Open Access

ARTICLE

Journal of Cyber Security, Vol.6, pp. 131-153, 2024, DOI:10.32604/jcs.2024.053954 - 17 December 2024
Abstract The changing nature of malware poses a cybersecurity threat, resulting in significant financial losses each year. However, traditional antivirus tools for detecting malware based on signatures are ineffective against disguised variations as they have low levels of accuracy. This study introduces Data Efficient Image Transformer-Malware Classifier (DeiT-MC), a system for classifying malware that utilizes Data-Efficient Image Transformers. DeiT-MC treats malware samples as visual data and integrates a newly developed Hybrid GridBay Optimizer (HGBO) for hyperparameter optimization and better model performance under varying malware scenarios. With HGBO, DeiT-MC outperforms the state-of-the-art techniques with a strong accuracy More >

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ARTICLE

Journal of Cyber Security, Vol.6, pp. 117-130, 2024, DOI:10.32604/jcs.2024.048332 - 06 December 2024
Abstract A URL (Uniform Resource Locator) is used to locate a digital resource. With this URL, an attacker can perform a variety of attacks, which can lead to serious consequences for both individuals and organizations. Therefore, attackers create malicious URLs to gain access to an organization’s systems or sensitive information. It is crucial to secure individuals and organizations against these malicious URLs. A combination of machine learning and deep learning was used to predict malicious URLs. This research contributes significantly to the field of cybersecurity by proposing a model that seamlessly integrates the accuracy of machine More >

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73

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REVIEW

Journal of Cyber Security, Vol.6, pp. 89-116, 2024, DOI:10.32604/jcs.2024.056164 - 06 December 2024
Abstract The constantly increasing degree and frequency of cyber threats require the emergence of flexible and intelligent approaches to systems’ protection. Despite the calls for the use of artificial intelligence (AI) and machine learning (ML) in strengthening cyber security, there needs to be more literature on an integrated view of the application areas, open issues or trends in AI and ML for cyber security. Based on 90 studies, in the following literature review, the author categorizes and systematically analyzes the current research field to fill this gap. The review evidences that, in contrast to rigid rule-based… More >

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79

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ARTICLE

Journal of Cyber Security, Vol.6, pp. 69-87, 2024, DOI:10.32604/jcs.2024.051196 - 28 August 2024
Abstract This paper investigates the impact of reducing feature-vector dimensionality on the performance of machine learning (ML) models. Dimensionality reduction and feature selection techniques can improve computational efficiency, accuracy, robustness, transparency, and interpretability of ML models. In high-dimensional data, where features outnumber training instances, redundant or irrelevant features introduce noise, hindering model generalization and accuracy. This study explores the effects of dimensionality reduction methods on binary classifier performance using network traffic data for cybersecurity applications. The paper examines how dimensionality reduction techniques influence classifier operation and performance across diverse performance metrics for seven ML models. Four… More >

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263

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ARTICLE

Journal of Cyber Security, Vol.6, pp. 41-68, 2024, DOI:10.32604/jcs.2024.049658 - 04 June 2024
Abstract With the rapid advancement of the Internet, network attack methods are constantly evolving and adapting. To better identify the network attack behavior, a universal gravitation clustering algorithm was proposed by analyzing the dissimilarities and similarities of the clustering algorithms. First, the algorithm designated the cluster set as vacant, with the introduction of a new object. Subsequently, a new cluster based on the given object was constructed. The dissimilarities between it and each existing cluster were calculated using a defined difference measure. The minimum dissimilarity was selected. Through comparing the proposed algorithm with the traditional Back More >

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313

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ARTICLE

Journal of Cyber Security, Vol.6, pp. 25-39, 2024, DOI:10.32604/jcs.2023.045859 - 11 January 2024
Abstract Phishing emails have experienced a rapid surge in cyber threats globally, especially following the emergence of the COVID-19 pandemic. This form of attack has led to substantial financial losses for numerous organizations. Although various models have been constructed to differentiate legitimate emails from phishing attempts, attackers continuously employ novel strategies to manipulate their targets into falling victim to their schemes. This form of attack has led to substantial financial losses for numerous organizations. While efforts are ongoing to create phishing detection models, their current level of accuracy and speed in identifying phishing emails is less… More >

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ARTICLE

Journal of Cyber Security, Vol.6, pp. 1-23, 2024, DOI:10.32604/jcs.2023.046915 - 03 January 2024
Abstract The importance of cybersecurity in contemporary society cannot be inflated, given the substantial impact of networks on various aspects of daily life. Traditional cybersecurity measures, such as anti-virus software and firewalls, safeguard networks against potential threats. In network security, using Intrusion Detection Systems (IDSs) is vital for effectively monitoring the various software and hardware components inside a given network. However, they may encounter difficulties when it comes to detecting solitary attacks. Machine Learning (ML) models are implemented in intrusion detection widely because of the high accuracy. The present work aims to assess the performance of More >

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784

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ARTICLE

Journal of Cyber Security, Vol.4, No.4, pp. 287-298, 2022, DOI:10.32604/jcs.2023.042486
Abstract Unmanned Aerial Vehicles (UAVs) proliferate quickly and play a significant part in crucial tasks, so it is important to protect the security and integrity of UAV communication channels. Intrusion Detection Systems (IDSs) are required to protect the UAV communication infrastructure from unauthorized access and harmful actions. In this paper, we examine a new approach for enhancing intrusion detection in UAV communication channels by utilizing the Long Short-Term Memory network (LSTM) combined with the Synthetic Minority Oversampling Technique (SMOTE) algorithm, and this integration is the binary classification method (LSTM-SMOTE). We successfully achieved 99.83% detection accuracy by More >

