Xiabin Zhang^1,2, Zhongyi Hu^1,2,*, Lei Xiao^1,2, Hui Huang^1,2

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2879-2905, 2024, DOI:10.32604/cmc.2024.048725

Abstract Various deep learning models have been proposed for the accurate assisted diagnosis of early-stage Alzheimer’s disease (AD). Most studies predominantly employ Convolutional Neural Networks (CNNs), which focus solely on local features, thus encountering difficulties in handling global features. In contrast to natural images, Structural Magnetic Resonance Imaging (sMRI) images exhibit a higher number of channel dimensions. However, during the Position Embedding stage of Multi Head Self Attention (MHSA), the coded information related to the channel dimension is disregarded. To tackle these issues, we propose the RepBoTNet-CESA network, an advanced AD-aided diagnostic model that is capable… More >

Yutao Hu¹, Yuntao Zhao^1,*, Yongxin Feng², Xiangyu Ma¹

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 509-530, 2024, DOI:10.32604/cmc.2024.042216

Abstract In the face of the increasingly severe Botnet problem on the Internet, how to effectively detect Botnet traffic in real-time has become a critical problem. Although the existing deep Q network (DQN) algorithm in Deep reinforcement learning can solve the problem of real-time updating, its prediction results are always higher than the actual results. In Botnet traffic detection, although it performs well in the training set, the accuracy rate of predicting traffic is as high as%; however, in the test set, its accuracy has declined, and it is impossible to adjust its prediction strategy on… More >

Ashraf S. Mashaleh^1,2,*, Noor Farizah Binti Ibrahim¹, Mohammad Alauthman³, Mohammad Almseidin⁴, Amjad Gawanmeh⁵

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2245-2267, 2024, DOI:10.32604/cmc.2023.047323

Abstract Increasing Internet of Things (IoT) device connectivity makes botnet attacks more dangerous, carrying catastrophic hazards. As IoT botnets evolve, their dynamic and multifaceted nature hampers conventional detection methods. This paper proposes a risk assessment framework based on fuzzy logic and Particle Swarm Optimization (PSO) to address the risks associated with IoT botnets. Fuzzy logic addresses IoT threat uncertainties and ambiguities methodically. Fuzzy component settings are optimized using PSO to improve accuracy. The methodology allows for more complex thinking by transitioning from binary to continuous assessment. Instead of expert inputs, PSO data-driven tunes rules and membership More >

Mamona Arshad¹, Ahmad Karim¹, Salman Naseer², Shafiq Ahmad³, Mejdal Alqahtani³, Akber Abid Gardezi⁴, Muhammad Shafiq^5,*, Jin-Ghoo Choi⁵

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2123-2135, 2023, DOI:10.32604/cmc.2022.028680

Abstract The exponential growth in the development of smartphones and handheld devices is permeated due to everyday activities i.e., games applications, entertainment, online banking, social network sites, etc., and also allow the end users to perform a variety of activities. Because of activities, mobile devices attract cybercriminals to initiate an attack over a diverse range of malicious activities such as theft of unauthorized information, phishing, spamming, Distributed Denial of Services (DDoS), and malware dissemination. Botnet applications are a type of harmful attack that can be used to launch malicious activities and has become a significant threat… More >

Donghyun Kim¹, Seungho Jeon², Jiho Shin³, Jung Taek Seo^4,*

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2979-2997, 2023, DOI:10.32604/iasc.2023.040019

Abstract The smart city comprises various infrastructures, including healthcare, transportation, manufacturing, and energy. A smart city’s Internet of Things (IoT) environment constitutes a massive IoT environment encompassing numerous devices. As many devices are installed, managing security for the entire IoT device ecosystem becomes challenging, and attack vectors accessible to attackers increase. However, these devices often have low power and specifications, lacking the same security features as general Information Technology (IT) systems, making them susceptible to cyberattacks. This vulnerability is particularly concerning in smart cities, where IoT devices are connected to essential support systems such as healthcare… More >

