Social phishing
Open accessAbstract
Sometimes a "friendly" email message tempts recipients to reveal more online than they otherwise would, playing right into the sender's hand.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In Jagatic et al., the phishing attack contains three separate steps for data gathering, payload distribution and deception.
“In [Jagatic et al. 2007], the phishing attack contains three separate steps for data gathering, payload distribution and deception.”
From A Taxonomy of Attacks and a Survey of Defence Mechanisms for Semantic Social Engineering Attacks (2016) · cites this paper as Jagatic et al. 2007
Cited by
Sorted by citations
Social network sites: definition, history, and scholarship
boyd, D. M., & Ellison, N. B. (2007) · Journal of Computer-Mediated Communication · doi:10.1111/j.1083-6101.2007.00393.x · Cited by 16,251 · see citing works
Imagined Communities: Awareness, Information Sharing, and Privacy on the Facebook
Acquisti, A., & Gross, R. (2006) · Lecture Notes in Computer Science · doi:10.1007/11957454_3 · Cited by 1,895 · see citing works
The spread of low-credibility content by social bots
Shao, C., Ciampaglia, G. L., Varol, O., Yang, K.-C., Flammini, A., & Menczer, F. (2018) · Nature Communications · doi:10.1038/s41467-018-06930-7 · Cited by 1,125 · see citing works
Self-citationDetecting spammers on social networks
Stringhini, G., Kruegel, C., & Vigna, G. (2010) · Proceedings of the 26th Annual Computer Security Applications Conference · doi:10.1145/1920261.1920263 · Cited by 791 · see citing works
Uncovering social spammers: social honeypots + machine learning
Lee, K., Caverlee, J., & Webb, S. (2010) · Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval · doi:10.1145/1835449.1835522 · Cited by 619 · see citing works
Advanced social engineering attacks
Krombholz, K., Hobel, H., Huber, M., & Weippl, E. (2015) · Journal of Information Security and Applications · doi:10.1016/j.jisa.2014.09.005 · Cited by 575 · see citing works
Arming the public with artificial intelligence to counter social bots
Yang, K., Varol, O., Davis, C. A., Ferrara, E., Flammini, A., & Menczer, F. (2019) · Human Behavior and Emerging Technologies · doi:10.1002/hbe2.115 · Cited by 419 · see citing works
“Unlike other social engineering attacks, such as spear phishing (Jagatic et al., 2007), bots can achieve scalability through automation.”
BackgroundSelf-citationUncovering Large Groups of Active Malicious Accounts in Online Social Networks
Cao, Q., Yang, X., Yu, J., & Palow, C. (2014) · Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security · doi:10.1145/2660267.2660269 · Cited by 274 · see citing works
A Taxonomy of Attacks and a Survey of Defence Mechanisms for Semantic Social Engineering Attacks
Heartfield, R., & Loukas, G. (2016) · ACM Computing Surveys · doi:10.1145/2835375 · Cited by 202 · see citing works
Social engineering attack examples, templates and scenarios
Mouton, F., Leenen, L., & Venter, H. S. (2016) · Computers & Security · doi:10.1016/j.cose.2016.03.004 · Cited by 194 · see citing works
A survey of phishing attack techniques, defence mechanisms and open research challenges
Jain, A. K., & Gupta, B. B. (2022) · Enterprise Information Systems · doi:10.1080/17517575.2021.1896786 · Cited by 192 · see citing works
Stringhini, G., Wang, G., Egele, M., Kruegel, C., Vigna, G., Zheng, H., & Zhao, B. Y. (2013) · Proceedings of the 2013 conference on Internet measurement conference · doi:10.1145/2504730.2504731 · Cited by 169 · see citing works
The Moral Psychology of Artificial Intelligence
Bonnefon, J.-F., Rahwan, I., & Shariff, A. (2024) · Annual Review of Psychology · doi:10.1146/annurev-psych-030123-113559 · Cited by 151 · see citing works
Privacy Awareness: A Means to Solve the Privacy Paradox?
Pötzsch, S. (2009) · IFIP Advances in Information and Communication Technology · doi:10.1007/978-3-642-03315-5_17 · Cited by 107 · see citing works
Human Cognition Through the Lens of Social Engineering Cyberattacks
Montañez, R., Golob, E., & Xu, S. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.01755 · Cited by 106 · see citing works
Detection of malicious social bots: A survey and a refined taxonomy
Latah, M. (2020) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.113383 · Cited by 94 · see citing works
Predicting Phishing Websites Using Classification Mining Techniques with Experimental Case Studies
Aburrous, M., Hossain, M. A., Dahal, K., & Thabtah, F. (2010) · 2010 Seventh International Conference on Information Technology: New Generations · doi:10.1109/itng.2010.117 · Cited by 86 · see citing works
The decision to access patient information from a social media site: what would you do?
