Pub Date : 2024-01-18DOI: 10.1080/19361610.2024.2302241
Mine Özaşçılar
Recognizing that it is a widespread crime, retailers in Turkey have adopted Crime Prevention through Environmental Design (CPTED) techniques to prevent shoplifting. Using data from 1,150 young adul...
{"title":"Young Adults’ Perceptions of Store Environment: Evaluation of the Perceived Effectiveness of CPTED-Based Techniques in Preventing Shoplifting","authors":"Mine Özaşçılar","doi":"10.1080/19361610.2024.2302241","DOIUrl":"https://doi.org/10.1080/19361610.2024.2302241","url":null,"abstract":"Recognizing that it is a widespread crime, retailers in Turkey have adopted Crime Prevention through Environmental Design (CPTED) techniques to prevent shoplifting. Using data from 1,150 young adul...","PeriodicalId":44585,"journal":{"name":"Journal of Applied Security Research","volume":"14 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139552817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-08DOI: 10.1080/19361610.2023.2296765
Susan Henrico, Dries Putter
Intelligence collection is an integral part of the intelligence cycle. In fact, some authors declare that it is at the heart of the intelligence discipline. Intelligence collection is typically don...
情报收集是情报周期的一个组成部分。事实上，一些作者宣称它是情报学科的核心。情报收集工作通常...
{"title":"Intelligence Collection Disciplines—A Systematic Review","authors":"Susan Henrico, Dries Putter","doi":"10.1080/19361610.2023.2296765","DOIUrl":"https://doi.org/10.1080/19361610.2023.2296765","url":null,"abstract":"Intelligence collection is an integral part of the intelligence cycle. In fact, some authors declare that it is at the heart of the intelligence discipline. Intelligence collection is typically don...","PeriodicalId":44585,"journal":{"name":"Journal of Applied Security Research","volume":"111 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139397927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-30DOI: 10.1080/19361610.2023.2288419
Walid Dhifallah, Tarek Moulahi, Mounira Tarhouni, Salah Zidi
Many strategies use ML algorithms for intelligent IDS as part of the development of IoT security. These algorithms are quite susceptible to being manipulated to provide biased results. A variety of...
{"title":"Intelligent Chain: A Safer Decision-Making Framework with Blockchain-Based Incentives","authors":"Walid Dhifallah, Tarek Moulahi, Mounira Tarhouni, Salah Zidi","doi":"10.1080/19361610.2023.2288419","DOIUrl":"https://doi.org/10.1080/19361610.2023.2288419","url":null,"abstract":"Many strategies use ML algorithms for intelligent IDS as part of the development of IoT security. These algorithms are quite susceptible to being manipulated to provide biased results. A variety of...","PeriodicalId":44585,"journal":{"name":"Journal of Applied Security Research","volume":"177 ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138504943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-22DOI: 10.1080/19361610.2023.2279399
Bapi Saha, Ajoy Kumar Khan, Vuyyuru Lakshmi Lalitha, L. V. Narasimha Prasad
There are various new-age crime rackets reported with the help of digital technology and such cases are routinely investigated by the police and digital forensics analysts. In the course of investi...
{"title":"A Digital Forensics Model for the Examination of QR Code and Android App to Investigate Aadhaar Card Identity Fraud","authors":"Bapi Saha, Ajoy Kumar Khan, Vuyyuru Lakshmi Lalitha, L. V. Narasimha Prasad","doi":"10.1080/19361610.2023.2279399","DOIUrl":"https://doi.org/10.1080/19361610.2023.2279399","url":null,"abstract":"There are various new-age crime rackets reported with the help of digital technology and such cases are routinely investigated by the police and digital forensics analysts. In the course of investi...","PeriodicalId":44585,"journal":{"name":"Journal of Applied Security Research","volume":"143 ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138504950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-20DOI: 10.1080/19361610.2023.2277513
Brian K. Payne, Ida Oesteraas, David C. May
A critical shortage of cybersecurity talent exists in the United States. The lack of personnel has resulted in increased competition for the cybersecurity professionals. As the field of cybersecuri...
