Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Applied Sciences
Special Issues
Emerging Technologies in Network Security and Cryptography
share announcement

Emerging Technologies in Network Security and Cryptography

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

Deadline for manuscript submissions: 20 November 2024 | Viewed by 4241

Special Issue Editors

Dr. Masoud Kaveh

E-Mail Website
Guest Editor
Department of Information and Communication Engineering, Aalto University, Espoo‎, ‎Finland
Interests: hardware security; machine learning; cryptographic protocols PUFs; IoT security; blockchain security; FPGA design; VHDL programming; applied cryptography; physical layer security
Dr. Diego Martín

E-Mail Website
Guest Editor
ETSI de Telecomunicación, Universidad Politécnica de Madrid, Av. Complutense 30, 28040 Madrid, Spain
Interests: Internet of Things; blockchain technologies; cyber physical systems; knowledge management; information retrieval
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In today's rapidly evolving digital landscape, ensuring the security and privacy of network communications has become paramount. The emergence of new technologies brings both opportunities and challenges in the field of network security and cryptography. This Special Issue aims to explore the latest advancements and innovations in these areas, focusing on the development and application of emerging technologies for enhanced network security and cryptography.

Scope and Topics of Interest:

We invite researchers and practitioners to contribute their original research, case studies, and reviews on various topics related to the emerging technologies in network security and cryptography. This Special Issue covers a broad range of subjects, including but not limited to:

  • Blockchain technology for secure and decentralized networks;
  • Machine learning and artificial intelligence for network threat detection and prevention;
  • Quantum-resistant cryptography and post-quantum security algorithms;
  • Privacy-preserving techniques for data protection and anonymity in networks;
  • Secure protocols for Internet of Things (IoT) and cyber-physical systems (CPS);
  • Secure communication and authentication mechanisms in wireless networks;
  • Cloud and edge computing security in distributed systems;
  • Privacy and security challenges in social networks and online platforms;
  • Threat intelligence and analysis for proactive network defense;
  • Secure software-defined networking (SDN) and network function virtualization (NFV);
  • Cryptographic protocols for secure data transmission and storage;
  • Emerging technologies for secure data sharing and collaboration;
  • Secure multi-party computation and homomorphic encryption techniques;
  • Hardware and physical layer security for network infrastructure;
  • Integration of emerging technologies with traditional security mechanisms.

Keynote Lectures and Tutorials:

In addition to research contributions, this Special Issue will include keynote lectures and tutorials from renowned experts in the field of network security and cryptography. These sessions will provide valuable insights into the latest trends, challenges, and future directions in emerging technologies.

Dr. Masoud Kaveh
Dr. Diego Martín
Guest Editors

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.

Published Papers (4 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Review

22 pages, 6228 KiB  
Article
Detecting Malicious Devices in IPSEC Traffic with IPv4 Steganography
by Gabriel Jekateryńczuk, Damian Jankowski, René Veyland and Zbigniew Piotrowski
Appl. Sci. 2024, 14(9), 3934; https://doi.org/10.3390/app14093934 - 5 May 2024
Viewed by 691
Abstract
This study investigates the application of steganography for enhancing network security by detecting and promptly eliminating malicious packets to prevent flooding and consequent denial of service attacks while also identifying malicious equipment. The paper discusses foundational concepts such as the prisoner’s dilemma, covert [...] Read more.
This study investigates the application of steganography for enhancing network security by detecting and promptly eliminating malicious packets to prevent flooding and consequent denial of service attacks while also identifying malicious equipment. The paper discusses foundational concepts such as the prisoner’s dilemma, covert channels, qualitative metrics, and existing steganography techniques in computer communications. An architecture was developed to assess the effectiveness of this solution, and experiments were conducted, with their results presented. This contribution leverages established steganographic principles and seamlessly integrates with widely adopted IPsec protocols, offering a solution to improve covert communication within computer networks. Full article
(This article belongs to the Special Issue Emerging Technologies in Network Security and Cryptography)
►▼ Show Figures

