,*, Abdur Rehman², Khalid Masood Khan¹, Mohammed A. Al Ghamdi³, Sultan H. Almotiri³

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 467-480, 2021, DOI:10.32604/cmc.2020.013121

Abstract Networks provide a significant function in everyday life, and cybersecurity therefore developed a critical field of study. The Intrusion detection system (IDS) becoming an essential information protection strategy that tracks the situation of the software and hardware operating on the network. Notwithstanding advancements of growth, current intrusion detection systems also experience dif- ficulties in enhancing detection precision, growing false alarm levels and identifying suspicious activities. In order to address above mentioned issues, several researchers concentrated on designing intrusion detection systems that rely on machine learning approaches. Machine learning models will accurately identify the underlying variations among regular information and irregular… More >

Tao Li¹, Yongjin Hu^1,*, Ankang Ju¹, Zhuoran Hu²

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 407-420, 2021, DOI:10.32604/cmc.2020.012023

Abstract Owing to the continuous barrage of cyber threats, there is a massive amount of cyber threat intelligence. However, a great deal of cyber threat intelligence come from textual sources. For analysis of cyber threat intelligence, many security analysts rely on cumbersome and time-consuming manual efforts. Cybersecurity knowledge graph plays a significant role in automatics analysis of cyber threat intelligence. As the foundation for constructing cybersecurity knowledge graph, named entity recognition (NER) is required for identifying critical threat-related elements from textual cyber threat intelligence. Recently, deep neural network-based models have attained very good results in NER. However, the performance of these… More >