Fetching the paper…
Reading the bibliography…
The advanced capabilities of Large Language Models (LLMs) have made them invaluable across various applications, from conversational agents and content creation to data analysis, research, and innovation.
K. Papineni, S. Roukos, T. Ward, and W.-J. Zhu, “Bleu: a method for automatic evaluation of machine translation,” 2002. [Online]. Available:
2002
Earlier work this paper cites.
B. Klimt and Y. Yang, “The enron corpus: A new dataset for email classification research,” in
2004
Earlier work this paper cites.
C.-Y. Lin, “ROUGE: A Package for Automatic Evaluation of Summaries,” 2004. [Online]. Available:
2004
Earlier work this paper cites.
J. S. Downs, M. Holbrook, and L. F. Cranor, “Behavioral response to phishing risk,” in
2007
Earlier work this paper cites.
W. Dai, G.-R. Xue, Q. Yang, and Y. Yu, “Transferring naive bayes classifiers for text classification,” in
2007
Earlier work this paper cites.
L. Kang and J. Xiang, “Captcha phishing: A practical attack on human interaction proofing,” in
2009
Earlier work this paper cites.
I.-F. Lam, W.-C. Xiao, S.-C. Wang, and K.-T. Chen, “Counteracting phishing page polymorphism: An image layout analysis approach,” in
2009
Earlier work this paper cites.
——, “Captcha phishing: a practical attack on human interaction proofing,” in
2010
Earlier work this paper cites.
Z. Liu, X. Lv, K. Liu, and S. Shi, “Study on svm compared with the other text classification methods,” in
2010
Earlier work this paper cites.
J. Erkkila, “Why we fall for phishing,” in
2011
Earlier work this paper cites.
S. Afroz and R. Greenstadt, “Phishzoo: Detecting phishing websites by looking at them,” in
2011
Earlier work this paper cites.
T. Vidas, E. Owusu, S. Wang, C. Zeng, L. F. Cranor, and N. Christin, “Qrishing: The susceptibility of smartphone users to qr code phishing attacks,” in
2013
Earlier work this paper cites.
F. Rosner, A. Hinneburg, M. Röder, M. Nettling, and A. Both, “Evaluating topic coherence measures,”
2014
Earlier work this paper cites.
D. Lacey, P. Salmon, and P. Glancy, “Taking the bait: a systems analysis of phishing attacks,”
2015
Earlier work this paper cites.
X. Han, N. Kheir, and D. Balzarotti, “Phisheye: Live monitoring of sandboxed phishing kits,” in
2016
Earlier work this paper cites.
G. Varshney, M. Misra, and P. K. Atrey, “A survey and classification of web phishing detection schemes,”
2016
Earlier work this paper cites.
B. Liang, M. Su, W. You, W. Shi, and G. Yang, “Cracking classifiers for evasion: A case study on the google’s phishing pages filter,” in
2016
Earlier work this paper cites.
B. E. Gavett, R. Zhao, S. E. John, C. A. Bussell, J. R. Roberts, and C. Yue, “Phishing suspiciousness in older and younger adults: The role of executive functioning,”
2017
Earlier work this paper cites.
J. Mao, W. Tian, P. Li, T. Wei, and Z. Liang, “Phishing-alarm: robust and efficient phishing detection via page component similarity,”
2017
Earlier work this paper cites.
M. Shkatov. (2018, January) Chatting our way into creating a polymorphic malware. CyberArk. [Online]. Available:
2018
Earlier work this paper cites.
A. Oest, Y. Safei, A. Doupé, G.-J. Ahn, B. Wardman, and G. Warner, “Inside a phisher’s mind: Understanding the anti-phishing ecosystem through phishing kit analysis,” in
2018
Earlier work this paper cites.
2018
Earlier work this paper cites.
A. Cidon, L. Gavish, I. Bleier, N. Korshun, M. Schweighauser, and A. Tsitkin, “High precision detection of business email compromise,” in
2019
Earlier work this paper cites.
G. Ho, A. Cidon, L. Gavish, M. Schweighauser, V. Paxson, S. Savage, G. M. Voelker, and D. Wagner, “Detecting and characterizing lateral phishing at scale,” in
2019
Earlier work this paper cites.
2019
Earlier work this paper cites.
2019
Earlier work this paper cites.
C. Ventures, “Beware of lookalike domains in punycode phishing attacks,”
2019
Earlier work this paper cites.
B. Fouss, D. M. Ross, A. B. Wollaber, and S. R. Gomez, “Punyvis: A visual analytics approach for identifying homograph phishing attacks,” in
2019
Earlier work this paper cites.
A. Oest, Y. Safaei, A. Doupé, G.-J. Ahn, B. Wardman, and K. Tyers, “Phishfarm: A scalable framework for measuring the effectiveness of evasion techniques against browser phishing blacklists,” in
2019
Earlier work this paper cites.
Z. Yang, Z. Dai, Y. Yang, J. Carbonell, R. R. Salakhutdinov, and Q. V. Le, “Xlnet: Generalized autoregressive pretraining for language understanding,”
2019
Earlier work this paper cites.
“PhishTank,”
2020
Earlier work this paper cites.
A. Oest, P. Zhang, B. Wardman, E. Nunes, J. Burgis, A. Zand, K. Thomas, A. Doupé, and G.-J. Ahn, “Sunrise to sunset: Analyzing the end-to-end life cycle and effectiveness of phishing attacks at scale,” in
2020
Earlier work this paper cites.
