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New Insights on Intelligence and Security for Sustainable Applications

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A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (26 March 2023) | Viewed by 28310

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Special Issue Editors

Dr. Ilsun You

E-Mail Website
Guest Editor

Department of Information Security Engineering, Soonchunhyang University, 22 Soonchunhyang-ro, Shinchang-myeon, Asan-si 31538, Choongchungnam-do, Republic of Korea
Interests: 5G security; IoT security; authentication and access control; formal security analysis; mobile internet security
Special Issues, Collections and Topics in MDPI journals

Dr. Ramon Alcarria

E-Mail Website
Co-Guest Editor

School of Geospatial Engineering, Universidad Politécnica de Madrid, Madrid, Spain
Interests: service architectures; sensor networks; human-computer interaction and prosumer environments
Special Issues, Collections and Topics in MDPI journals

Dr. Pelin Angin

E-Mail Website
Co-Guest Editor

Computer Engineering, Middle East Technical University, 06800 Ankara, Turkey
Interests: 5G security; high-performance mobile-cloud computing; cloud computing and IoT security; distributed systems; blockchain
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

WISA is one of the main security research venues hosted by the Korea Institute of Information Security and Cryptology (KIISC) and sponsored by the Ministry of Science, ICT and Future Planning (MSIP), and co-sponsored by the Electronics and Telecommunications Research Institute (ETRI), the Korea Internet and Security Agency (KISA), and the National Security Research Institute (NSRI). It has successfully played an important role in the Korean flagship international security conference in particular. The primary focus of WISA 2020 will be on systems and network security, including all other technical and practical aspects of security applications. This Special Issue will include extended versions of selected papers from WISA 2020, along with general papers closely related to the conference themes.

We believe that this Special Issue will showcase the latest advances in systems and network security through the publication of not only the extended versions of outstanding papers presented at WISA 2020 but also general submissions of high quality.

Prof. Dr. Ilsun You
Dr. Ramon Alcarria
Dr. Pelin Angin
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. Sustainability 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

Analysis of network and security protocols
Anonymity and censorship-resistant technologies
Applications of cryptographic techniques
Authentication and authorization
Automated tools for source code/binary analysis
Automobile security
Botnet defense
Blockchain security
Critical infrastructure security
Denial-of-service attacks and countermeasures
Digital Forensics
Embedded systems security
Exploit techniques and automation
Hardware and physical security
HCI security and privacy
Intrusion detection and prevention
Malware analysis
Mobile/wireless/cellular system security
Network-based attacks
Network infrastructure security
Operating system security
Practical cryptanalysis (hardware, DRM, etc.)
Security policy
Side channel attacks and countermeasures
Storage and file systems security
Techniques for developing secure systems
Trustworthy computing
Trusted execution environments
Unmanned System Security for Vehicle/Drone/Ship Systems
Vulnerability research
Web security

Published Papers (10 papers)

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Research

Jump to: Review

15 pages, 5227 KiB

Open AccessArticle

Improvement of Negative Emotion Recognition in Visible Images Enhanced by Thermal Imaging

by Ji-Min Lee, Young-Eun An, EunSang Bak and Sungbum Pan

Sustainability 2022, 14(22), 15200; https://doi.org/10.3390/su142215200 - 16 Nov 2022

Cited by 4 | Viewed by 1321

Abstract

Facial expressions help in understanding the intentions of others as they are an essential means of communication, revealing human emotions. Recently, thermal imaging has been playing a complementary role in emotion recognition and is considered an alternative to overcome the drawbacks of visible imaging. Notably, a relatively severe recognition error of fear among negative emotions frequently occurs in visible imaging. This study aims to improve the recognition performance of fear by using the visible and thermal images acquired simultaneously. When fear was not recognized in a visible image, we analyzed the causes of misrecognition. We thus found the condition of replacing the image with a thermal image. It improved emotion recognition performance by 4.54% on average, compared to the performance of using only visible images. Finally, we confirmed that the thermal image effectively compensated for the visible image’s shortcomings. Full article

