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Users' behavioral prediction for phishing detection

Lung-Hao Lee, Kuei-Ching Lee, Yen-Cheng Juan, Hsin-Hsi Chen, Yuen-Hsien Tseng
2014 Proceedings of the 23rd International Conference on World Wide Web - WWW '14 Companion  
This study explores the users' web browsing behaviors that confront phishing situations for context-aware phishing detection.  ...  ., domain name, bag-of-words, generic Top-Level Domains, IP address, and port number, to develop a linear chain CRF model for users' behavioral prediction.  ...  We are also grateful to Trend Micro research laboratory for the support of click-through data.  ... 
doi:10.1145/2567948.2577320 dblp:conf/www/LeeLJCT14 fatcat:hnivqhmw3zcpxjjo5egyoif3t4

Replication: Challenges in Using Data Logs to Validate Phishing Detection Ability Metrics

Casey Inez Canfield, Alex Davis, Baruch Fischhoff, Alain Forget, Sarah Pearman, Jeremy Thomas
2017 Symposium On Usable Privacy and Security  
This paper demonstrates a new strategy for validating phishing detection ability metrics by comparing performance on a phishing signal detection task with data logs found in the SBO.  ...  The Security Behavior Observatory (SBO) is a longitudinal fieldstudy of computer security habits that provides a novel dataset for validating computer security metrics.  ...  (Nudging Users Towards Privacy); and the Hewlett Foundation, through the Center for Long-Term Cybersecurity (CLTC) at the University of California, Berkeley.  ... 
dblp:conf/soups/CanfieldDFFPT17 fatcat:ysyu47ahzfcv7nz26u33ertu7a

Prediction of Phishing Susceptibility Based on a Combination of Static and Dynamic Features

Rundong Yang, Kangfeng Zheng, Bin Wu, Chunhua Wu, Xiujuan Wang
2022 Mathematical Problems in Engineering  
Current research on phishing focuses on examining the static characteristics of the phishing behavior phenomenon, which cannot truly predict a user's susceptibility to phishing.  ...  According to the experimental results, the correct prediction rate of the DSM is higher than that for individual feature prediction, which reached 92.34%.  ...  issue for phishing prevention and detection is security awareness.  ... 
doi:10.1155/2022/2884769 doaj:81f2af8a73134b959be65b28fa1879eb fatcat:kcfvsbvaazgptaqsjg3pftmxru

An adaptive approach for internet phishing detection based on log data

Ahmed J. Obaid, Kareem K. Ibrahim, Azmi Shawkat Abdulbaqi, Salwa Mohammed Nejrs
2021 Periodicals of Engineering and Natural Sciences (PEN)  
behavior. and feature-extracting URL analysis to detect website phishing addresses.  ...  The proposed system for this paper includes efficient data extraction from the web file through data collection and preprocessing. and web usage mining procedure to extract features that demonstrate user  ...  Exploratory techniques are effective in detecting fraudulent websites, based on the characteristics of phishing websites and user behavior features.  ... 
doi:10.21533/pen.v9i4.2398 fatcat:hqmbnwsvbngcdmr5twui2st3oe

Predicting User Susceptibility to Phishing Based on Multidimensional Features

Rundong Yang, Kangfeng Zheng, Bin Wu, Di Li, Zhe Wang, Xiujuan Wang, Ahmed Mostafa Khalil
2022 Computational Intelligence and Neuroscience  
In this study, we propose the multidimensional phishing susceptibility prediction model (MPSPM) to implement the prediction of user phishing susceptibility.  ...  The experimental results indicated that some machine learning methods have high accuracy in predicting user phishing susceptibility, with a maximum accuracy rate of 89.04%.  ...  processes, knowledge and experience, and security behavior. ese are used as features for predicting user susceptibility using multidimensional features and multiple supervised machine learning methods  ... 
doi:10.1155/2022/7058972 pmid:35082844 pmcid:PMC8786481 fatcat:kjjr2wamwjb73ouixou5bqp34i

Developing a Framework for Detecting Phishing URLs using Machine Learning

Nguyen Tung Lam, Information Assurance dept. FPT University, Hanoi, Vietnam
2021 International Journal of Emerging Technology and Advanced Engineering  
Finally, based on the research results, we build a framework for detecting phishing URLs through endusers.  ...  Keywords— phishing URLs; detecting phishing URLs; abnormal behaviors of phishing URLs; Machine learning  ...  After obtaining the features and behavior of the URL, the API uses the RF algorithm to check whether this URL is a phishing URL or a clean URL. Developing API for detecting phishing URLs VI.  ... 
doi:10.46338/ijetae1121_08 fatcat:sjpchq2hnzdntmrox65paoy62i

Creative Persuasion: A Study on Adversarial Behaviors and Strategies in Phishing Attacks

Prashanth Rajivan, Cleotilde Gonzalez
2018 Frontiers in Psychology  
We aim at understanding human behaviors and strategies that adversaries use, and how these may determine the end-user response to phishing emails.  ...  Data from both phases of the study was combined and analyzed, to measure the effect of adversarial behaviors on end-user response to phishing emails.  ...  Future work could also test this paradigm as a training intervention for end-users to better detect phishing emails; similar to white-hat hackers, endusers could learn to think like hackers to better detect  ... 
doi:10.3389/fpsyg.2018.00135 pmid:29515478 pmcid:PMC5826381 fatcat:dxzgxypbbra3dbdlsmbbk5tgle

