Log in

Relevant bibliographies by topics / Network Threats / Journal articles

To see the other types of publications on this topic, follow the link: Network Threats.

Journal articles on the topic 'Network Threats'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Network Threats.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Saddam RA, Angga Pranata, Sugiono, et al. "Sniffing and Spoofing in Computer Security." International Journal of Integrative Sciences 2, no. 6 (2023): 881–86. http://dx.doi.org/10.55927/ijis.v2i6.4528.

Full text

Abstract:

The development of Information Technology (IT) has changed people's mindset. The presence of the Internet as the main platform for online activity is vulnerable to criminal acts by irresponsible parties. Criminal acts in cyberspace, of course, pose a major threat to the governance of online activities. One of these major threats is the threat of network security. Networks connected to the internet are basically insecure and can always be exploited by hackers, both LAN and wireless networks. The internet network has two data transmission media, namely wired and wireless. what happens is open. E

APA, Harvard, Vancouver, ISO, and other styles

2

Novokhrestov, Aleksey, Anton Konev, and Alexander Shelupanov. "Model of Threats to Computer Network Software." Symmetry 11, no. 12 (2019): 1506. http://dx.doi.org/10.3390/sym11121506.

Full text

Abstract:

This article highlights the issue of identifying information security threats to computer networks. The aim of the study is to increase the number of identified threats. Firstly, it was carried out the analysis of computer network models used to identify threats, as well as in approaches to building computer network threat models. The shortcomings that need to be corrected are highlighted. On the basis of the mathematical apparatus of attributive metagraphs, a computer network model is developed that allows to describe the software components of computer networks and all possible connections b

APA, Harvard, Vancouver, ISO, and other styles

3

Wahyuningsih, Tri, Irwan Sembiring, Adi Setiawan, and Iwan Setyawan. "Exploring network security threats through text mining techniques: a comprehensive analysis." Computer Science and Information Technologies 4, no. 3 (2023): 258–67. http://dx.doi.org/10.11591/csit.v4i3.pp258-267.

Full text

Abstract:

In response to the escalating cybersecurity threats, this research focuses on leveraging text mining techniques to analyze network security data effectively. The study utilizes user-generated reports detailing attacks on server networks. Employing clustering algorithms, these reports are grouped based on threat levels. Additionally, a classification algorithm discerns whether network activities pose security risks. The research achieves a noteworthy 93% accuracy in text classification, showcasing the efficacy of these techniques. The novelty lies in classifying security threat report logs acco

APA, Harvard, Vancouver, ISO, and other styles

4

Wahyuningsih, Tri, Irwan Sembiring, Adi Setiawan, and Iwan Setyawan. "Exploring network security threats through text mining techniques: a comprehensive analysis." Computer Science and Information Technologies 4, no. 3 (2023): 258–67. http://dx.doi.org/10.11591/csit.v4i3.p258-267.

Full text

Abstract:

In response to the escalating cybersecurity threats, this research focuses on leveraging text mining techniques to analyze network security data effectively. The study utilizes user-generated reports detailing attacks on server networks. Employing clustering algorithms, these reports are grouped based on threat levels. Additionally, a classification algorithm discerns whether network activities pose security risks. The research achieves a noteworthy 93% accuracy in text classification, showcasing the efficacy of these techniques. The novelty lies in classifying security threat report logs acco

APA, Harvard, Vancouver, ISO, and other styles

5

Wahyuningsih, Tri, Irwan Sembiring, Adi Setiawan, and Iwan Setyawan. "Exploring network security threats through text mining techniques: a comprehensive analysis." Computer Science and Information Technologies 4, no. 3 (2023): 258–67. https://doi.org/10.11591/csit.v4i3.pp258-267.

Full text

Abstract:

In response to the escalating cybersecurity threats, this research focuses on leveraging text mining techniques to analyze network security data effectively. The study utilizes user-generated reports detailing attacks on server networks. Employing clustering algorithms, these reports are grouped based on threat levels. Additionally, a classification algorithm discerns whether network activities pose security risks. The research achieves a noteworthy 93% accuracy in text classification, showcasing the efficacy of these techniques. The novelty lies in classifying security threat report logs acco

APA, Harvard, Vancouver, ISO, and other styles

6

Akoh Atadoga, Enoch Oluwademilade Sodiya, Uchenna Joseph Umoga, and Olukunle Oladipupo Amoo. "A comprehensive review of machine learning's role in enhancing network security and threat detection." World Journal of Advanced Research and Reviews 21, no. 2 (2024): 877–86. http://dx.doi.org/10.30574/wjarr.2024.21.2.0501.