美国网络安全人才严重短缺。人才的缺乏导致了对网络安全专业人员的竞争加剧。随着网络安全领域…
{"title":"Cybersecurity Students’ Interest in Government Careers: Impact of Demographic Characteristics and Job Dynamics","authors":"Brian K. Payne, Ida Oesteraas, David C. May","doi":"10.1080/19361610.2023.2277513","DOIUrl":"https://doi.org/10.1080/19361610.2023.2277513","url":null,"abstract":"A critical shortage of cybersecurity talent exists in the United States. The lack of personnel has resulted in increased competition for the cybersecurity professionals. As the field of cybersecuri...","PeriodicalId":44585,"journal":{"name":"Journal of Applied Security Research","volume":"149 ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138504949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-20DOI: 10.1080/19361610.2023.2283666
Sirapat Boonkrong
Intelligent systems, machine learning models, and artificial intelligence methods are increasing in complexity, and the integration of such technologies has also increased. However, the rise in the...
智能系统、机器学习模型和人工智能方法的复杂性正在增加，这些技术的集成也在增加。然而，…
{"title":"Attack Model for Generic Intelligent Systems","authors":"Sirapat Boonkrong","doi":"10.1080/19361610.2023.2283666","DOIUrl":"https://doi.org/10.1080/19361610.2023.2283666","url":null,"abstract":"Intelligent systems, machine learning models, and artificial intelligence methods are increasing in complexity, and the integration of such technologies has also increased. However, the rise in the...","PeriodicalId":44585,"journal":{"name":"Journal of Applied Security Research","volume":"175 ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138504944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-10DOI: 10.1080/19361610.2023.2264068
Nisha Balani, Pallavi Chavan
AbstractBlockchains are a secure alternative for long-length data storage & security deployments. Though blockchains are unbounded, their quality of service (QoS) performance reduces after adding a certain number of blocks. Thus, sidechains have become essential for making the system decentralized, secure, and effective for use thereby improving their scalability & QoS performance. Sidechains reduce data storage and extraction delays. However, all sidechains of a single blockchain are the same in size, capacity, and security. This limits their application to real-world use cases that require dynamic security. To overcome this limitation, the authors propose a meta-heuristic approach to design a system that produces customized sidechains based on the quantity and quality of data stored on the chain. The model uses a machine-learning approach to find the best possible sidechain configuration for different data types. It makes the system fast and scalable and improves storage & memory efficiency. The proposed model is tested on multiple data sets and compared with various state-of-art sidechain deployments. An improvement of 18% in terms of mining speed, 27% in terms of energy efficiency, 10% with regards to throughput, and 8% concerning packet delivery ratio is observed. The model is tested under various attacks and faulty nodes to validate its security performance. A consistent QoS performance is observed for the proposed model under these attack types, thereby validating its resiliency for different attacks. This enhancement in performance makes the proposed model eligible for deployment in high-speed, low-energy, and high-security applications like IoT, mobile ad-hoc networks, and sensor networks.Keywords: Blockchainsidechainthroughputenergy consumptionQoSmeta-heuristic
{"title":"CSIMH: Design of an Efficient Security-Aware Customized Sidechaining Model via Iterative Meta-Heuristics","authors":"Nisha Balani, Pallavi Chavan","doi":"10.1080/19361610.2023.2264068","DOIUrl":"https://doi.org/10.1080/19361610.2023.2264068","url":null,"abstract":"AbstractBlockchains are a secure alternative for long-length data storage & security deployments. Though blockchains are unbounded, their quality of service (QoS) performance reduces after adding a certain number of blocks. Thus, sidechains have become essential for making the system decentralized, secure, and effective for use thereby improving their scalability & QoS performance. Sidechains reduce data storage and extraction delays. However, all sidechains of a single blockchain are the same in size, capacity, and security. This limits their application to real-world use cases that require dynamic security. To overcome this limitation, the authors propose a meta-heuristic approach to design a system that produces customized sidechains based on the quantity and quality of data stored on the chain. The model uses a machine-learning approach to find the best possible sidechain configuration for different data types. It makes the system fast and scalable and improves storage & memory efficiency. The proposed model is tested on multiple data sets and compared with various state-of-art sidechain deployments. An improvement of 18% in terms of mining speed, 27% in terms of energy efficiency, 10% with regards to throughput, and 8% concerning packet delivery ratio is observed. The model is tested under various attacks and faulty nodes to validate its security performance. A consistent QoS performance is observed for the proposed model under these attack types, thereby validating its resiliency for different attacks. This enhancement in performance makes the proposed model eligible for deployment in high-speed, low-energy, and high-security applications like IoT, mobile ad-hoc networks, and sensor networks.Keywords: Blockchainsidechainthroughputenergy consumptionQoSmeta-heuristic","PeriodicalId":44585,"journal":{"name":"Journal of Applied Security Research","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136295779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-02DOI: 10.1080/19361610.2022.2079906
Susanto , D. Stiawan, Dian Palupi Rini, M. Arifin, Mohd Yazid Bin Idris, Nizar Alsharif, R. Budiarto
Abstract The Internet of Things (IoT) has unique characteristics with a minimalist design and has network access with great scalability, which makes it difficult to control access. Setting up an intrusion detection system (IDS) on an IoT system while taking into account its unique characteristics is a big challenge. In this paper, we propose a dimensional reduction approach utilizing the fast independent component analysis (ICA) method to address scalability issues of IDS for IoT systems. Experimental results show that the reduction of dimensions by the fast ICA method overall improves the IDS execution time and does not significantly affect accuracy.
