Turkish Journal of Computer and Mathematics Education (TURCOMAT)
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A ROBUST CYBER SECURITY THREAT DETECTION MODEL USING ARTIFICIAL INTELLIGENCE TECHNOLOGY
No full textThe difficulty of ensuring cyber-security is steadily growing as a result of the alarming development in computer connectivity and the sizeable number of applications associated to computers in recent years. The system also requires robust defines against the growing number of cyber threats. As a result, a possible role for cyber-security might be performed by developing intrusion detection systems (ids) to detect inconsistencies and threats in computer networks. An effective data-driven intrusion detection system has been created with the use of artificial intelligence, particularly machine learning techniques. This research proposes a novel twin support vector machine (tsvm) based security model which first considers the security features ranking according to their relevance before developing an ids model based on the significant features that have been selected. By lowering the feature dimensions, this approach not only improves predictive performance for unidentified tests but also lowers the model\u27s computational expense. Trials are conducted using four common ml techniques to compare the results to those of the current approaches (decision tree, random decision forest, random tree, and artificial neural network). The experimental findings of this study confirm that the suggested methods may be used as learning-based models for network intrusion detection and demonstrate that, when used in the real world, they outperform conventional ml techniques
Enhanced Secure Communication Protocol with Pipelined Advanced Encryption for Mobile Networks
No full textIn today\u27s increasingly connected world, the demand for secure mobile communications is paramount. The security protocols are specifically tailored for mobile communication systems, ensuring the confidentiality and integrity of sensitive data transmitted over wireless networks. It can be seamlessly integrated into various mobile applications such as messaging platforms, VoIP services, and mobile banking apps, providing end-to-end encryption for user privacy. Current encryption protocols used in mobile communications often face challenges related to performance and security. Traditional encryption methods may not adequately address the evolving threats posed by sophisticated attackers. Moreover, the computational overhead associated with encryption and decryption processes can impact the overall efficiency of mobile communication systems. This work presents a novel approach to enhancing the security of mobile communications through the design of a Pipelined Advanced Encryption Based Cryptography Protocol (PAEBCP). The proposed protocol aims to address the vulnerabilities present in existing encryption methods by leveraging a pipelined architecture for efficient encryption and decryption processes. The proposed PAEBCP protocol introduces a pipelined architecture that optimizes the encryption and decryption processes for mobile communication systems. By dividing the encryption process into multiple stages and parallelizing key operations, the protocol enhances both security and performance
Implementation of Systolic Multiplier Using Hybrid Multiplexer Dependent Adder
No full textMultipliers are basic building blocks in various integrated circuits like microprocessors, micro controllers, and ALUs. The existing multipliers suffer from high power consumption and inefficient use of hardware resources. They often rely on traditional adder structures that are not tailored for specific operations, leading to suboptimal performance. Additionally, their fixed architectures limit adaptability and scalability in different applications. So, the proposed approach offers enhanced computational efficiency and reduced power consumption compared to conventional multiplier designs. By integrating multiplexer-dependent adders into the systolic array, the proposed method optimizes resource utilization and delivers improved performance for various arithmetic operations. This integration allows for dynamic selection of adder types based on the specific multiplication operation, significantly reducing power consumption and latency. By adapting the hardware resources to computational needs, the method achieves higher efficiency and flexibility, making it suitable for a wide range of applications in digital signal processing and data processing systems
DETECTION OF FRAUDULENT PHONE CALLS DETECTION IN MOBILE APPLICATIONS
No full textThe primary challenge faced over the course of this decade-long endeavour is the difficulty in devising effective features without direct access to telephony network infrastructure. we conducted an extensive three-month measurement study using these call logs, which encompassed a staggering 9 billion records. Based on the insights gleaned from this study, we identified and designed 29 features that could be used by machine learning algorithms to predict malicious calls. Fraudulent phone calls or scams and spam s via telephone or mobile phone have become a common threat to individuals and organizations. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as powerful tools in detecting and analyzing fraud or malicious calls. This paper presents an overview of AI-based fraud or spam detection and analysis techniques, along with its challenges and potential solutions. The novel fraud call detection approach is proposed that achieved high accuracy and precision. The outcomes revealed that the most effective approach could reduce unblocked malicious calls by up to 90%, while maintaining a precision rate exceeding 93.79% for benign call traffic. Moreover, our analysis demonstrated that these models could be implemented efficiently without incurring significant latency overhead
TRI-LEVEL CASCADING CONTROL TO AUGMENT POWER QUALITY CONCERNS IN DISTRIBUTION NETWORKS
No full textPower distribution systems have been affected by harmonic problems for decades. Harmonic currents can affect line voltage and direct to numerous adversative results including equipment overheating, failure of solid-state equipment, and restraint with communication systems. They deteriorate power quality by causing poor power factors and increasing total harmonic distortion. To reduce harmonics and to improve power quality, a grid-tie active power filter (APF) is introduced which eliminates both lower and upper-order harmonics. In this proposed paper, APF is used along with an LCL filter with versatile controlling techniques, Clarke’s and Park’s transformations are implemented in the paper. The proposed scheme can fulfill the problem faced in the power system due to non-linear loads. The results are simulated and validated using MATLAB/Simulink environment
ABNORMAL TRAFFIC DETECTION BASED ON ATTENTION AND BIG STEP CONVOLUTION