Full text

Abstract:

As network security threats continue to evolve in complexity and sophistication, there is a growing need for advanced solutions to enhance network security and threat detection capabilities. Machine learning (ML) has emerged as a powerful tool in this context, offering the potential to detect and mitigate threats in real-time by analyzing vast amounts of network data. This comprehensive review explores the role of machine learning in enhancing network security and threat detection. The review begins by providing an overview of the current landscape of network security threats and the challenge

APA, Harvard, Vancouver, ISO, and other styles

7

Akoh, Atadoga, Oluwademilade Sodiya Enoch, Joseph Umoga Uchenna, and Oladipupo Amoo Olukunle. "A comprehensive review of machine learning's role in enhancing network security and threat detection." World Journal of Advanced Research and Reviews 21, no. 2 (2024): 877–86. https://doi.org/10.5281/zenodo.14008462.

Full text

Abstract:

As network security threats continue to evolve in complexity and sophistication, there is a growing need for advanced solutions to enhance network security and threat detection capabilities. Machine learning (ML) has emerged as a powerful tool in this context, offering the potential to detect and mitigate threats in real-time by analyzing vast amounts of network data. This comprehensive review explores the role of machine learning in enhancing network security and threat detection. The review begins by providing an overview of the current landscape of network security threats and the challenge

APA, Harvard, Vancouver, ISO, and other styles

8

K, Pramod, and Aswathy Venu. "Self-Defending Networks." International Journal for Research in Applied Science and Engineering Technology 11, no. 3 (2023): 2330–37. http://dx.doi.org/10.22214/ijraset.2023.49894.

Full text

Abstract:

Abstract: As the nature of the threat in networks evolves daily, it is vitally important that defense techniques evolve as well. Earlier threats from both internal and external sources were gradual and can be easily tracked and destroyed. But now Internet worms are spread all over the world, so it is essential for protection systems and the network itself to respond immediately to threats. The basis of community self-defense is the importance of countering threats in the community. Every device found in a community plays a vital role in keeping the community safe. This guarantees the security

APA, Harvard, Vancouver, ISO, and other styles

9

Kwubeghari, Anthony, Lucy Ifeyinwa Ezigbo, and Francis Amaechi Okoye. "Modelling of Cyber Attack Detection and Response System for 5G Network Using Machine Learning Technique." ABUAD Journal of Engineering Research and Development (AJERD) 7, no. 2 (2024): 297–307. http://dx.doi.org/10.53982/ajerd.2024.0702.29-j.

Full text

Abstract:

The rapid increase in the adoption of 5G networks has revolutionized communication technologies, enabling high-speed data transmission and connectivity across various domains. However, the advent of 5G technology comes with an increased risk of cyber-attacks and security breaches, necessitating the development of robust defence mechanisms to safeguard network infrastructure and mitigate potential threats. The work presents a novel approach for modelling a cyber-attack response system tailored specifically for 5G networks, leveraging machine learning techniques to enhance threat detection and r

APA, Harvard, Vancouver, ISO, and other styles

10

Yang, Hongyu, Renyun Zeng, Fengyan Wang, Guangquan Xu, and Jiyong Zhang. "An Unsupervised Learning-Based Network Threat Situation Assessment Model for Internet of Things." Security and Communication Networks 2020 (November 28, 2020): 1–11. http://dx.doi.org/10.1155/2020/6656066.

Full text

Abstract:

With the wide application of network technology, the Internet of Things (IoT) systems are facing the increasingly serious situation of network threats; the network threat situation assessment becomes an important approach to solve these problems. Aiming at the traditional methods based on data category tag that has high modeling cost and low efficiency in the network threat situation assessment, this paper proposes a network threat situation assessment model based on unsupervised learning for IoT. Firstly, we combine the encoder of variational autoencoder (VAE) and the discriminator of generat

APA, Harvard, Vancouver, ISO, and other styles

11

Lv, Huiying, Yuan Zhang, and Jie Wang. "Network Threat Identification and Analysis Based on a State Transition Graph." Cybernetics and Information Technologies 13, Special-Issue (2013): 51–61. http://dx.doi.org/10.2478/cait-2013-0037.

Full text

Abstract:

Abstract With the rapid popularity of Internet and information technology, local area network is becoming insecure. Along with the improving advantages, security threats are emerging continually and bringing great pressure and challenges. An identification and analysis method for network real-time threats is proposed to accurately assess and master the current network security situation, and thereby preferably guide a dynamic defense. This method recognizes the current threats and predicts the subsequent threats by modeling attack scenarios and simulating attack state transferring. The threat

APA, Harvard, Vancouver, ISO, and other styles

12

Sandy, Djoko Andoko, Poppy Setiawati Nurisnaeny, and Mira Murniasari. "The Threat of Social Network Games in Indonesia." Borneo Educational Journal (Borju) 5, no. 2 (2023): 335–51. http://dx.doi.org/10.24903/bej.v5i2.1393.

Full text

Abstract:

This research examines the potential threat through SNG in Indonesia. The theories of threat, social media, cyber, and network society are used to analyze the research problem through qualitative analysis. Data was obtained through interviews and literature studies. The results of the study show that the potential threat on SNG includes ideological threats in society, growing illegal and pornographic content, theft of personal data, illegal monitoring of user activities, online fraud, cyberbullying, inappropriate content, dependence, and cyber attacks that threaten the activities of social net

APA, Harvard, Vancouver, ISO, and other styles

13

Belosay, Ruchita P. "Security Risks in 5G." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem50837.