(This article belongs to the Special Issue New Insights on Intelligence and Security for Sustainable Applications)

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15 pages, 6316 KiB

Open AccessArticle

Verification of Privacy Protection Reliability through Mobile Forensic Approach Regarding iOS-Based Instant Messenger

by Jiho Shin and Jung-Taek Seo

Sustainability 2022, 14(20), 13281; https://doi.org/10.3390/su142013281 - 15 Oct 2022

Cited by 1 | Viewed by 1516

Abstract

With the diffusion of mobile devices and Internet hyperconnectivity technology, all daily living records of individuals are being recorded on mobile devices in real time. However, from the user’s point of view, the reliability of privacy protection, that is, whether the user’s data on the mobile device completely disappears when it is deleted, is critical. This is because, for the sustainability of social growth, it is necessary to control the digitalization and technology that heightens the risks of the future society. Therefore, this study aims to check the traces of the SQLite database to see if instant messenger messages deleted by the user can be recovered. When the SQLite database record is deleted, if the database shrink function or other application-level deletion does not work, it is possible to recover the deleted record. We chose two iOS-based instant messengers, WhatsApp and WeChat, and analyzed the SQLite DB file and Table Schema where messages are stored. As a result of the experiment in this study, it was verified that the area where the deleted message was stored in the SQLite DB file was overwritten with 0 × 00 or updated with a NULL value, making it impossible to recover the deleted message. This process operates at the app level, and user data is safely protected. Full article

(This article belongs to the Special Issue New Insights on Intelligence and Security for Sustainable Applications)

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22 pages, 2368 KiB

Open AccessArticle

Deep Model-Based Security-Aware Entity Alignment Method for Edge-Specific Knowledge Graphs

by Jongmo Kim, Kunyoung Kim, Mye Sohn and Gyudong Park

Sustainability 2022, 14(14), 8877; https://doi.org/10.3390/su14148877 - 20 Jul 2022

Cited by 3 | Viewed by 1366

Abstract

This paper proposes a deep model-based entity alignment method for the edge-specific knowledge graphs (KGs) to resolve the semantic heterogeneity between the edge systems’ data. To do so, this paper first analyzes the edge-specific knowledge graphs (KGs) to find unique characteristics. The deep model-based entity alignment method is developed based on their unique characteristics. The proposed method performs the entity alignment using a graph which is not topological but data-centric, to reflect the characteristics of the edge-specific KGs, which are mainly composed of the instance entities rather than the conceptual entities. In addition, two deep models, namely BERT (bidirectional encoder representations from transformers) for the concept entities and GAN (generative adversarial networks) for the instance entities, are applied to model learning. By utilizing the deep models, neural network models that humans cannot interpret, it is possible to secure data on the edge systems. The two learning models trained separately are integrated using a graph-based deep learning model GCN (graph convolution network). Finally, the integrated deep model is utilized to align the entities in the edge-specific KGs. To demonstrate the superiority of the proposed method, we perform the experiment and evaluation compared to the state-of-the-art entity alignment methods with the two experimental datasets from DBpedia, YAGO, and wikidata. In the evaluation metrics of Hits@k, mean rank (MR), and mean reciprocal rank (MRR), the proposed method shows the best predictive and generalization performance for the KG entity alignment. Full article

(This article belongs to the Special Issue New Insights on Intelligence and Security for Sustainable Applications)

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13 pages, 4211 KiB

Open AccessArticle

Multi-Session Surface Electromyogram Signal Database for Personal Identification

by Jin-Su Kim, Cheol-Ho Song, EunSang Bak and Sung-Bum Pan

Sustainability 2022, 14(9), 5739; https://doi.org/10.3390/su14095739 - 09 May 2022