Phishing Detection

Gokul R, B.Sc. Information Technology Student Department of CS&IT, JAIN (Deemed-To-BeUniversity), Felix M Philip, Assistant Professor Department of CS&IT, JAIN (Deemed-To-Be University)
2022 Ymer  
So There are many ways to detect these phishing mails nowadays using Machine Learning. so using the phishing mail detector where these links could be tested and then predicted and to detect whether it  ...  Phishing is a type of social engineering attack often used to steal user data, including login credentials and credit card numbers.  ...  A predictive model for phishing detection Many anti-phishing systems are currently being developed to detect phishing content in online communication systems.  ... 
doi:10.37896/ymer21.06/39 fatcat:43p7oc6qivayvgd7ol4wyrvu3m

Iterating the Cybernetic Loops in Anti-Phishing Behavior: A Theoretical Integration

Alaa Nehme, Joey F. George
2018 Americas Conference on Information Systems  
As phishing emails represent continuous attack vectors, users' continuance in anti-phishing behavior is highly significant.  ...  Our model explores the (1) continuous interdependence of avoidance and adoption cognitive systems in anti-phishing behavior, and (2) continuous interdependence of education, awareness and training.  ...  Further research on integrated cybernetics and the interdependence of avoidance behavior, adoption behavior and SETA elements in information security is needed.  ... 
dblp:conf/amcis/NehmeG18a fatcat:7g4mcit545ambklzrzwat7bvdu

Phishing Attacks Root Causes [chapter]

Hossein Abroshan, Jan Devos, Geert Poels, Eric Laermans
2018 Lecture Notes in Computer Science  
There are a number of anti-phishing techniques and tools in place, but unfortunately phishing still works.  ...  The illustrated diagram is extendable with additional phishing causes.  ...  If we know that a psychological reason, for instance gullibility, is one of the root causes of phishing attacks then we can detect users' gullibility level, for example by using a psychological test and  ... 
doi:10.1007/978-3-319-76687-4_13 fatcat:wmpfd7siufcpnozanfble4p6va

Quantifying Phishing Susceptibility for Detection and Behavior Decisions

Casey Inez Canfield, Baruch Fischhoff, Alex Davis
2016 Human Factors  
Those responsible for managing security risks must understand user decision making in order to create and evaluate potential solutions.  ...  Results: In both experiments, despite exhibiting cautious behavior, participants' limited detection ability left them vulnerable to phishing attacks.  ...  In addition, we thank Carnegie Mellon's Behavior, Decision, and Policy Working Group and the CyLab Usable Privacy and Security Laboratory for their feedback.  ... 
doi:10.1177/0018720816665025 pmid:27562565 fatcat:qvhzmrbz3zgrzmo7xs6ipjf3be

Defending against Spear Phishing: Motivating Users through Fear appeal Manipulations

Sebastian Walter Schütz, Paul Benjamin Lowry, Jason Bennett Thatcher
2016 Pacific Asia Conference on Information Systems  
Unfortunately, anti-phishing training campaigns struggle with effectively fighting this threatpartially because users see security as a secondary priority, and partially because users are rarely motivated  ...  Overall, we (1) improve training based on PMT and CLT, (2) expand PMT for guiding fear appeal design; and (3) demonstrate a full application of CLT.  ...  The motivation to actively engage in protective behaviors becomes especially salient for spear phishing, as this type of attack is well disguised and hard to detect based solely upon visual cues.  ... 
dblp:conf/pacis/SchutzLT16 fatcat:7nladvb5jvalhptcoz2xgj3djm

PREVENTION OF PHISHING ATTACKS: A THREE-PILLARED APPROACH

2020 Issues in Information Systems  
This paper presents a three-pillared strategy for the prevention of phishing attacks.  ...  Phishing is a deceptive method of creating and distributing emails and/or websites that attempt to fool users into sharing sensitive financial or identification information.  ...  These barriers do not rely on human behavior, but rather attempt to predict the possible mistakes that humans can make and put a stop to the phishing before it happens.  ... 
doi:10.48009/2_iis_2020_1-8 fatcat:utxwhp377zde7odzwcw3e4mocy

Prediction of Phishing Website for e-Banking Using Data Mining Techniques

Nemmi Swathi Nemmi Swathi, C Maddilety C Maddilety
2021 International Journal of Engineering Technology and Management Sciences  
In this paper, we present a novel approach to overcome the difficulty and complexity in detecting and predicting e-banking phishing website.  ...  Classification Data Mining (DM) Techniques can be a very useful tool in detecting and identifying e-banking phishing websites.  ...  This type of e-banking websites is known as phishing website. In order to detect and predict e-banking phishing website.  ... 
doi:10.46647/ijetms.2021.v05i06.003 fatcat:os3gt4kypnchlkkzw64pwpnfvu

A Dynamic and Combined Phishing Detection Technique

2020 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
Therefore ,to deal with this conundrum we are putting forward a generalized algorithm for phishing detection with improved accuracy.  ...  seem real .Many systems and algorithms have been developed to predict phishing attacks .However ,the achievement rate of phishing attacks stays high and it's detection is prone towards high true negative  ...  Authors[10] have proposed a method to use random forest classifier for phishing detection.  ... 
doi:10.35940/ijitee.e2819.039520 fatcat:jfc3x2lbmnezzmd3gc423njfga
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