Full text

Abstract:

This paper presents a comprehensive review of security vulnerabilities in fifth-generation (5G) wireless networks. It investigates emerging threats across the core network, protocol layers, and software-defined infrastructures, emphasizing risks introduced by network slicing, open APIs, and virtualization. The methodology involves comparative analysis of recent technical literature and classification of threats such as denial-of-service attacks, weak authentication mechanisms, and endpoint vulnerabilities. The study evaluates current mitigation strategies including encryption, slice isolation,

APA, Harvard, Vancouver, ISO, and other styles

14

Farooqui, Muhammad Najmul Islam, Junaid Arshad, and Muhammad Mubashir Khan. "A Layered Approach to Threat Modeling for 5G-Based Systems." Electronics 11, no. 12 (2022): 1819. http://dx.doi.org/10.3390/electronics11121819.

Full text

Abstract:

The rise of 5G networks promises a wide range of cutting-edge services with the aim of achieving high performance and reliability. Cutting-edge applications facilitated by 5G architecture make use of various enabling technologies, which introduce various new and emerging security threats and attacks. Threat modeling is a proactive approach to identify security requirements, as well as potential threats and vulnerabilities, and prioritize remediation methods. In addition, 5G networks are complex and are usually divided into separate layers to foster the understanding and management of different

APA, Harvard, Vancouver, ISO, and other styles

15

Chadrack, Irabaruta, and Dr Nyesheja Muhire Enan. "AI Powered Network Traffic Detection." Journal of Information and Technology 5, no. 2 (2025): 53–65. https://doi.org/10.70619/vol5iss2pp53-65.

Full text

Abstract:

This study presents an AI-powered network traffic detection framework capable of recognizing anomalies and addressing cyber threats in real-time. Traditional detection systems struggle to keep pace with evolving threats, necessitating more adaptive and intelligent approaches. To this end, the research integrates Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) models to enhance detection accuracy and operational efficiency. The framework is evaluated using benchmark datasets such as UNSW-NB15 and CICIDS2017, focusing on performance metrics including accuracy, precision, re

APA, Harvard, Vancouver, ISO, and other styles

16

Golchha, Prakhar, Rajesh Deshmukh, and Palak Lunia. "A Review on Network Security Threats and Solutions." International Journal of Scientific Engineering and Research 3, no. 4 (2015): 21–24. https://doi.org/10.70729/ijser1567.

Full text

APA, Harvard, Vancouver, ISO, and other styles

17

Simonjan, Jennifer, Sebastian Taurer, and Bernhard Dieber. "A Generalized Threat Model for Visual Sensor Networks." Sensors 20, no. 13 (2020): 3629. http://dx.doi.org/10.3390/s20133629.

Full text

Abstract:

Today, visual sensor networks (VSNs) are pervasively used in smart environments such as intelligent homes, industrial automation or surveillance. A major concern in the use of sensor networks in general is their reliability in the presence of security threats and cyberattacks. Compared to traditional networks, sensor networks typically face numerous additional vulnerabilities due to the dynamic and distributed network topology, the resource constrained nodes, the potentially large network scale and the lack of global network knowledge. These vulnerabilities allow attackers to launch more sever

APA, Harvard, Vancouver, ISO, and other styles

18

Dandamudi, Sai Ratna Prasad, Jaideep Sajja, and Amit Khanna. "AI Transforming Data Networking and Cybersecurity through Advanced Innovations." International Journal of Innovative Research in Computer Science and Technology 13, no. 1 (2025): 42–49. https://doi.org/10.55524/ijircst.2025.13.1.6.

Full text

Abstract:

The rapid expansion of data networking infrastructure has necessitated advancements in cybersecurity to mitigate increasingly sophisticated cyber threats. As the digital landscape evolves, networks are handling unprecedented volumes of data, fueled by innovations like the Internet of Things (IoT), 5G technology, and cloud computing. This growth has created not only opportunities for improved connectivity but also significant challenges in safeguarding sensitive information from advanced cyber threats. Simultaneously, artificial intelligence (AI) has emerged as a transformative technology with

APA, Harvard, Vancouver, ISO, and other styles

19

Bhelkar,, Mr Sahil. "Network Intrusion Detection System." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31278.

Full text

Abstract:

Network intrusion detection systems (NIDS) play a crucial role in safeguarding network infrastructures against unauthorized access and malicious activities. This abstract explores the fundamental concepts, methodologies, and challenges associated with NIDS. It delves into the various techniques employed by NIDS, ranging from signature-based detection to anomaly detection, and highlights the importance of real-time monitoring and analysis for timely threat detection and response. Additionally, the abstract discusses the evolving landscape of cyber threats and the need for continuous adaptation

APA, Harvard, Vancouver, ISO, and other styles

20

Hu, Teng, Bangzhou Xin, Xiaolei Liu, Ting Chen, Kangyi Ding, and Xiaosong Zhang. "Tracking the Insider Attacker: A Blockchain Traceability System for Insider Threats." Sensors 20, no. 18 (2020): 5297. http://dx.doi.org/10.3390/s20185297.