Cited by 5 | Viewed by 1695

Abstract

Surface electromyogram (sEMG) refers to a biosignal acquired from the skin surface during the contraction of skeletal muscles, and a different signal waveform is generated, depending on the motion performed. Therefore, in contrast to generic personal identification, which uses only a piece of registered information, the sEMG changes the registered information in a personal identification method. The sEMG database (DB) for conventional personal identification has shortcomings, such as a few subjects and the inability to verify sEMG signal variability. In order to solve the problems of DBs, this paper describes a method for constructing a multi-session sEMG DB for many subjects. Data were obtained in two channels when each of the 200 subjects performed 12 motions. There were three sessions, and each motion was repeated 10 times in time intervals of a day or longer between each session. Furthermore, to verify the effectiveness of the constructed sEMG DB, we conducted a personal identification experiment. According to the experimental results, the accuracy for five subjects was 74.19%, demonstrating the applicability of the constructed multi-session sEMG DB. Full article

(This article belongs to the Special Issue New Insights on Intelligence and Security for Sustainable Applications)

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11 pages, 338 KiB

Open AccessArticle

Efficient Detection of Link-Flooding Attacks with Deep Learning

by Chih-Hsiang Hsieh, Wei-Kuan Wang, Cheng-Xun Wang, Shi-Chun Tsai and Yi-Bing Lin

Sustainability 2021, 13(22), 12514; https://doi.org/10.3390/su132212514 - 12 Nov 2021

Cited by 1 | Viewed by 1743

Abstract

The DDoS attack is one of the most notorious attacks, and the severe impact of the DDoS attack on GitHub in 2018 raises the importance of designing effective defense methods for detecting this type of attack. Unlike the traditional network architecture that takes too long to cope with DDoS attacks, we focus on link-flooding attacks that do not directly attack the target. An effective defense mechanism is crucial since as long as a link-flooding attack is undetected, it will cause problems over the Internet. With the flexibility of software-defined networking, we design a novel framework and implement our ideas with a deep learning approach to improve the performance of the previous work. Through rerouting techniques and monitoring network traffic, our system can detect a malicious attack from the adversary. A CNN architecture is combined to assist in finding an appropriate rerouting path that can shorten the reaction time for detecting DDoS attacks. Therefore, the proposed method can efficiently distinguish the difference between benign traffic and malicious traffic and prevent attackers from carrying out link-flooding attacks through bots. Full article

(This article belongs to the Special Issue New Insights on Intelligence and Security for Sustainable Applications)

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20 pages, 822 KiB

Open AccessArticle

Chaining Optimization Methodology: A New SHA-3 Implementation on Low-End Microcontrollers

by Young Beom Kim, Taek-Young Youn and Seog Chung Seo

Sustainability 2021, 13(8), 4324; https://doi.org/10.3390/su13084324 - 13 Apr 2021

Cited by 4 | Viewed by 2459

Abstract

Since the Keccak algorithm was selected by the US National Institute of Standards and Technology (NIST) as the standard SHA-3 hash algorithm for replacing the currently used SHA-2 algorithm in 2015, various optimization methods have been studied in parallel and hardware environments. However, in a software environment, the SHA-3 algorithm is much slower than the existing SHA-2 family; therefore, the use of the SHA-3 algorithm is low in a limited environment using embedded devices such as a Wireless Sensor Networks (WSN) enviornment. In this article, we propose a software optimization method that can be used generally to break through the speed limit of SHA-3. We combine the

θ

π

, and

ρ

processes into one, reducing memory access to the internal state more efficiently than conventional software methods. In addition, we present a new SHA-3 implementation for the proposed method in the most constrained environment, the 8-bit AVR microcontroller. This new implementation method, which we call the chaining optimization methodology, implicitly performs the

