Deception Detection

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As I advance my research, I add to this page, so do check back from time to time :)


This page was last updated on 9 April 2024

Useful Research Papers

These are in chronological order, so scroll down to the bottom for the most recent papers. 

I have linked to the papers where they are available in the public domain. For unlinked papers, try searching the citation on Google Scholar and then emailing one or more of the authors to request a copy.


Hancock, Jeffrey T., Jennifer Thom-Santelli, and Thompson Ritchie. "Deception and design: The impact of communication technology on lying behavior." Proceedings of the SIGCHI conference on Human factors in computing systems. 2004.

Agyemang, Malik, Ken Barker, and Reda Alhajj. "Framework for mining web content outliers." Proceedings of the 2004 ACM symposium on Applied computing. 2004.

Dzindolet, Mary T., and Linda G. Pierce. "Using a linguistic analysis tool to detect deception." Proceedings of the Human Factors and Ergonomics Society Annual Meeting. Vol. 49. No. 3. Sage CA: Los Angeles, CA: SAGE Publications, 2005.

Liu, Wenyin, et al. "An antiphishing strategy based on visual similarity assessment." IEEE Internet Computing 10.2 (2006): 58-65.

Hancock, Jeffrey T., et al. "On lying and being lied to: A linguistic analysis of deception in computer-mediated communication." Discourse Processes 45.1 (2007): 1-23.

Ru, Yanbo, and Ellis Horowitz. "Automated classification of HTML forms on e‐commerce web sites." Online Information Review 31.4 (2007): 451-466.

Zhou, Lina, and Dongsong Zhang. "Following linguistic footprints: Automatic deception detection in online communication." Communications of the ACM 51.9 (2008): 119-122.

Qi, Xiaoguang, and Brian D. Davison. "Web page classification: Features and algorithms." ACM computing surveys (CSUR) 41.2 (2009): 1-31.

Tausczik, Yla R., and James W. Pennebaker. "The psychological meaning of words: LIWC and computerized text analysis methods." Journal of language and social psychology 29.1 (2010): 24-54.

van der Laan, Jake, Brodie M. Shannon, and Christopher Baker. "Identifying Internet mediated securities fraud: trends and technology." (2010). 

Maurer, Max-Emanuel, and Dennis Herzner. "Using visual website similarity for phishing detection and reporting." CHI'12 extended abstracts on human factors in computing systems. 2012. 1625-1630.

Mikolov, Tomas, et al. "Distributed representations of words and phrases and their compositionality." Advances in neural information processing systems 26 (2013).

Eswaran, Dhivya, Paul N. Bennett, and Joseph J. Pfeiffer III. "Modeling website topic cohesion at scale to improve webpage classification." Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2015.

Rao, Routhu Srinivasa, and Syed Taqi Ali. "A computer vision technique to detect phishing attacks." 2015 Fifth International Conference on Communication Systems and Network Technologies. IEEE, 2015.

Conroy, Nadia K., Victoria L. Rubin, and Yimin Chen. "Automatic deception detection: Methods for finding fake news." Proceedings of the association for information science and technology 52.1 (2015): 1-4.

Lau, Jey Han, and Timothy Baldwin. "An empirical evaluation of doc2vec with practical insights into document embedding generation." arXiv preprint arXiv:1607.05368 (2016).

Yao, Wenlin, et al. "Online deception detection refueled by real world data collection." arXiv preprint arXiv:1707.09406 (2017).

Maktabar, Mahdi, et al. "Content based fraudulent website detection using supervised machine learning techniques." Hybrid Intelligent Systems: 17th International Conference on Hybrid Intelligent Systems (HIS 2017) held in Delhi, India, December 14-16, 2017. Springer International Publishing, 2018.

Verma, Karunendra, Prateek Srivastava, and Prasun Chakrabarti. "Exploring structure oriented feature tag weighting algorithm for web documents identification." Soft Computing Systems: Second International Conference, ICSCS 2018, Kollam, India, April 19–20, 2018, Revised Selected Papers 2. Springer Singapore, 2018.

Khazane, Anish, et al. "Deeptrax: Embedding graphs of financial transactions." 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA). IEEE, 2019.

Corcoran, Craig, et al. "Disinformation: Detect to Disrupt." TTO. 2019.

Aydin, Mustafa, et al. "Using attribute-based feature selection approaches and machine learning algorithms for detecting fraudulent website URLs." 2020 10th Annual Computing and Communication Workshop and Conference (CCWC). IEEE, 2020.

Ciftci, Umur Aybars, Ilke Demir, and Lijun Yin. "Fakecatcher: Detection of synthetic portrait videos using biological signals." IEEE transactions on pattern analysis and machine intelligence (2020).