No full textThe identification of abnormal traffic is essential to network security and service quality. A big-step convolutional neural network traffic detection model based on the attention mechanism is provided as a solution to the significant challenges in abnormal traffic identification caused by feature similarity and the detection model\u27s single dimension. First, the raw traffic is preprocessed and mapped into a two-dimensional grayscale picture after the network traffic characteristics are examined. After that, histogram equalization is used to create multi-channel grayscale pictures. An attention mechanism is then added to give traffic characteristics varying weights in order to improve local features. In order to improve the flaws in convolutional neural networks, including local feature omission and overfitting, pooling-free convolutional neural networks are finally integrated to extract traffic characteristics of various depths. Both a real data collection and a balanced public data set were used for the simulation experiment. The suggested model is contrasted with ANN, CNN, RF, Bayes, and the two most recent models using the widely used method SVM as a baseline. 99.5% accuracy percentage with several classes is achieved experimentally. The best anomaly detection is found in the suggested model. Additionally, the suggested technique performs better in F1, recall, and accuracy than existing models. It is shown that the model is not only effective in detecting things, but also resilient to a variety of complicated contexts
GENDER AND OTHER SIGNIFICANT FACTORS CAUSING DISPARITIES IN SENIOR HIGH SCHOOL STUDENTS’ MATHEMATICS PERFORMANCE
No full textResearch findings on gender and other student related, teacher related and school related factors affecting students’ performance in mathematics are still debatable. With the recent trend of poor performance in mathematics recorded in both district and national performance statistics in the Assin North District, this present study examined gender factor and other significant factors causing disparities in mathematics performance among high school students. A mathematics achievement test and questionnaires were employed to collect data from a representative sample of 500 final-year students from three public senior high schools in the Assin North District, Ghana. Data were analysed descriptively and quantitatively using independent t-test and probit regression. Results show that male students did better than female students in the mathematics achievement test. The differences were statistically significant at .05 significance level. Aside gender, self-assurance and self-regard were identified as significant student related factors affecting the mathematics performance among senior high school students in the Assin North District. Teacher subject matter knowledge, teacher methods and teacher-student interaction were also significant teacher related factors affecting performance in mathematics. Finally, teacher motivation and school environment were identified as significant school related factors affecting mathematics performance among the senior high school. Other factors such as students’ socioeconomic background and teaching resources had effect on students’ performance but they were not statistically significant. The study recommends that senior high school mathematics teachers should employ gender responsive pedagogies in their teaching practices. It is also recommended that professional learning communities should also be formed at school levels to enable mathematics teachers improve upon their knowledge, motivation and teaching styles
POLYMER FLAT PLATE SOLAR COLLECTOER: A REVIEW
No full textA brief description on polymer flat plat solar collector manufacturing, design, and applications are given in this work. The main obstacles that face these collectors type, and how can be processed are also discussed. It is found that polymer low thermal conductivity, and degradation are the most essential difficulties in this industry, and increase heat transfer area and additives are the best common solutions. While stabilizers can be added to increase polymer life time
A STUDY ON MARKETING MIX ELEMENTS (PRODUCT, PRICE, PLACE, PROMOTION) AND THEIR INTERPLAY IN DRIVING CUSTOMER ACQUISITION, RETENTION
No full textThe paper aims to investigate the influencing of marketing mix (MM) elements (product, price, place or distribution, and promotion) on increasing the effectiveness of product promotion and their role to reduce the problems within the organization. The main importance aspects of this paper are to discuss the theoretical part of MM, to provide some perspectives for the researchers, and to give some instructions for the marketing department in Al-Saaeda Company for medical equipment technologies. The researchers used the main related academic resources from university library, and internet, and they designed and distributed questionnaires on a random sample of Al-Saaeda Company for Medical Equipment Technologies customers and the company employees to measure the impact of promotion on the marketing of its product (Glucocard 01-mini plus). The main findings of this paper can be concluded as following: 1. The promotion has a very high level of impact to increase the sales of products. 2. The good distribution of product can effect positively on customer satisfaction. 3. The company\u27s policy for promoting has a very good reflection on increasing the sales of products. The researchers recommended that the company must strengthen the level of promotions in its activities and departments, and the increasing of sales points is very important, so the company must enhance its policies of distribution
AN EFFICIENT IMAGE PROCESSING BASED IMAGE TO CARTOON GENERATION BASED ON DEEP LEARNING
No full textThis paper proposes an approach to convert real life images into cartoon images using image processing. The cartoon images have sharp edges, reduced colour quantity compared to the original image, and smooth colour regions. With the rapid advancement in artificial intelligence, recently deep learning methods have been developed for image to cartoon generation. Most of these methods perform extremely huge computations and require large datasets and are time consuming, unlike traditional image processing which involves direct manipulation on the input images. In this paper, we have developed an image processing based method for image to cartoon generation. Here, we perform parallel operations of enhancing the edges and quantizing the colour. The edges are extracted and dilated to highlight them in the output colour image. For colour quantization, the colours are assigned based on proposed formulation on separate colour channels. Later, these images are combined and the highlighted edges are added to generate the cartoon image. The generated images are compared with existing image processing approaches and deep learning based methods. From the experimental results, it is evident that the proposed approach generates high quality cartoon images which are visually appealing, have superior contrast and are able to preserve the contextual information at lower computational cost