Full text

Abstract:

The insider threats have always been one of the most severe challenges to cybersecurity. It can lead to the destruction of the organisation’s internal network system and information leakage, which seriously threaten the confidentiality, integrity and availability of data. To make matters worse, since the attacker has authorized access to the internal network, they can launch the attack from the inside and erase their attack trace, which makes it challenging to track and forensics. A blockchain traceability system for insider threats is proposed in this paper to mitigate the issue. First, this

APA, Harvard, Vancouver, ISO, and other styles

21

Michael, Tressa. "CNN Intrusion Detection for Threat Analysis of a Network." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (2021): 3945–49. http://dx.doi.org/10.17762/turcomat.v12i3.1683.

Full text

Abstract:

The technological advancement realized in the discovery and embrace of both IoT and IIoT is totally indispensable. Many systems and subsystems both robust and miniaturized have made their existence into the technical arena due to IoT. It goes without saying that IoT has brought into light very diverse benefits that cut across universal applications.However, the pre-requisite of a network channel existence for an IoT operation to be successful is the only pitfall that this essentially unique system possesses. There is a significant amount of danger associated with transmission networks. They ha

APA, Harvard, Vancouver, ISO, and other styles

22

Nayana R, Harish G N, and Asharani R. "A comprehensive survey of modern network security techniques and challenges." World Journal of Advanced Research and Reviews 3, no. 2 (2019): 101–10. http://dx.doi.org/10.30574/wjarr.2019.3.2.0069.

Full text

Abstract:

This review paper provides a comprehensive survey of modern network security techniques and the multifaceted challenges they address in an increasingly interconnected world. As cyber threats continue to evolve in both sophistication and frequency, organizations must deploy advanced defense mechanisms to protect sensitive data and maintain network integrity. We explore the shifting landscape of cyber threats, ranging from traditional attacks like malware and ransomware to more complex and persistent threats such as Advanced Persistent Threats (APTs) and zero-day exploits. The paper examines a r

APA, Harvard, Vancouver, ISO, and other styles

23

Ivanovich Vatin, Nikolai, and Rama Sundari. "Securing electric transportation networks: A machine learning-driven cyber threat detection." MATEC Web of Conferences 392 (2024): 01184. http://dx.doi.org/10.1051/matecconf/202439201184.

Full text

Abstract:

The study examines the cybersecurity environment of electric transportation networks using a machine learning-based methodology. It analyzes the behaviors of electric vehicles, charging patterns, cyber threat occurrences, and the performance of machine learning models. An analysis of electric vehicle (EV) data shows that there are differences in battery capacity and distances covered, suggesting the presence of possible weaknesses across different cars. Cyber threat logs provide a comprehensive view of the various levels of threat severity and the time it takes to discover them, illustrating t

APA, Harvard, Vancouver, ISO, and other styles

24

Amirthayogam, G., N. Kumaran, S. Gopalakrishnan, K. R. Aravind Brito, S. RaviChand, and Shruti Bhargava Choubey. "Integrating Behavioral Analytics and Intrusion Detection Systems to Protect Critical Infrastructure and Smart Cities." Babylonian Journal of Networking 2024 (July 1, 2024): 88–97. http://dx.doi.org/10.58496/bjn/2024/010.

Full text

Abstract:

In an age notable by growing digitization and relatedness, protecting critical infrastructure and smart cities against cyber threats is a biggest obstacle. This abstract examines the combination of Behavioural Analytics (BA) and Intrusion Detection Systems (IDS) as a active and best plan to boost cybersecurity defences. Behavioural Analytics uses machine learning algorithms and statistical models to notice usual entities behaviour patterns inside networks, empowering the identification of anomalies that indicate possible security infringements. This approach is improved through modern techniqu

APA, Harvard, Vancouver, ISO, and other styles

25

Hariyadi, Dedy, Kartikadyota Kusumaningtyas, and Burhan Alfironi Muktamar. "Implementasi Malicious Traffic Untuk Mendeteksi Serangan Siber di SMK Muhammadiyah 1 Yogyakarta." INTEK : Jurnal Informatika dan Teknologi Informasi 6, no. 2 (2023): 73–78. http://dx.doi.org/10.37729/intek.v6i2.3776.