π

process of the f-function while minimizing memory access to the internal state of SHA-3. Through this, it achieves up to 26.1% performance improvement compared to the previous implementation in an AVR microcontroller and reduces the performance gap with the SHA-2 family to the maximum. Finally, we apply our SHA-3 implementation in Hash_Deterministic Random Bit Generator (Hash_DRBG), one of the upper algorithms of a hash function, to prove the applicability of our chaining optimization methodology on 8-bit AVR MCUs. Full article

(This article belongs to the Special Issue New Insights on Intelligence and Security for Sustainable Applications)

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14 pages, 5146 KiB

Open AccessArticle

AIS Meets IoT: A Network Security Mechanism of Sustainable Marine Resource Based on Edge Computing

by Han-Chieh Chao, Hsin-Te Wu and Fan-Hsun Tseng

Sustainability 2021, 13(6), 3048; https://doi.org/10.3390/su13063048 - 10 Mar 2021

Cited by 10 | Viewed by 2781

Abstract

The sustainable utilization of marine resources is a vital issue to enrich marine life and to prevent species extinction caused by overfishing. Nowadays, it is common that commercial and smaller vessels are equipped with an Automatic Identification System (AIS) and GPS for better vessel tracking to avoid vessel collision as well as mayday calls. Additionally, governments can monitor vessels’ sea activities through AIS messages, stopping them from overfishing or tracking if any vessel has caused marine pollution. However, because AIS devices cannot guarantee data security, they are susceptible to malicious attacks such as message modification or an illegitimate identity faking a distress signal that causes other vessels to change their course. Given the above, a comprehensive network security system of a sustainable marine environment should be proposed to ensure secure communication. In this paper, a stationary IoT-enabled (Internet of Things) vessel tracking system of a sustainable marine environment is proposed. The system combines network security, edge computing, and tracking management. It offers the following functions: (1) The IoT-based vessel tracking system tracks each aquafarmer’s farming zone and issues periodic warning to prevent vessel collision for pursuing a sustainable marine environment; (2) the system can serve as a relay station that evaluates whether a vessel’s AIS data is correct; (3) the system detects abnormal behavior and any irregular information to law enforcement; (4) the system’s network security mechanism adopts a group key approach to ensure secure communication between vessels; and (5) the proposed edge computing mechanism enables the tracking system to perform message authentication and analysis, and to reduce computational burden for the remote or cloud server. Experiment results indicate that our proposed system is feasible, secure, and sustainable for the marine environment, and the tendered network security mechanism can reduce the computational burden while still ensuring security. Full article

(This article belongs to the Special Issue New Insights on Intelligence and Security for Sustainable Applications)

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16 pages, 494 KiB

Open AccessArticle

Dynamic Membership Management in Anonymous and Deniable Distance Bounding

by Nam-Su Jho and Taek-Young Youn

Sustainability 2020, 12(24), 10330; https://doi.org/10.3390/su122410330 - 10 Dec 2020

Cited by 1 | Viewed by 1586

Abstract

For secure location proof in many applications, distance bounding protocols are considered as one of the useful tools that can be used in practice. In distance bounding protocols, a prover and a verifier can measure the distance between them by performing an interactive protocol. In general, the verifier is regarded as an honest service provider, and thus, an adversarial verifier is not considered for security analysis. However, we cannot ignore the possibility of the corruption of the verifier, which can spoil the prover’s privacy. To handle the security problem, a prover-anonymous and deniable distance bounding protocol is proposed, which can guarantee the privacy of the prover even though the verifier is corrupted. In this paper, we review the prover-anonymous and deniable distance bounding protocol in terms of the membership management, and we show that the communication overhead in the protocol for each membership change is

O (n)

where n is the number of users. Then, we propose an improved membership management technique, which can efficiently support membership change in terms of the communication overhead. The improved technique requires

O (1)

for each membership change instead of

O (n)

, as in the existing protocol. Full article

(This article belongs to the Special Issue New Insights on Intelligence and Security for Sustainable Applications)