Jent, J. F., Eaton, C. K., Merrick, M. T., Englebert, N. E., Dandes, S. K., Chapman, A. V., & Hershorin, E. R. (2011) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2011.02.004 · Cited by 79 · see citing works
“[7] Jagatic TN, Johnson NA, Jakobsson M, et al.”
BackgroundWhat Happens After You Are Pwnd: Understanding the Use of Leaked Webmail Credentials in the Wild
Onaolapo, J., Mariconti, E., & Stringhini, G. (2016) · Proceedings of the 2016 Internet Measurement Conference · doi:10.1145/2987443.2987475 · Cited by 74 · see citing works
Automated Decision-Making and Big Data: Concerns for People With Mental Illness
Monteith, S., & Glenn, T. (2016) · Current Psychiatry Reports · doi:10.1007/s11920-016-0746-6 · Cited by 62 · see citing works
Chen, Y., Zahedi, F. M., Abbasi, A., & Dobolyi, D. (2021) · Information & Management · doi:10.1016/j.im.2020.103394 · Cited by 53 · see citing works
Personality, emotion and individual differences in response to online fraud
Norris, G., & Brookes, A. (2021) · Personality and Individual Differences · doi:10.1016/j.paid.2020.109847 · Cited by 50 · see citing works
Hamby, S., Blount, Z., Smith, A., Jones, L., Mitchell, K., & Taylor, E. (2018) · Journal of Trauma & Dissociation · doi:10.1080/15299732.2018.1441357 · Cited by 46 · see citing works
Social Engineering and Insider Threats
Xiangyu, L., Qiuyang, L., & Chandel, S. (2017) · 2017 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC) · doi:10.1109/cyberc.2017.91 · Cited by 43 · see citing works
Social engineering in social networking sites: Affect-based model
Algarni, A., Xu, Y., Chan, T., & Tian, Y.-C. (2013) · 8th International Conference for Internet Technology and Secured Transactions (ICITST-2013) · doi:10.1109/icitst.2013.6750253 · Cited by 41 · see citing works
Ferrara, E. (2023) · doi:10.2139/ssrn.4614223 · Cited by 266 · see citing works
The anatomy of written scam communications: An empirical analysis
Carter, E. (2015) · Crime Media Culture An International Journal · doi:10.1177/1741659015572310 · Cited by 26 · see citing works
Vulnerability to social engineering in social networks: a proposed user-centric framework
Albladi, S., & Weir, G. R. S. (2016) · 2016 IEEE International Conference on Cybercrime and Computer Forensic (ICCCF) · doi:10.1109/icccf.2016.7740435 · Cited by 22 · see citing works
Measuring Source Credibility of Social Engineering Attackers on Facebook
Algarni, A., Xu, Y., & Chan, T. (2016) · 2016 49th Hawaii International Conference on System Sciences (HICSS) · doi:10.1109/hicss.2016.460 · Cited by 18 · see citing works
Open Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agents
de Witt, C. S., Krawiecka, K., Krawczuk, I., Hagag, B., Anderson, W. L., Belcak, P., Bucknall, B., Cai, X., Chopra, A., Cohen, D., et al. (2025) · arXiv · doi:10.48550/arxiv.2505.02077 · Cited by 2 · see citing works
- Authors
- Jagatic, T. N., Johnson, N. A., Jakobsson, M., & Menczer, F.
- Affiliations
- Massachusetts Institute of Technology (US)
- Indiana University Bloomington (US)
- Venue
- Communications of the ACM
- Published
- 2007-10
- Volume
- 50
- Issue
- 10
- Pages
- 94-100
- ISSN
- 0001-0782 (ISSN-L)
- 1557-7317
- OpenAlex
- W2335888457
- Cited by
- 1,156
- References
- 0
- Citations by year
- 2026: 23 · 2025: 46 · 2024: 34 · 2023: 42 · 2022: 35 · 2021: 69 · 2020: 83 · 2019: 55 · 2018: 71 · 2017: 64 · 2016: 70 · 2015: 65 · 2014: 76 · 2013: 67 · 2012: 91
- FWCI
- 163.58
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Communications of the ACM (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Spam and Phishing Detection
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Physical Sciences › Computer Science › Information Systems › Cybercrime and Law Enforcement Studies
- Keywords
- email, information disclosure, online privacy, social engineering, email security
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review