Yan, Xiaodan, et al. "Learning URL embedding for malicious website detection." IEEE Transactions on Industrial Informatics 16.10 (2020): 6673-6681.

Zhou, Xinyi, and Reza Zafarani. "A survey of fake news: Fundamental theories, detection methods, and opportunities." ACM Computing Surveys (CSUR) 53.5 (2020): 1-40.

Sun, Yanan, et al. "Automatically designing CNN architectures using the genetic algorithm for image classification." IEEE transactions on cybernetics 50.9 (2020): 3840-3854.

Dolhansky, Brian, et al. "The deepfake detection challenge (dfdc) dataset." arXiv preprint arXiv:2006.07397 (2020).

Hajek, Petr, Aliaksandr Barushka, and Michal Munk. "Fake consumer review detection using deep neural networks integrating word embeddings and emotion mining." Neural Computing and Applications 32.23 (2020): 17259-17274.

van der Laan, Jacob Jan. "The semantics of persuasion: a case study using phishing emails." (2021).

Sahoo, Somya Ranjan, and Brij B. Gupta. "Multiple features based approach for automatic fake news detection on social networks using deep learning." Applied Soft Computing 100 (2021): 106983.

Fornaciari, Tommaso, et al. "BERTective: Language models and contextual information for deception detection." Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume. Association for Computational Linguistics, 2021.

El-Din, Aml Emad, Ezz El-Din Hemdan, and Ayman El-Sayed. "Malweb: An efficient malicious websites detection system using machine learning algorithms." 2021 International Conference on Electronic Engineering (ICEEM). IEEE, 2021.

Mridha, Muhammad F., et al. "A comprehensive review on fake news detection with deep learning." IEEE access 9 (2021): 156151-156170.

Khoo, Eric, et al. "Fraudulent e-commerce website detection model using HTML, text and image features." Proceedings of the 11th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2019) 11. Springer International Publishing, 2021.

Zhang, Mengni, et al. "A new fraudulent website detection technology based on transfer learning." 2022 IEEE 5th International Conference on Automation, Electronics and Electrical Engineering (AUTEEE). IEEE, 2022.

Wankhade, Mayur, Annavarapu Chandra Sekhara Rao, and Chaitanya Kulkarni. "A survey on sentiment analysis methods, applications, and challenges." Artificial Intelligence Review 55.7 (2022): 5731-5780.

Gopal, Ram D., Afrouz Hojati, and Raymond A. Patterson. "Analysis of third-party request structures to detect fraudulent websites." Decision Support Systems 154 (2022): 113698.

Alsubari, S. Nagi, et al. "Data analytics for the identification of fake reviews using supervised learning." Computers, Materials & Continua 70.2 (2022): 3189-3204.

Groh, Matthew, et al. "Human Detection of Political Speech Deepfakes across Transcripts, Audio, and Video." arXiv preprint arXiv:2202.12883 (2022).

Cozzolino, Davide, et al. "Audio-visual person-of-interest deepfake detection." Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2023.

Zhou, Shengli, et al. "Multimodal fraudulent website identification method based on heterogeneous model ensemble." China Communications 20.5 (2023): 263-274.

Constâncio, Alex Sebastião, et al. "Deception detection with machine learning: A systematic review and statistical analysis." Plos one 18.2 (2023): e0281323.

Adane, Kibreab, Berhanu Beyene, and Mohammed Abebe. "Single and hybrid-ensemble learning-based phishing website detection: examining impacts of varied nature datasets and informative feature selection technique." Digital Threats: Research and Practice 4.3 (2023): 1-27.

Asudani, Deepak Suresh, Naresh Kumar Nagwani, and Pradeep Singh. "Impact of word embedding models on text analytics in deep learning environment: a review." Artificial intelligence review 56.9 (2023): 10345-10425.

Safi, Asadullah, and Satwinder Singh. "A systematic literature review on phishing website detection techniques." Journal of King Saud University-Computer and Information Sciences 35.2 (2023): 590-611.

Heidari, Arash, et al. "Deepfake detection using deep learning methods: A systematic and comprehensive review." Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery (2023): e1520.

Nanda, Neel, et al. "Progress measures for grokking via mechanistic interpretability." arXiv preprint arXiv:2301.05217 (2023).

Zhang, Mingxue, et al. "CSChecker: Revisiting GDPR and CCPA Compliance of Cookie Banners on the Web." 2024 IEEE/ACM 46th International Conference on Software Engineering (ICSE). IEEE Computer Society, 2024.

Zhou, Shengli, et al. "Image recognition model of fraudulent websites based on image leader decision and Inception-V3 transfer learning." China Communications 21.1 (2024): 215-227.

Gong, Liang Yu, and Xue Jun Li. "A Contemporary Survey on Deepfake Detection: Datasets, Algorithms, and Challenges." Electronics 13.3 (2024): 585.

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