Full text

Abstract:

The Covid-19 pandemic has had a positive impact including the increasing implementation of information technology in various fields including the education sector. One of them is the increasing use of mobile devices such as cell phones or tote computers that utilize wireless networks. Connecting devices via wireless networks has a serious impact on the potential threat of cyber attacks. The potential threat of cyberattacks on devices during the Covid-19 pandemic is increasing, this is indicated by 975 million anomalous traffic recorded by Badan Siber dan Sandi Negara (BSSN) in 2022. To identif

APA, Harvard, Vancouver, ISO, and other styles

26

HARSHINI A, Ms. "WIRELESS NETWORK SECURITY ENHANCEMENT WITH ZITA." International Scientific Journal of Engineering and Management 04, no. 04 (2025): 1–7. https://doi.org/10.55041/isjem03186.

Full text

Abstract:

Abstract - With the growing cybersecurity threats, predictive maintenance has turned out to be a critical approach for ensuring reliability and efficiency in wireless networks. In this paper, we demonstrate the use of supervised machine learning methods in predictive maintenance for the detection and mitigation of attacks on wireless networks. Using past network data containing different network metrics and security attacks, our developed model predicts possible network attacks. To pass this intercept, users use the supervised learning; this means that the model is trained on labelled datasets

APA, Harvard, Vancouver, ISO, and other styles

27

Terentyev, Alexander, Olena Dolya, Tamara Lyashchenko, and Oleh Kuzminskyi. "DIAGNOSING AND COUNTERACTING NETWORK THREATS." Management of Development of Complex Systems, no. 42 (June 4, 2020): 125–31. http://dx.doi.org/10.32347/2412-9933.2020.42.125-131.

Full text

APA, Harvard, Vancouver, ISO, and other styles

28

Newson, Alan. "Network threats and vulnerability scanners." Network Security 2005, no. 12 (2005): 13–15. http://dx.doi.org/10.1016/s1353-4858(05)70314-7.

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

Parida Amalia and Muhammad Irwan Padli Nasution. "TANTANGAN TERKINI DALAM KEAMANAN INFORMASI ANALISIS RESIKO DAN UPAYA PERLINDUNGAN." JURNAL EKONOMI BISNIS DAN MANAJEMEN 2, no. 1 (2023): 24–37. http://dx.doi.org/10.59024/jise.v2i1.529.

Full text

Abstract:

Threats and attacks that can result in leaks of personal or sensitive data or reduced business performance have a significant impact on the security of networks and information systems. Insider attacks, eavesdropping, misconfiguration, missing functionality, confusion, man-in- attacks, virus attacks, denial of service attacks are some of the dangers that threaten your network security or threaten the security of your network. Attacks are possible. Influencing information systems. Companies risk losing information appropriate security measures, such as network and information system security. Y

APA, Harvard, Vancouver, ISO, and other styles

30

Sheela Hundekari. "Cybersecurity Threats in Digital Payment Systems (DPS): A Data Science Perspective." Journal of Information Systems Engineering and Management 10, no. 13s (2025): 491–503. https://doi.org/10.52783/jisem.v10i13s.2104.

Full text

Abstract:

The growing dependence on digital payment systems has resulted in a rise in cyber-attacks, therefore endangering user confidence and financial stability. Understanding these threats, evaluating their effect, and investigating data-driven solutions for reducing cybersecurity risks drives this research. The purpose of the study is to explore the cybersecutiy threats in digital payment systems (DPS) and the role of data science techniques in threat detection and prevention. The technique used in the current study is Exploratory Factor Analysis (EFA). It was found that the following are the three

APA, Harvard, Vancouver, ISO, and other styles

31

Reddy, Mr K. V. Siva Prasad, B. Mohith, P. Mahesh Babu, and K. Navtej. "CyberSleuth AI: Intelligent Network Forensics Analyzer." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 1643–47. https://doi.org/10.22214/ijraset.2025.68420.

Full text

Abstract:

Abstract: CyberSleuth represents a cutting-edge cybersecurity initiative designed to protect Canada's critical infrastructure through advanced threat detection and response capabilities. This comprehensive system combines artificial intelligence, machine learning, and human expertise to provide real-time monitoring, analysis, and protection against evolving cyber threats. By leveraging AI-driven analytics for network traffic analysis, anomaly detection, and automated threat response, CyberSleuth processes vast amounts of security data to identify potential threats while minimizing false positi

APA, Harvard, Vancouver, ISO, and other styles

32

Popaja, Nejla, Sabina Baraković, and Jasmina Baraković Husić. "Analysis of Threats for Ambient Assisted Living (AAL) Wireless Sensor Network (WSN)-Based System." B&H Electrical Engineering 15, no. 2 (2021): 31–39. http://dx.doi.org/10.2478/bhee-2021-0015.

Full text

Abstract:

Abstract In the process of designing a system, it is necessary to identify potential threats to that system and to include appropriate countermeasures. The process that helps in finding problems in the initial phase of the system design is the threat modeling. Creating a threat model consists of several steps and there are many tools that can help in automating the procedure. This article deals with the threat analysis for an Ambient Assisted Living (AAL) system based on Wireless Sensor Network (WSN), whose main function is to provide information for carers in order to provide the best possibl

APA, Harvard, Vancouver, ISO, and other styles

33

Dr. R. Balasubramanian, P. Ramachandran ,. "TC-CNN: A Tree Classified model using AI for identifying malware intrusions in open Networks." Psychology and Education Journal 58, no. 2 (2021): 6561–73. http://dx.doi.org/10.17762/pae.v58i2.3189.