Figure 1

16 pages, 6863 KiB  
Article
HAE: A Hybrid Cryptographic Algorithm for Blockchain Medical Scenario Applications
by Ziang Chen, Jiantao Gu and Hongcan Yan
Appl. Sci. 2023, 13(22), 12163; https://doi.org/10.3390/app132212163 - 9 Nov 2023
Cited by 2 | Viewed by 1809
Abstract
The integration of cryptographic algorithms like Advanced Encryption Standard (AES) and Elliptic Curve Cryptography (ECC) is pivotal in bolstering the core attributes of blockchain technology, especially in achieving decentralization, tamper resistance, and anonymization within the realm of medical applications. Despite their widespread utilization, [...] Read more.
The integration of cryptographic algorithms like Advanced Encryption Standard (AES) and Elliptic Curve Cryptography (ECC) is pivotal in bolstering the core attributes of blockchain technology, especially in achieving decentralization, tamper resistance, and anonymization within the realm of medical applications. Despite their widespread utilization, the conventional AES and ECC face significant hurdles in security and efficiency when dealing with expansive medical data, posing a challenge to the effective preservation of patient privacy. In light of these challenges, this study introduces HAE (hybrid AES and ECC), an innovative hybrid cryptographic algorithm that ingeniously amalgamates the robustness of AES with the agility of ECC. HAE is designed to symmetrically encrypt original data with AES while employing ECC for the asymmetric encryption of the initial AES key. This strategy not only alleviates the complexities associated with AES key management but also enhances the algorithm’s security without compromising its efficiency. We provide an in-depth exposition of HAE’s deployment within a framework tailored for medical scenarios, offering empirical insights into its enhanced performance metrics. Our experimental outcomes underscore HAE’s exemplary security, time efficiency, and optimized resource consumption, affirming its potential as a breakthrough advancement for augmenting blockchain applications in the medical sector, heralding a new era of enhanced data security and privacy within this critical domain. Full article
(This article belongs to the Special Issue Emerging Technologies in Network Security and Cryptography)
►▼ Show Figures

Figure 1

23 pages, 5222 KiB  
Article
A Decision-Fusion-Based Ensemble Approach for Malicious Websites Detection
by Abed Alanazi and Abdu Gumaei
Appl. Sci. 2023, 13(18), 10260; https://doi.org/10.3390/app131810260 - 13 Sep 2023
Viewed by 777
Abstract
Malicious websites detection is one of the cyber-security tasks that protects sensitive information such as credit card details and login credentials from attackers. Machine learning (ML)-based methods have been commonly used in several applications of cyber-security research. Although there are some methods and [...] Read more.
Malicious websites detection is one of the cyber-security tasks that protects sensitive information such as credit card details and login credentials from attackers. Machine learning (ML)-based methods have been commonly used in several applications of cyber-security research. Although there are some methods and approaches proposed in the state-of-the-art studies, the advancement of the most effective solution is still of research interest and needs to be improved. Recently, decision fusion methods play an important role in improving the accuracy of ML methods. They are broadly classified based on the type of fusion into a voting decision fusion technique and a divide and conquer decision fusion technique. In this paper, a decision fusion ensemble learning (DFEL) model is proposed based on voting technique for detecting malicious websites. It combines the predictions of three effective ensemble classifiers, namely, gradient boosting (GB) classifier, extreme gradient boosting (XGB) classifier, and random forest (RF) classifier. We use these classifiers because their advantages to perform well for class imbalanced and data with statistical noises such as in the case of malicious websites detection. A weighted majority-voting rule is utilized for generating the final decisions of used classifiers. The experimental results are conducted on a publicly available large dataset of malicious and benign websites. The comparative study exposed that the DFEL model achieves high accuracies, which are 97.25% on average of 10-fold cross-validation test and 98.50% on a holdout of 30% test set. This confirms the ability of proposed approach to improve the detection rate of malicious websites. Full article
(This article belongs to the Special Issue Emerging Technologies in Network Security and Cryptography)
►▼ Show Figures

Figure 1

Review

Jump to: Research

16 pages, 257 KiB  
Review
Optimization Algorithms in SDN: Routing, Load Balancing, and Delay Optimization
by Maria Daniela Tache (Ungureanu), Ovidiu Păscuțoiu and Eugen Borcoci
Appl. Sci. 2024, 14(14), 5967; https://doi.org/10.3390/app14145967 - 9 Jul 2024
Viewed by 419
Abstract
Software-Defined Networking is today a mature technology, which is developed in many networks and also embedded in novel architectures like 5G and 6G. The SDN control centralization concept brings significant advantages for management and control in SDN together with the programmability of the [...] Read more.
Software-Defined Networking is today a mature technology, which is developed in many networks and also embedded in novel architectures like 5G and 6G. The SDN control centralization concept brings significant advantages for management and control in SDN together with the programmability of the data plane. SDN represents a paradigm shift towards agile, efficient, and secure network infrastructures, moving away from traditional, hardware-centric models to embrace dynamic, software-driven paradigms. SDN is compliant also with the virtualization architecture defined in the Network Function Virtualization framework. However, SDN should cooperate seamlessly for some years with the distributed TCP/IP control developed during the years all over the world. Among others, the traditional tasks of routing, forwarding, load balancing, QoS assurance, security, and privacy should be solved. The SDN native centralization brings also some new challenges and problems which are different from the traditional distributed control IP networks. The algorithms and protocols usable in SDN should meet requirements like scalability, convergence, redundancy assurance, sustainability, and good real-time response, and allow orchestrated automation in enhancing network resilience and adaptability. This work presents a theoretical review of state-of-the-art SDN optimization techniques, offering a critical and comparative discussion of various algorithms having tasks such as routing (including dynamic ones), forwarding, load balancing and traffic optimization, and forwarding delay minimization. Attention is pointed to general algorithms which can offer pragmatic solutions for large systems or multiple metric routing. Full article
(This article belongs to the Special Issue Emerging Technologies in Network Security and Cryptography)
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-4
Back to TopTop