Secure Short URL Generation Method that Recognizes Risk of Target URL

Mun, Hyung-Jin; Li, Yongzhen

doi:10.1007/s11277-016-3866-8

Cited by 7 publications

(6 citation statements)

References 10 publications

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“…Malicious URLs contains vulnerabilities and poses a significant threat to the computer. This malicious website threat has become an important rising issue [17,18,19]. Many studies have been proposed for analyzing and detecting malicious URLs.…”

Section: Related Workmentioning

confidence: 99%

“…Many types of research concerned about the risk and impact on their computer when surfing website. In [18] proposed risk assessment to monitor the risk on URL by using the destination information when generating a short URL. By monitoring URL, any risky URL or risk over the threshold will be blocked to prevent malicious attack [19], especially from drive-by download through the short URL.…”

Section: Related Workmentioning

confidence: 99%

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A malicious URLs detection system using optimization and machine learning classifiers

Lee

Heryanto

Razak

et al. 2020

IJEECS

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<span>The openness of the World Wide Web (Web) has become more exposed to cyber-attacks. An attacker performs the cyber-attacks on Web using malware Uniform Resource Locators (URLs) since it widely used by internet users. Therefore, a significant approach is required to detect malicious URLs and identify their nature attack. This study aims to assess the efficiency of the machine learning approach to detect and identify malicious URLs. In this study, we applied features optimization approaches by using a bio-inspired algorithm for selecting significant URL features which able to detect malicious URLs applications. By using machine learning approach with static analysis technique is used for detecting malicious URLs applications. Based on this combination as well as significant features, this paper shows promising results with higher detection accuracy. The bio-inspired algorithm: particle swarm optimization (PSO) is used to optimized URLs features. In detecting malicious URLs, it shows that naïve Bayes and support vector machine (SVM) are able to achieve high detection accuracy with rate value of 99%, using URL as a feature.</span>

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

A malicious URLs detection system using optimization and machine learning classifiers

Lee

Heryanto

Razak

et al. 2020

IJEECS

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show abstract

“…Therefore, most of the attacker sends a short URL to victims, and it is difficult to verify which file or webpage the short URL interfaces to users. Therefore, [ 35 ] proposed a method that composes the destination information of the short URL. Furthermore, the method analyzed the webpage and measured the risk of the webpage and blocked the short URL by comparing with predefined threshold.…”

Section: Literature Reviewmentioning

confidence: 99%

Detecting Phishing SMS Based on Multiple Correlation Algorithms

Sonowal

2020

SN COMPUT. SCI.

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The SMS phishing is another method where the phisher operates the SMS as a medium to communicate with the victims and this method is identified as smishing (SMS + phishing). Researchers promoted several anti-phishing methods where the correlation algorithm is applied to explore the relevancy of the features since there are numerous features in the features corpus. The correlation algorithm assesses the rank of the features that is the highest rank leads to the more relevant to the appropriate assignment. Therefore, this paper analyses four rank correlation algorithms particularly Pearson rank correlation, Spearman’s rank correlation, Kendall rank correlation, and Point biserial rank correlation with a machine-learning algorithm to determine the best features set for detecting Smishing messages. The result of the investigation reveals that the AdaBoost classifier offered better accuracy. Further analysis shows that the classifier with the ranking algorithm that is Kendall rank correlation appeared superior accuracy than the other correlation algorithms. The inferred of this experiment confirms that the ranking algorithm was able to reduce the dimension of features with 61.53% and presented an accuracy of 98.40%.

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“…The knowledge-based CES-D matrix is constructed based on highly reliable data determined from context information within the smart health system. The paper by Mun and Li [18] introduces a secure short URL-generation method that recognizes the risk posed by the target URL. The service provider of a short URL monitors the risk of the target URL page for the generated short URL and decides whether to provide the service.…”

mentioning

confidence: 99%

ICT-Based Wireless Personal Computing

Rhyu¹,

2017

Wireless Pers Commun

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Information and communications technologies (ICT)-based wireless personal computing has created increasing interest in convergence technology-based personal services, in which personal equipment is combined with wireless network-based services. Smart services, in which convergence technology services and hybrid peer-to-peer, personal environment network technology plus wireless network information technology are combined, are future-oriented. With the emergence of the smart mobile age, personal users can enjoy a lifestyle that uses content, such as information recommendation and personal services, based on various applications in smart IoT devices. This special issue introduces selected research papers by the authors who submitted them. This issue includes trends in ICTbased wireless personal computing, including digital convergence, hybrid networking systems, big data mining, interactive mobile applications, cloud services, secure data transmission, P2P network architectures, hybrid wireless protocols, index structures, multichannel protocols, crowdsourcing, future communications systems, network architectures, personal computing, short URL generation, and multicasting communications.The paper by Jeong and Shin [1] proposes an efficient access reduction scheme for big data based on total probability theory. Big data collected from a wide variety of areas shows a little variation in information search processing time, depending on the type and size of data. This study is on the reduction approach of divide-and-conquer; that is, it distinguishes all the attributes of data so as to minimize the data to improve the efficiency of data access based on the probability values within the big data group. The paper by Jung et al. [2] presents efficient malicious packet capture through an advanced & SangYeob Oh

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Secure Short URL Generation Method that Recognizes Risk of Target URL

Cited by 7 publications

References 10 publications

A malicious URLs detection system using optimization and machine learning classifiers

A malicious URLs detection system using optimization and machine learning classifiers

Detecting Phishing SMS Based on Multiple Correlation Algorithms

ICT-Based Wireless Personal Computing

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