Full text

Abstract:

Proliferation of the internet by multiple devices has led to dramatic increases in network traﬃc. The Internet medium has also been growing with this usage, but this fast growth has also resulted in new threats making networks vulnerable to intruders and attackers or malicious users. This has made network security an important factor due to excessive usage of ICT (Information and Communications Technology) as threats to IVTs has also grown manifold. Securing data is a major issue, especially when they are transmitted across open networks. IDSs (Intrusion Detection Systems) are methods or techn

APA, Harvard, Vancouver, ISO, and other styles

34

Addula, Santosh Reddy, Udit Mamodiya, Weiwei Jiang, and Mohammed Amin Almaiah. "Generative AI-Enhanced Intrusion Detection Framework for Secure Healthcare Networks in MANETs." SHIFRA 2025 (February 1, 2025): 62–68. https://doi.org/10.70470/shifra/2025/003.

Full text

Abstract:

Recent developments in healthcare security and network intrusion detection have seen the domain of Artificial Intelligence (AI) act as a decisive presence due to its increased adaptability and more resilient level of resistance towards emerging cyber threats. Due to decentralized nature and its cost-effective communication, mobile ad hoc networks (MANETs) are widely used in healthcare applications and present security vulnerabilities like access from unauthorized nodes, node mobility and the bandwidth constraint. In general, traditional encryption and authentication alone will not eliminate th

APA, Harvard, Vancouver, ISO, and other styles

35

NIKLEKAJ, Malvina. "Security in Computer Networks: Threats, Challenges, and Protection." Ingenious 3, no. 1 (2023): 51–60. http://dx.doi.org/10.58944/mcne2043.

Full text

Abstract:

This scientific article aims to examine the issue of security in computer networks, highlighting the threats, challenges, and methods of protection. With the development of technology and the increased use of the internet, security in computer networks has become a critical issue for individuals, organizations, and society as a whole. In this article, we will discuss how attackers can infiltrate communication systems and compromise the integrity, confidentiality, and availability of data. The techniques used by attackers to achieve their malicious goals will also be described. Furthermore, the

APA, Harvard, Vancouver, ISO, and other styles

36

Chavan, Mr Vikram. "Malware Classification using Machine Learning Algorithms and Tools." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 69–73. http://dx.doi.org/10.22214/ijraset.2021.34353.

Full text

Abstract:

The explosive growth of malware variants poses a major threat to information security. Malware is the one which frequently growing day by day and becomes major threats to the Internet Security. According to numerous increasing of worm malware in the networks nowadays, it became a serious danger that threatens our computers. Networks attackers did these attacks by designing the worms. A designed system model is needed to defy these threats, prevent it from multiplying and spreading through the network, and harm our computers. In this paper, we designed a classification on system model for this

APA, Harvard, Vancouver, ISO, and other styles

37

Maystrenko, V. A., and O. A. Bezrodnykh. "ASSESSMENT OF NETWORK THREATS TO INFORMATION SECURITY FOR SOFTWARE AND HARDWARE OF MEDICAL INFORMATION SYSTEMS." DYNAMICS OF SYSTEMS, MECHANISMS AND MACHINES 10, no. 3 (2022): 79–86. http://dx.doi.org/10.25206/2310-9793-2022-10-3-79-86.

Full text

Abstract:

This article discusses the issues of assessing network threats to information security for software and hardware components of medical information systems (MIS). For threats, an analysis of statistical data and analytical materials from various sources on network threats to information security (IST) was carried out. The study of statistical data and analytical materials allows us to classify the IST of interest to us according to the frequency of their occurrence. Based on the data obtained, using fuzzy logic methods, an assessment is made of the degree of threat and relevance of network IST

APA, Harvard, Vancouver, ISO, and other styles

38

Lysov, Bogdan, Vira Huskova, Tetiana Prosiankina-Zharova, and Artem Khalygov. "Information technology for the classification of data monitoring systems and data transmission networks for cyber threat detection." Bulletin of the National Technical University "KhPI" A series of "Information and Modeling" 1, no. 1 (13) (2025): 129–47. https://doi.org/10.20998/2411-0558.2025.01.09.

Full text

Abstract:

Nowadays, the security of critical infrastructure (CI) is a key challenge in the modern digital environment. The growing complexity of information systems and cyberattack methods necessitates the development of effective approaches for threat detection and classification. This paper presents a methodology for classifying types of threats for critical infrastructure based on network data. It proposes the use of machine learning and anomaly detection methods to identify malicious activities. Modern threat classification algorithms and neural networks are analyzed. The obtained results demonstrat

APA, Harvard, Vancouver, ISO, and other styles

39

Shaik, Sabeeruddin. "Emerging Network Security Threats: Preparing for the Next Decade." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 02 (2025): 1–7. https://doi.org/10.55041/ijsrem30039.

