Today's social network sites: An analysis of emerging security risks and their counter measures

Hameed, Khizar; Rahman, N. U.

doi:10.1109/comtech.2017.8065764

Cited by 11 publications

(6 citation statements)

References 39 publications

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“…The attacks cause more and more economic losses. Mouton et al have clarified SE as "The science of using social interaction have a way to convince others to respond with an attacker request" [5]. SE attacks are carried out in several phases with malicious activities as in Table 1.…”

Section: Social Engineeringmentioning

confidence: 99%

“…In social sites, a phishing attack is the most serious Cyber-Attack [5] that could cause destructive losses [26]. It is the most critical aspect of threats to internet security.…”

Section: Social Network Phishing Attacksmentioning

confidence: 99%

“…OSNs applications like LinkedIn, Pinterest, Whatsapp, Facebook, and Twitter are important for communication with others via links with other members with common interests in the cloud despite thinking about geographical distances [4]. OSNs are not just for communication and continuous knowledge of the latest opinions and stories about any digital topic around the globe via the network [5]. In addition, they enhance E-Business by providing advertisements and promotions [6].…”

Section: Introductionmentioning

confidence: 99%

“…OSNs help in connecting people with similar interests and builds social relations. This leads to the availability of an enormous amount of users' information which attracts malicious users to open the way for criminals, perform undesired activities like phishing and identity theft, and begin attacks to access this information and violate the privacy of the users [5].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Machine Learning Techniques for Detecting Phishing URL Attacks

Mosa¹,

Shams²,

Abohany³

et al. 2023

Computers, Materials &Amp; Continua

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Cyber Attacks are critical and destructive to all industry sectors. They affect social engineering by allowing unapproved access to a Personal Computer (PC) that breaks the corrupted system and threatens humans. The defense of security requires understanding the nature of Cyber Attacks, so prevention becomes easy and accurate by acquiring sufficient knowledge about various features of Cyber Attacks. Cyber-Security proposes appropriate actions that can handle and block attacks. A phishing attack is one of the cybercrimes in which users follow a link to illegal websites that will persuade them to divulge their private information. One of the online security challenges is the enormous number of daily transactions done via phishing sites. As Cyber-Security have a priority for all organizations, Cyber-Security risks are considered part of an organization's risk management process. This paper presents a survey of different modern machine-learning approaches that handle phishing problems and detect with high-quality accuracy different phishing attacks. A dataset consisting of more than 11000 websites from the Kaggle dataset was utilized and studying the effect of 30 website features and the resulting class label indicating whether or not it is a phishing website (1 or −1). Furthermore, we determined the confusion matrices of Machine Learning models: Neural Networks (NN), Naïve Bayes, and Adaboost, and the results indicated that the accuracies achieved were 90.23%, 92.97%, and 95.43%, respectively.

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Section: Social Engineeringmentioning

confidence: 99%

“…In social sites, a phishing attack is the most serious Cyber-Attack [5] that could cause destructive losses [26]. It is the most critical aspect of threats to internet security.…”

Section: Social Network Phishing Attacksmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Machine Learning Techniques for Detecting Phishing URL Attacks

Mosa¹,

Shams²,

Abohany³

et al. 2023

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…But there are other cases like the aforementioned, including the example of a breach of the privacy of Sony users in 2011 (Social Media and Our Privacy, 2016, [5]). The issue of the security of social networking users, the breach of their personal data and other risks arising from the breach of personal data of users is a concern that necessarily accompanies the use of social networking sites by both users and researchers("Today's social network sites," 2017, [6]).…”

Section: Introductionmentioning

confidence: 99%

Risks Inherent in Inaccurate or Inadvertent Use of Social Networks in Greece

Stratigopoulou

Ntalianis

Kikili

et al. 2020

International Journal of Education and Information Technologies

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Social Networking Websites are not only the most widely used tools to facilitate communication in today's digital age, but they are also one of the biggest sources of Big Data. There are of course many benefits of data applications, for both ordinary users and professionals alike, but also there are many risks, that users of Social Networking Sites can face. As users' interest in using Social Networking Websites grows, so does their concern about the risks they pose. The purpose of this thesis is to investigate the risks posed by the use of Social Networking Websites to adult users in Greece and examine the behaviors of users that may lead to risk exposure, (behaviors such as Risk Taking, Privacy Behavior, Trust in SNS companies, Privacy Concern, Perceived Control of Information, Information Identity Disclosure will be examined).It will also examine the correlation of user behaviors and exposure to risk and socio-demographic data of users. The results of the present study show that exposure to Risk in SNS is related to gender and also “Privacy Behavior” and “Information Identity Disclosure” are related to Age and Educational Level

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An Investigation into Students Responses to Various Phishing Emails and Other Phishing-Related Behaviours

Frauenstein

2019

Communications in Computer and Information Science

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Today's social network sites: An analysis of emerging security risks and their counter measures

Cited by 11 publications

References 39 publications

Machine Learning Techniques for Detecting Phishing URL Attacks

Machine Learning Techniques for Detecting Phishing URL Attacks

Risks Inherent in Inaccurate or Inadvertent Use of Social Networks in Greece

An Investigation into Students Responses to Various Phishing Emails and Other Phishing-Related Behaviours

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