物联网(Internet of Things, IoT)具有极简设计的独特特点，其网络接入具有极大的可扩展性，使得接入控制变得困难。在物联网系统上设置入侵检测系统(IDS)，同时考虑到其独特的特性是一项巨大的挑战。在本文中，我们提出了一种利用快速独立分量分析(ICA)方法来解决物联网系统IDS的可扩展性问题的降维方法。实验结果表明，快速ICA方法的降维总体上提高了IDS的执行时间，且对准确率没有显著影响。
{"title":"Dimensional Reduction With Fast ICA for IoT Botnet Detection","authors":"Susanto , D. Stiawan, Dian Palupi Rini, M. Arifin, Mohd Yazid Bin Idris, Nizar Alsharif, R. Budiarto","doi":"10.1080/19361610.2022.2079906","DOIUrl":"https://doi.org/10.1080/19361610.2022.2079906","url":null,"abstract":"Abstract The Internet of Things (IoT) has unique characteristics with a minimalist design and has network access with great scalability, which makes it difficult to control access. Setting up an intrusion detection system (IDS) on an IoT system while taking into account its unique characteristics is a big challenge. In this paper, we propose a dimensional reduction approach utilizing the fast independent component analysis (ICA) method to address scalability issues of IDS for IoT systems. Experimental results show that the reduction of dimensions by the fast ICA method overall improves the IDS execution time and does not significantly affect accuracy.","PeriodicalId":44585,"journal":{"name":"Journal of Applied Security Research","volume":"18 1","pages":"665 - 688"},"PeriodicalIF":1.3,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44940991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Using the dataset of the first nationwide victimization survey in Azerbaijan, the current paper analyzed whether home security systems have a relationship with the perceived probability of property crime victimization. The ordinal logistic regression analysis was employed. Examination of the distribution of security systems identified that dwelling type, residential location and income had a higher level of significance than the perceived risk of property crime victimization in predicting the level of security systems at home. As to the predictive capacity of security systems in relation to the perceived risk of property crime victimization, the former is statistically significant. Additionally, being a victim of property crime, residential location, age, and perceived neighborhood disorder level predicted the perceived risk of property crime victimization.
{"title":"The Analysis of the Relationship between residents’ Perceived Probability of Property Victimization in Dwellings and the Level of Home Security Systems","authors":"Ingilab Shahbazov, Zaur Afandiyev, Ayshem Balayeva","doi":"10.1080/19361610.2023.2240305","DOIUrl":"https://doi.org/10.1080/19361610.2023.2240305","url":null,"abstract":"Using the dataset of the first nationwide victimization survey in Azerbaijan, the current paper analyzed whether home security systems have a relationship with the perceived probability of property crime victimization. The ordinal logistic regression analysis was employed. Examination of the distribution of security systems identified that dwelling type, residential location and income had a higher level of significance than the perceived risk of property crime victimization in predicting the level of security systems at home. As to the predictive capacity of security systems in relation to the perceived risk of property crime victimization, the former is statistically significant. Additionally, being a victim of property crime, residential location, age, and perceived neighborhood disorder level predicted the perceived risk of property crime victimization.","PeriodicalId":44585,"journal":{"name":"Journal of Applied Security Research","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135420855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-30DOI: 10.1080/19361610.2023.2240281
Folahanmi Aina
{"title":"Politics of “Localised Legitimacy”, Vigilantism, Non-State Policing and Counter-Banditry in Northwest Nigeria: Evidence from the Epicenter","authors":"Folahanmi Aina","doi":"10.1080/19361610.2023.2240281","DOIUrl":"https://doi.org/10.1080/19361610.2023.2240281","url":null,"abstract":"","PeriodicalId":44585,"journal":{"name":"Journal of Applied Security Research","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48296573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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