Full text

Abstract:

The swift advancement of network technologies has created an unprecedented level of connectivity and efficiency in digital systems. This expansion has also led to the rise of advanced network security threats, undermining traditional defensive strategies. This research study examines the dynamics of new network security risks, assessing their core causes, impacts, and the technology improvements necessary for effective countermeasures. This study examines critical concerns including ransomware, advanced persistent threats (APTs), IoT vulnerabilities, and AI-driven cyberattacks, with the object

APA, Harvard, Vancouver, ISO, and other styles

40

Shaik, Sabeeruddin. "Emerging Network Security Threats: Preparing for the Next Decade." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem44270.

Full text

Abstract:

The swift advancement of network technologies has created an unprecedented level of connectivity and efficiency in digital systems. This expansion has also led to the rise of advanced network security threats, undermining traditional defensive strategies. This research study examines the dynamics of new network security risks, assessing their core causes, impacts, and the technology improvements necessary for effective countermeasures. This study examines critical concerns including ransomware, advanced persistent threats (APTs), IoT vulnerabilities, and AI-driven cyberattacks, with the object

APA, Harvard, Vancouver, ISO, and other styles

41

Kearney, Stephen G., Vanessa M. Adams, Richard A. Fuller, Hugh P. Possingham, and James E. M. Watson. "Estimating the benefit of well-managed protected areas for threatened species conservation." Oryx 54, no. 2 (2018): 276–84. http://dx.doi.org/10.1017/s0030605317001739.

Full text

Abstract:

AbstractProtected areas are central to global efforts to prevent species extinctions, with many countries investing heavily in their establishment. Yet the designation of protected areas alone can only abate certain threats to biodiversity. Targeted management within protected areas is often required to achieve fully effective conservation within their boundaries. It remains unclear what combination of protected area designation and management is needed to remove the suite of processes that imperil species. Here, using Australia as a case study, we use a dataset on the pressures facing threate

APA, Harvard, Vancouver, ISO, and other styles

42

Ye, Shengke, Kaiye Dai, Guoli Fan, Ling Zhang, and Zhihao Liang. "Exploring the intersection of network security and database communication: a PostgreSQL Socket Connection case study." Transactions on Computer Science and Intelligent Systems Research 3 (April 10, 2024): 1–9. http://dx.doi.org/10.62051/pzqebt34.

Full text

Abstract:

In this study, the network security of PostgreSQL database using Socket connection is deeply analyzed. By exploring Socket connections established by PostgreSQL over TCP, we find potential security threats and vulnerabilities during data transmission, which may expose database systems to network attacks such as unauthorized access and data leakage. In order to assess these security risks, this study simulated a variety of network attack scenarios, especially the implantation and detection of Webshell, to reveal the vulnerability of PostgreSQL to such network threats. Especially in defending ag

APA, Harvard, Vancouver, ISO, and other styles

43

Subha K, Benitlin. "AI-Driven Cybersecurity Model for Real-Time Threat Detection and Prevention." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47712.

Full text

Abstract:

Abstract - As cyber threats become more dynamic and sophisticated, traditional intrusion detection systems often fall short in identifying emerging attacks in real-time. This project introduces a hybrid AI-driven cybersecurity model that combines supervised machine learning and deep reinforcement learning for adaptive, explainable, and real-time threat detection and prevention. It uses an XGBoost classifier trained on the UNSW-NB15 dataset to predict initial threats and a Deep Q-Network (DQN) agent, built with PyTorch, to make optimal security decisions based on evolving threats. The DQN inter

APA, Harvard, Vancouver, ISO, and other styles

44

He, Fangzhou, Wei Bai, and Zhiqi Wang. "Optimization of the Decision-making Process of Digital Twins in Network Security Based on Graph Neural Networks." Network Security 2024, no. 10 (2025): 73–83. https://doi.org/10.70985/rpa1ez48.

Full text

Abstract:

The network security model based on static rules lacks flexibility and adaptability, and it is difficult to adapt to and respond to dynamically changing network threats in real-time. Therefore, this paper proposes a method for optimizing the decision-making process of digital twins (DTs) in network security based on graph neural networks (GNNs). First, this paper applies the Adam optimizer to adjust the learning rate by optimizing the GNN structure, combines the cross entropy loss function to improve the attack recognition ability, and uses L2 regularization and Dropout to prevent overfitting

APA, Harvard, Vancouver, ISO, and other styles

45

Enyinaya Stefano Okafor, Olatunji Akinrinola, Favour Oluwadamilare Usman, Olukunle Oladipupo Amoo, and Nneka Adaobi Ochuba. "CYBERSECURITY ANALYTICS IN PROTECTING SATELLITE TELECOMMUNICATIONS NETWORKS: A CONCEPTUAL DEVELOPMENT OF CURRENT TRENDS, CHALLENGES, AND STRATEGIC RESPONSES." International Journal of Applied Research in Social Sciences 6, no. 3 (2024): 254–66. http://dx.doi.org/10.51594/ijarss.v6i3.854.