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3

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ARTICLE

Journal of Cyber Security, Vol.4, No.2, pp. 79-94, 2022, DOI:10.32604/jcs.2022.029020
Abstract Personal data are strongly linked to web browsing history. By visiting a certain website, a user can share her favorite items, location, employment status, financial information, preferences, gender, medical status, news, etc. Therefore, web tracking is considered as one of the most significant internet privacy threats that can have a serious impact on end-users. Usually, it is used by most websites to track visitors through the internet in order to enhance their services and improve search customization. Moreover, selling users’ data to the advertising companies without their permission. Although there are more research efforts focused More >

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1615

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1

Open Access

ARTICLE

Journal of Cyber Security, Vol.4, No.2, pp. 119-133, 2022, DOI:10.32604/jcs.2022.032915
Abstract Increasingly advanced image processing technology has made digital image editing easier and easier. With image processing software at one’s fingertips, one can easily alter the content of an image, and the altered image is so realistic that it is illegible to the naked eye. These tampered images have posed a serious threat to personal privacy, social order, and national security. Therefore, detecting and locating tampered areas in images has important practical significance, and has become an important research topic in the field of multimedia information security. In recent years, deep learning technology has been widely… More >

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1939

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ARTICLE

Journal of Cyber Security, Vol.4, No.3, pp. 153-167, 2022, DOI:10.32604/jcs.2022.033436
Abstract Vehicular ad hoc networks (VANETs) are designed in accordance with the ad hoc mobile networks (MANETs), i.e., impulsive formation of a wireless network for V2V (vehicle-to-vehicle) communication. Each vehicle is preserved as a node which remains as share of network. All the vehicle in the network is made to be under communication in a VANET because of which all the vehicles in the range can be made connected to a to a unit & a wide network can be established with a huge range. Healthier traffic management, vehicle-to-vehicle communication and provision of road information can… More >

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1077

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ARTICLE

Journal of Cyber Security, Vol.4, No.2, pp. 95-107, 2022, DOI:10.32604/jcs.2022.029451
Abstract Due to its unique security, blockchain technology is widely used in the financial field. Under the background of the rapid development of information technology and the rapid improvement of medical level, it is also a general trend to integrate blockchain technology into the medical field. According to the characteristics of blockchain and the research contents of many scholars on the application of blockchain in the medical field, this paper analyzes and summarizes the problems existing in the current development of blockchain, puts forward corresponding solutions, and looks forward to the further application of blockchain technology More >

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1061

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ARTICLE

Journal of Cyber Security, Vol.4, No.2, pp. 65-77, 2022, DOI:10.32604/jcs.2022.028065
Abstract Cryo-electron microscopy (cryo-EM) has become one of the mainstream techniques for determining the structures of proteins and macromolecular complexes, with prospects for development and significance. Researchers must select hundreds of thousands of particles from micrographs to acquire the database for single-particle cryo-EM reconstruction. However, existing particle picking methods cannot ensure that the particles are in the center of the bounding box because the signal-to-noise ratio (SNR) of micrographs is extremely low, thereby directly affecting the efficiency and accuracy of 3D reconstruction. We propose an automated particle-picking method (CenterPicker) based on particle center point detection to… More >

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1021

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ARTICLE

Journal of Cyber Security, Vol.4, No.2, pp. 109-118, 2022, DOI:10.32604/jcs.2022.030498
Abstract Nowadays, emerging trends in the field of technology related to big data, cognitive computing, and the Internet of Things (IoT) have become closely related to people’s lives. One of the hottest areas these days is transforming traditional cities into smart cities, using the concept of IoT depending on several types of modern technologies to develop and manage cities in order to improve and facilitate the quality of life. The Internet of Things networks consist of a huge number of interconnected devices and sensors that process and transmit data. Such Activities require efficient energy to be More >

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1178

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ARTICLE

Journal of Cyber Security, Vol.4, No.3, pp. 189-200, 2022, DOI:10.32604/jcs.2022.038401
Abstract As a typical representative of web 2.0, Ethereum has significantly boosted the development of blockchain finance. However, due to the anonymity and financial attributes of Ethereum, the number of phishing scams is increasing rapidly and causing massive losses, which poses a serious threat to blockchain financial security. Phishing scam address identification enables to detect phishing scam addresses and alerts users to reduce losses. However, there are three primary challenges in phishing scam address recognition task: 1) the lack of publicly available large datasets of phishing scam address transactions; 2) the use of multi-order transaction information… More >

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763

Open Access

ARTICLE

Journal of Cyber Security, Vol.4, No.1, pp. 57-64, 2022, DOI:10.32604/jcs.2022.028792
Abstract Vehicular ad hoc network (VANET) is a self-organizing wireless sensor network model, which is extensively used in the existing traffic. Due to the openness of wireless channel and the sensitivity of traffic information, data transmission process in VANET is vulnerable to leakage and attack. Authentication of vehicle identity while protecting vehicle privacy information is an advantageous way to improve the security of VANET. We propose a scheme based on fair blind signature and secret sharing algorithm. In this paper, we prove that the scheme is feasible through security analysis. More >

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1057

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ARTICLE

Journal of Cyber Security, Vol.4, No.1, pp. 17-28, 2022, DOI:10.32604/jcs.2022.027524
Abstract Resilient network infrastructure is pivotal for business entities that are growing reliance on the Internet. Distributed Denial-of-Service (DDOS) is a common network threat that collectively overwhelms and exhausts network resources using coordinated botnets to interrupt access to network services, devices, and resources. IDS is typically deployed to detect DDOS based on Snort rules. Although being fairly accurate, IDS operates on a compute-intensive packet inspection technique and lacks rapid DDOS detection. Meanwhile, SNMP is a comparably lightweight countermeasure for fast detection. However, this SNMP trigger is often circumvented if the DDOS burst rate is coordinated to… More >

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