Design a mobile game for home computer users to prevent from “phishing attacks”

2011 ◽  
Author(s):  
Nalin Asanka Gamagedara Arachchilage ◽  
Melissa Cole
Keyword(s):  
Computer Users ◽  
Home Computer ◽  
Mobile Game ◽  
Phishing Attacks

scholarly journals Can a Mobile Game Teach Computer Users to Thwart Phishing Attacks?

2013 ◽  
Vol 6 (3/4) ◽  
pp. 720-730 ◽  
Author(s):  
Nalin Asanka Gamagedara Arachchilage ◽  
Steve Love ◽  
Carsten Maple
Keyword(s):  
Computer Users ◽  
Mobile Game ◽  
Phishing Attacks

scholarly journals How Do Home Computer Users Browse the Web?

2022 ◽  
Vol 16 (1) ◽  
pp. 1-27
Author(s):  
Kyle Crichton ◽  
Nicolas Christin ◽  
Lorrie Faith Cranor
Keyword(s):  
Internet Use ◽  
Computer Users ◽  
Future Research ◽  
Small Scale ◽  
The Internet ◽  
Home Computer ◽  
Security Behavior ◽  
Browsing Behavior ◽  
The Web ◽  
Analyze Data

With the ubiquity of web tracking, information on how people navigate the internet is abundantly collected yet, due to its proprietary nature, rarely distributed. As a result, our understanding of user browsing primarily derives from small-scale studies conducted more than a decade ago. To provide an broader updated perspective, we analyze data from 257 participants who consented to have their home computer and browsing behavior monitored through the Security Behavior Observatory. Compared to previous work, we find a substantial increase in tabbed browsing and demonstrate the need to include tab information for accurate web measurements. Our results confirm that user browsing is highly centralized, with 50% of internet use spent on 1% of visited websites. However, we also find that users spend a disproportionate amount of time on low-visited websites, areas with a greater likelihood of containing risky content. We then identify the primary gateways to these sites and discuss implications for future research.

scholarly journals Designing a Mobile Game to Teach Conceptual Knowledge of Avoiding “Phishing Attacks”

2012 ◽  
Vol 2 (1) ◽  
pp. 127-132 ◽  
Author(s):  
Nalin Asanka Gamagedara Arachchilage ◽  
Steve Love ◽  
Michael Scott
Keyword(s):  
Conceptual Knowledge ◽  
Mobile Game ◽  
Phishing Attacks

scholarly journals Review of the machine learning methods in the classification of phishing attack

2019 ◽  
Vol 8 (4) ◽  
pp. 1545-1555
Author(s):  
John Arthur Jupin ◽  
Tole Sutikno ◽  
Mohd Arfian Ismail ◽  
Mohd Saberi Mohamad ◽  
Shahreen Kasim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Computer Network ◽  
Computer Users ◽  
Machine Learning Method ◽  
Learning Method ◽  
Phishing Attacks ◽  
Internet Users ◽  
Internet Networks ◽  
Use Of Internet

The development of computer networks today has increased rapidly. This can be seen based on the trend of computer users around the world, whereby they need to connect their computer to the Internet. This shows that the use of Internet networks is very important, whether for work purposes or access to social media accounts. However, in widely using this computer network, the privacy of computer users is in danger, especially for computer users who do not install security systems in their computer. This problem will allow hackers to hack and commit network attacks. This is very dangerous, especially for Internet users because hackers can steal confidential information such as bank login account or social media login account. The attacks that can be made include phishing attacks. The goal of this study is to review the types of phishing attacks and current methods used in preventing them. Based on the literature, the machine learning method is widely used to prevent phishing attacks. There are several algorithms that can be used in the machine learning method to prevent these attacks. This study focused on an algorithm that was thoroughly made and the methods in implementing this algorithm are discussed in detail.

Detecting Phishing Sites Using URLs Collected from Emails

2013 ◽  
Vol 479-480 ◽  
pp. 916-922
Author(s):  
Chuan Sheng Wang ◽  
Fu Hau Hsu ◽  
Shih Jen Chen ◽  
Yan Ling Hwang ◽  
Min Hao Wu
Keyword(s):  
Web Sites ◽  
Personal Information ◽  
Computer Users ◽  
Web Pages ◽  
False Negatives ◽  
New Approach ◽  
Malicious Behavior ◽  
Phishing Attacks ◽  
Edge Router ◽  
The Web

Phishing is the malicious behavior of stealing personal information from computer users. It is a very popular account-theft-method among cyber criminals. Hence, developing a new approach to solve phishing attacks becomes an important issue. This paper proposes a router-based solution, called Shark, to phishing attacks. The router-based property allows Shark to protect a whole network without the need to install or maintain any software in any internal host. Based on the URLs collected from emails and the properties of the web pages pointed by these URLs, Shark quickly and automatically identifies phishing web pages. Experimental results demonstrate that Shark installed on a Linux edge router can accurately detect and attack phishing sites with low false positives and false negatives. And even though a false positive occurs, erroneous counterattacks do not influence the normal operations of legal web sites.

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