Advances in Computer Network Security and Information Retrieval Technology

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 11873

Special Issue Editor

Department of Computer Science, International Islamic University Malaysia, Kuala Lumpur 50728, Malaysia
Interests: computer network; computer network security

Special Issue Information

Dear Colleagues,

Modern civilizations rely heavily on the availability of trustworthy forms of networked communication. Information retrieval technology relies heavily on annotating and extracting information attributes. Operating and protecting computer networks in the face of a persistent security threat is difficult. The state of the art in computer network protection methods and tools is critical. Substantial consideration given to the integrated nature of network security tools, policies, and administrative goals. Data organisation is the other main focus and the key to implementing good information retrieval technology. To protect the privacy of information transmitted over the internet, information retrieval through a network is not simply an effective method of gathering data. This Special Issue on “Advances in Computer Network Security and Information Retrieval Technology” provides an in-depth look at the practical applications and future directions of computer network security and information retrieval technology after a review of their current condition.

Dr. Adamu I. Abubakar
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • network security
  • information retrieval
  • confidentiality, autheinticity, privacy
  • search engine

Published Papers (5 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Jump to: Review

24 pages, 1485 KiB  
Article
Hybrid Detection Technique for IP Packet Header Modifications Associated with Store-and-Forward Operations
by Asmaa Munshi
Appl. Sci. 2023, 13(18), 10229; https://doi.org/10.3390/app131810229 - 12 Sep 2023
Viewed by 789
Abstract
The detection technique for IP packet header modifications associated with store-and-forward operation pertains to a methodology or mechanism utilized for the identification and detection of alterations made to packet headers within a network setting that utilizes a store-and-forward operation. The problem that led [...] Read more.
The detection technique for IP packet header modifications associated with store-and-forward operation pertains to a methodology or mechanism utilized for the identification and detection of alterations made to packet headers within a network setting that utilizes a store-and-forward operation. The problem that led to employing this technique lies with the fact that previous research studies expected intrusion detection systems (IDSs) to perform everything associated with inspecting the entire network transmission session for detecting any modification. However, in the store-and-forward process, upon arrival at a network node such as a router or switch, a packet is temporarily stored prior to being transmitted to its intended destination. Throughout the duration of storage, IDS operation tasks would not be able to store that packet; however, it is possible that certain adjustments or modifications could be implemented to the packet headers that IDS does not recognize. For this reason, this current research uses a combination of a convolutional neural network and long short-term memory to predict the detection of any modifications associated with the store-and-forward process. The combination of CNN and LSTM suggests a significant improvement in the model’s performance with an increase in the number of packets within each flow: on average, 99% detection performance was achieved. This implies that when comprehending the ideal pattern, the model exhibits accurate predictions for modifications in cases where the transmission abruptly increases. This study has made a significant contribution to the identification of IP packet header modifications that are linked to the store-and-forward operation. Full article
Show Figures

Figure 1

17 pages, 2918 KiB  
Article
Illegal Domain Name Generation Algorithm Based on Character Similarity of Domain Name Structure
by Yuchen Liang, Yanan Cheng, Zhaoxin Zhang, Tingting Chai and Chao Li
Appl. Sci. 2023, 13(6), 4061; https://doi.org/10.3390/app13064061 - 22 Mar 2023
Cited by 1 | Viewed by 1364
Abstract
Detecting and controlling illegal websites (gambling and pornography sites) through illegal domain names has been an unsolved problem. Therefore, how to mine and discover potential illegal domain names in advance has become a current research hotspot. This paper studies a method of generating [...] Read more.
Detecting and controlling illegal websites (gambling and pornography sites) through illegal domain names has been an unsolved problem. Therefore, how to mine and discover potential illegal domain names in advance has become a current research hotspot. This paper studies a method of generating illegal domain names based on the character similarity of domain name structure. Firstly, the K-means algorithm classified illegal domain names with similar structures. Then, put the classified clusters into the adversarial generative network for training. Finally, through a specific result verification method, the experiment shows that the average concentration of the generation algorithm is 23.82%, the effective concentration is 63.54%, and the expansion rate is 7.5. By comparing the results with the enumeration algorithm, the generation algorithm has greatly improved in terms of generation efficiency and accuracy. Full article
Show Figures