Yi Qing¹, Xiangyu Liu², Yanhui Du^2,*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2095-2119, 2023, DOI:10.32604/cmc.2023.039980

Abstract Distributed Denial of Service (DDoS) attacks have always been a major concern in the security field. With the release of malware source codes such as BASHLITE and Mirai, Internet of Things (IoT) devices have become the new source of DDoS attacks against many Internet applications. Although there are many datasets in the field of IoT intrusion detection, such as Bot-IoT, Constrained Application Protocol–Denial of Service (CoAP-DoS), and LATAM-DDoS-IoT (some of the names of DDoS datasets), which mainly focus on DDoS attacks, the datasets describing new IoT DDoS attack scenarios are extremely rare, and only N-BaIoT… More >

Muhammad Waqas Nadeem^1,*, Hock Guan Goh¹, Yichiet Aun¹, Vasaki Ponnusamy²

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2201-2217, 2023, DOI:10.32604/csse.2023.039893

Abstract Over the past few years, rapid advancements in the internet and communication technologies have led to increasingly intricate and diverse networking systems. As a result, greater intelligence is necessary to effectively manage, optimize, and maintain these systems. Due to their distributed nature, machine learning models are challenging to deploy in traditional networks. However, Software-Defined Networking (SDN) presents an opportunity to integrate intelligence into networks by offering a programmable architecture that separates data and control planes. SDN provides a centralized network view and allows for dynamic updates of flow rules and software-based traffic analysis. While the… More >

Ebu Yusuf GÜVEN, Zeynep GÜRKAŞ-AYDIN^*

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 419-437, 2023, DOI:10.32604/iasc.2023.038043

Abstract The Internet of Things (IoT) has aided in the development of new products and services. Due to the heterogeneity of IoT items and networks, traditional techniques cannot identify network risks. Rule-based solutions make it challenging to secure and manage IoT devices and services due to their diversity. While the use of artificial intelligence eliminates the need to define rules, the training and retraining processes require additional processing power. This study proposes a methodology for analyzing constrained devices in IoT environments. We examined the relationship between different sized samples from the Kitsune dataset to simulate the… More >

Arkan Hammoodi Hasan Kabla, Mohammed Anbar, Selvakumar Manickam, Alwan Ahmed Abdulrahman Alwan, Shankar Karuppayah^*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3375-3398, 2023, DOI:10.32604/cmc.2023.036587

Abstract The cyber-criminal compromises end-hosts (bots) to configure a network of bots (botnet). The cyber-criminals are also looking for an evolved architecture that makes their techniques more resilient and stealthier such as Peer-to-Peer (P2P) networks. The P2P botnets leverage the privileges of the decentralized nature of P2P networks. Consequently, the P2P botnets exploit the resilience of this architecture to be arduous against take-down procedures. Some P2P botnets are smarter to be stealthy in their Command-and-Control mechanisms (C2) and elude the standard discovery mechanisms. Therefore, the other side of this cyberwar is the monitor. The P2P botnet… More >

Saeed Masoud Alshahrani¹, Fatma S. Alrayes², Hamed Alqahtani³, Jaber S. Alzahrani⁴, Mohammed Maray⁵, Sana Alazwari⁶, Mohamed A. Shamseldin⁷, Mesfer Al Duhayyim^8,*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3085-3100, 2023, DOI:10.32604/cmc.2023.032972

Abstract Nowadays, Internet of Things (IoT) has penetrated all facets of human life while on the other hand, IoT devices are heavily prone to cyberattacks. It has become important to develop an accurate system that can detect malicious attacks on IoT environments in order to mitigate security risks. Botnet is one of the dreadful malicious entities that has affected many users for the past few decades. It is challenging to recognize Botnet since it has excellent carrying and hidden capacities. Various approaches have been employed to identify the source of Botnet at earlier stages. Machine Learning… More >