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23 pages, 1715 KiB

Open AccessArticle

Faster Data Forwarding in Content-Centric Network via Overlaid Packet Authentication Architecture

by Taek-Young Youn, Joongheon Kim, David Mohaisen and Seog Chung Seo

Sustainability 2020, 12(20), 8746; https://doi.org/10.3390/su12208746 - 21 Oct 2020

Cited by 2 | Viewed by 1928

Abstract

Content-Centric Networking (CCN) is one of the emerging paradigms for the future Internet, which shifts the communication paradigm from host-centric to data-centric. In CCN, contents are delivered by their unique names, and a public-key-based signature is built into data packets to verify the authenticity and integrity of the contents. To date, research has tried to accelerate the validation of the given data packets, but existing techniques were designed to improve the performance of content verification from the requester’s viewpoint. However, we need to efficiently verify the validity of data packets in each forwarding engine, since the transmission of invalid packets influences not only security but also performance, which can lead to a DDoS (Distributed Denial of Service) attack on CCN. For example, an adversary can inject a number of meaningless packets into CCN to consume the forwarding engines’ cache and network bandwidth. In this paper, a novel authentication architecture is introduced, which can support faster forwarding by accelerating the performance of data validation in forwarding engines. Since all forwarding engines verify data packets, our authentication architecture can eliminate invalid packets before they are injected into other CCN nodes. The architecture utilizes public-key based authentication algorithms to support public verifiability and non-repudiation, but a novel technique is proposed in this paper to reduce the overhead from using PKI for verifying public keys used by forwarding engines and end-users in the architecture. The main merit of this work is in improving the performance of data-forwarding in CCN regardless of the underlying public-key validation mechanism, such as PKI, by reducing the number of accesses to the mechanism. Differently from existing approaches that forgive some useful features of the Naive CCN for higher performance, the proposed technique is the only architecture which can support all useful features given by the Naive CCN. Full article

(This article belongs to the Special Issue New Insights on Intelligence and Security for Sustainable Applications)

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Review

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21 pages, 577 KiB

Open AccessReview

Security of Zero Trust Networks in Cloud Computing: A Comparative Review

by Sirshak Sarkar, Gaurav Choudhary, Shishir Kumar Shandilya, Azath Hussain and Hwankuk Kim

Sustainability 2022, 14(18), 11213; https://doi.org/10.3390/su141811213 - 07 Sep 2022

Cited by 16 | Viewed by 9830

Abstract

Recently, networks have shifted from traditional in-house servers to third-party-managed cloud platforms due to its cost-effectiveness and increased accessibility toward its management. However, the network remains reactive, with less accountability and oversight of its overall security. Several emerging technologies have restructured our approach to the security of cloud networks; one such approach is the zero-trust network architecture (ZTNA), where no entity is implicitly trusted in the network, regardless of its origin or scope of access. The network rewards trusted behaviour and proactively predicts threats based on its users’ behaviour. The zero-trust network architecture is still at a nascent stage, and there are many frameworks and models to follow. The primary focus of this survey is to compare the novel requirement-specific features used by state-of-the-art research models for zero-trust cloud networks. In this manner, the features are categorized across nine parameters into three main types: zero-trust-based cloud network models, frameworks and proofs-of-concept. ZTNA, when wholly realized, enables network administrators to tackle critical issues such as how to inhibit internal and external cyber threats, enhance the visibility of the network, automate the calculation of trust for network entities and orchestrate security for users. The paper further focuses on domain-specific issues plaguing modern cloud computing networks, which leverage choosing and implementing features necessary for future networks and incorporate intelligent security orchestration, automation and response. The paper also discusses challenges associated with cloud platforms and requirements for migrating to zero-trust architecture. Finally, possible future research directions are discussed, wherein new technologies can be incorporated into the ZTA to build robust trust-based enterprise networks deployed in the cloud. Full article

(This article belongs to the Special Issue New Insights on Intelligence and Security for Sustainable Applications)

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