Figure 1

16 pages, 857 KiB  
Article
EETO-GA: Energy Efficient Trajectory Optimization of UAV-IoT Collaborative System Using Genetic Algorithm
by M M Hafizur Rahman, Mohammed Al-Naeem, Anuradha Banerjee and Abu Sufian
Appl. Sci. 2023, 13(4), 2535; https://doi.org/10.3390/app13042535 - 16 Feb 2023
Cited by 4 | Viewed by 1129
Abstract
Unmanned aerial vehicle (UAVs) is capable of adding significant potential to the internet of thing (IoT) devices and hence smart UAV–IoT collaborative system has attracted the attention of many researchers. This system has to be energy efficient for its nature and functionalities. Optimized [...] Read more.
Unmanned aerial vehicle (UAVs) is capable of adding significant potential to the internet of thing (IoT) devices and hence smart UAV–IoT collaborative system has attracted the attention of many researchers. This system has to be energy efficient for its nature and functionalities. Optimized trajectory planning is a significant area of research for any automatic movable device. In this article, we propose a technique, called EETO-GA for energy-efficient trajectory optimization of UAV–IoT using a genetic algorithm (GA). This technique prescribes each device of: (i) the next timestamp of arrival on the present cluster of IoT devices, at which the task queue of its header contains the highest possible number of tasks, and (ii) the minimum amount of energy that requires to complete all the tasks present in task queue of the IoT device. This technique uses a GA for optimization where the fitness function is designed by optimizing objectives: (i) the total number of tasks that can be completed, (ii) minimization of consumed energy, and (iii) the number of devices that could be served. A GA is applied here to accommodate a large number of IoT devices. A binary method of encoding is applied and methods like cross-over and mutation are used to arrive at the optimal solution. Through a simulation study, the proposed technique shows significant improvement in terms of UAV energy saved (UAVE), energy saving in IoT devices (IoTDEC), the average delay in execution of the task (ADET), and the percentage of tasks that could be completed (PTSK). Proposed EETO-GA improved average UAVE: 43%, IoTDEC: 56%, PTSK: 7.5%, and ADET: 38% over the state of the art. Full article
Show Figures

Figure 1

Review

Jump to: Research

44 pages, 1816 KiB  
Review
A Survey on Bug Deduplication and Triage Methods from Multiple Points of View
by Cheng Qian, Ming Zhang, Yuanping Nie, Shuaibing Lu and Huayang Cao
Appl. Sci. 2023, 13(15), 8788; https://doi.org/10.3390/app13158788 - 29 Jul 2023
Viewed by 1298
Abstract
To address the issue of insufficient testing caused by the continuous reduction of software development cycles, many organizations maintain bug repositories and bug tracking systems to ensure real-time updates of bugs. However, each day, a large number of bugs is discovered and sent [...] Read more.
To address the issue of insufficient testing caused by the continuous reduction of software development cycles, many organizations maintain bug repositories and bug tracking systems to ensure real-time updates of bugs. However, each day, a large number of bugs is discovered and sent to the repository, which imposes a heavy workload on bug fixers. Therefore, effective bug deduplication and triage are of great significance in software development. This paper provides a comprehensive investigation and survey of the recent developments in bug deduplication and triage. The study begins by outlining the roadmap of the existing literature, including the research trends, mathematical models, methods, and commonly used datasets in recent years. Subsequently, the paper summarizes the general process of the methods from two perspectives—runtime information-based and bug report-based perspectives—and provides a detailed overview of the methodologies employed in relevant works. Finally, this paper presents a detailed comparison of the experimental results of various works in terms of usage methods, datasets, accuracy, recall rate, and F1 score. Drawing on key findings, such as the need to improve the accuracy of runtime information collection and refine the description information in bug reports, we propose several potential future research directions in the field, such as stack trace enrichment and the combination of new NLP models. Full article
Show Figures

Figure 1

24 pages, 670 KiB  
Review
A Systematic Literature Review on Penetration Testing in Networks: Future Research Directions
by Mariam Alhamed and M. M. Hafizur Rahman
Appl. Sci. 2023, 13(12), 6986; https://doi.org/10.3390/app13126986 - 09 Jun 2023
Cited by 3 | Viewed by 6194
Abstract
Given the widespread use of the internet at the individual, governmental, and nongovernmental levels, and the opportunities it offers, such as online shopping, security concerns may arise. Cyber criminals are responsible for stopping organizations’ access to internet, for stealing valuable and confidential data, [...] Read more.
Given the widespread use of the internet at the individual, governmental, and nongovernmental levels, and the opportunities it offers, such as online shopping, security concerns may arise. Cyber criminals are responsible for stopping organizations’ access to internet, for stealing valuable and confidential data, and causing other damage. Therefore, the network must be protected and meet security requirements. Network penetration testing is a type of security assessment used to find risk areas and vulnerabilities that threaten the security of a network. Thus, network penetration testing is designed to provide prevention and detection controls against attacks in the network. A tester looks for security issues in the network operation, design, or implementation of the particular company or organization. Thus, it is important to identify the vulnerabilities and identify the threats that may exploit them in order to find ways to reduce their dangers.The ports at risk are named and discussed in this study. Furthermore, we discuss the most common tools used for network penetration testing. Moreover, we look at potential attacks and typical remediation strategies that can be used to protect the vulnerable ports by reviewing the related publications. In conclusion, it is recommended that researchers in this field focus on automated network penetration testing. In the future, we will use machine learning in WLAN penetration testing, which provides new insight and high efficiency in performance. Moreover, we will train machine learning models to detect a wide range of vulnerabilities in order to find solutions to mitigate the risks in a short amount of time rather that through manual WLAN penetration testing, which consumes a lot of time. This will lead to improving security and reducing loss prevention. Full article
Show Figures

Figure 1

Back to TopTop