Full text

Abstract:

Cybersecurity is a critical concern in satellite telecommunications networks, given their vulnerability to cyber threats. This abstract presents a conceptual development of current trends, challenges, and strategic responses in using cybersecurity analytics to protect these networks. The paper discusses the increasing reliance on satellite telecommunications, making them attractive targets for cyber attacks. It explores the role of cybersecurity analytics in detecting and mitigating these threats, highlighting the importance of proactive monitoring and threat intelligence. Challenges in cybers

APA, Harvard, Vancouver, ISO, and other styles

46

Alin, G., A. Konsbayev, and N. Abdikaparov. "HARNESSING ARTIFICIAL INTELLIGENCE FOR ADVANCED THREAT DETECTION IN NETWORK INFRASTRUCTURES." INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGIES 5, no. 2(18) (2024): 70–83. http://dx.doi.org/10.54309/ijict.2024.18.2.007.

Full text

Abstract:

As cyber threats grow increasingly sophisticated, traditional security measures are falling behind in the face of these evolving attacks. This article highlights the role of Smart Sentinel, a cutting-edge threat detection system that utilizes Artificial Intelligence (AI) to strengthen network defenses. Unlike conventional security solutions, Smart Sentinel employs machine learning algorithms to continuously learn and adapt, enabling it to detect anomalies and potential threats in real-time. By analyzing a variety of data sources, including network traffic and user behavior, the system establis

APA, Harvard, Vancouver, ISO, and other styles

47

R. Vinoth Kumar. "Enhancing Threat Prioritization In Cybersecurity Using Avian Shield Optimizer (ASO) In Graph Forge Elite (GFE) Framework." Journal of Electrical Systems 20, no. 4s (2024): 2257–71. http://dx.doi.org/10.52783/jes.2396.

Full text

Abstract:

In the ever-evolving field of cybersecurity, the ability to effectively prioritize threats is essential for organizations to allocate resources wisely and proactively mitigate potential risks. Avian Shield Optimizer (ASO) is a revolutionary optimization technique specifically designed for threat prioritization. ASO utilizes evolutionary-inspired mechanisms to dynamically adjust the prioritization of threats based on a comprehensive analysis of factors such as severity, relevance, and potential impact on organizational assets. By continuously monitoring and adapting to the dynamic threat landsc

APA, Harvard, Vancouver, ISO, and other styles

48

Sun, Xiu Juan. "Personal Computer Network Security Prevention Research." Advanced Materials Research 971-973 (June 2014): 1684–87. http://dx.doi.org/10.4028/www.scientific.net/amr.971-973.1684.

Full text

Abstract:

this article from the various security threats facing the computer network, systematically introduces the network security technology. And in view of the campus network security issues, firstly analyzes the hidden dangers to the safety of network system in colleges and universities, and then from the build two aspects of security defense system and strengthen the safety management design of the campus network security policy. This paper study, the first thing I learned the main threat to the network security problem, and use the knowledge of security network security problems are analyzed. Sec

APA, Harvard, Vancouver, ISO, and other styles

49

Sitorus, Felix Noel, and Ruki Harwahyu. "Analysis of Employee Capacity Gap in Managing Network Security and Its Implementation Towards Insider Threat Prevention." MALCOM: Indonesian Journal of Machine Learning and Computer Science 5, no. 2 (2025): 635–44. https://doi.org/10.57152/malcom.v5i2.1878.

Full text

Abstract:

Network security is crucial for protecting organizational information in the rapidly evolving digital era. Threats to networks do not only come from external sources, such as malware or hacking, but also from within the organization, known as insider threats. These threats can cause significant losses, whether due to intentional or unintentional actions by employees or internal parties with access to the system. Therefore, employees' ability to manage network security is key to addressing these threats. Handling insider threats must be a top priority for organizations. This study aims to analy

APA, Harvard, Vancouver, ISO, and other styles

50

Ahmad, Iftikhar, Qazi Emad Ul Haq, Muhammad Imran, Madini O. Alassafi, and Rayed A. AlGhamdi. "An Efficient Network Intrusion Detection and Classification System." Mathematics 10, no. 3 (2022): 530. http://dx.doi.org/10.3390/math10030530.

Full text

Abstract:

Intrusion detection in computer networks is of great importance because of its effects on the different communication and security domains. The detection of network intrusion is a challenge. Moreover, network intrusion detection remains a challenging task as a massive amount of data is required to train the state-of-the-art machine learning models to detect network intrusion threats. Many approaches have already been proposed recently on network intrusion detection. However, they face critical challenges owing to the continuous increase in new threats that current systems do not understand. Th

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!