R. Alabdan, “Phishing attacks survey: Types, vectors, and technical approaches,”
2020
Earlier work this paper cites.
D. Jampen, G. Gür, T. Sutter, and B. Tellenbach, “Don’t click: towards an effective anti-phishing training. a comparative literature review,”
2020
Earlier work this paper cites.
“Google Safebrowsing,”
2020
Earlier work this paper cites.
“VirusTotal,”
2020
Earlier work this paper cites.
2020
Earlier work this paper cites.
P. He, X. Liu, J. Gao, and W. Chen, “Deberta: Decoding-enhanced bert with disentangled attention,”
2020
Cited alongside, same era.
M. Southern. (2021) Chatgpt examples: 5 ways businesses are using openai’s language model. [Online]. Available:
2021
Cited alongside, same era.
OpenAI, “Openai usage policies,” 2021. [Online]. Available:
2021
Cited alongside, same era.
C. Hoffman, “It’s scary easy to use chatgpt to write phishing emails,”
2021
Cited alongside, same era.
E. Kovacs. (2021, September) Malicious prompt engineering with ChatGPT. SecurityWeek. [Online]. Available:
2021
Cited alongside, same era.
L. Cohen. (2021, June) Chatgpt hack allows chatbot to generate malware. [Online]. Available:
2023
Closest in time.
2023
Closest in time.
K. M. Caramancion, “Harnessing the power of chatgpt to decimate mis/disinformation: Using chatgpt for fake news detection,” in
2023
Closest in time.
G. Deiana, M. Dettori, A. Arghittu, A. Azara, G. Gabutti, and P. Castiglia, “Artificial intelligence and public health: Evaluating chatgpt responses to vaccination myths and misconceptions,”
2023
Closest in time.
Anthropic, “Claude-intro,” 2023. [Online]. Available:
2023
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2021
Cited alongside, same era.
Z. Alkhalil, C. Hewage, L. Nawaf, and I. Khan, “Phishing attacks: A recent comprehensive study and a new anatomy,”
2021
Cited alongside, same era.
P. Zhang, A. Oest, H. Cho, Z. Sun, R. Johnson, B. Wardman, S. Sarker, A. Kapravelos, T. Bao, R. Wang
2021
Cited alongside, same era.
H. Bijmans, T. Booij, A. Schwedersky, A. Nedgabat, and R. van Wegberg, “Catching phishers by their bait: Investigating the dutch phishing landscape through phishing kit detection,” in
2021
Cited alongside, same era.
S. Blog, “Dissecting a phishing campaign with a captcha-based url,”
2021
Cited alongside, same era.
A. Odeh, I. Keshta, and E. Abdelfattah, “Machine learningtechniquesfor detection of website phishing: A review for promises and challenges,” in
2021
Cited alongside, same era.
Auth0. (2021, June) Preventing clickjacking attacks. [Online]. Available:
2021
Cited alongside, same era.
Closest in time.
2023
Closest in time.
Google, “Bard-google-ai,” 2023. [Online]. Available:
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
H. Li, D. Guo, W. Fan, M. Xu, and Y. Song, “Multi-step jailbreaking privacy attacks on chatgpt,”
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
K. Greshake, S. Abdelnabi, S. Mishra, C. Endres, T. Holz, and M. Fritz, “Not what you’ve signed up for: Compromising real-world llm-integrated applications with indirect prompt injection,” 2023
2023
Closest in time.
2023
Closest in time.
M. Gupta, C. Akiri, K. Aryal, E. Parker, and L. Praharaj, “From chatgpt to threatgpt: Impact of generative ai in cybersecurity and privacy,”
2023
Closest in time.
E. Derner and K. Batistič, “Beyond the safeguards: Exploring the security risks of chatgpt,”
2023
Closest in time.
L. De Angelis, F. Baglivo, G. Arzilli, G. P. Privitera, P. Ferragina, A. E. Tozzi, and C. Rizzo, “Chatgpt and the rise of large language models: the new ai-driven infodemic threat in public health,”
2023
Closest in time.
D. O. Otieno, A. S. Namin, and K. S. Jones, “The application of the bert transformer model for phishing email classification,” in
2023
Closest in time.
D. He, X. Lv, S. Zhu, S. Chan, and K.-K. R. Choo, “A method for detecting phishing websites based on tiny-bert stacking,”
2023
Closest in time.
Y. Wang, W. Zhu, H. Xu, Z. Qin, K. Ren, and W. Ma, “A large-scale pretrained deep model for phishing url detection,” in
2023
Closest in time.
OpenAI, “Openai api,” 2023. [Online]. Available:
2023
Closest in time.
Palo Alto Networks Unit 42, “Captcha-protected phishing: What you need to know,”
2023
Closest in time.
G. Developers, “recaptcha v3: Add the recaptcha script to your html or php file,”
2023
Closest in time.
M. Morgan, “Qr code phishing scams target users and enterprise organizations,”
2023
Closest in time.
M. Kan, “Fbi: Hackers are compromising legit qr codes to send you to phishing sites,”
2023
Closest in time.
QRCode Monkey, “QR Server,”
2023
Closest in time.
S. Team, “iframe injection attacks and mitigation,”
2023
Closest in time.
PortSwigger, “Same-origin policy,”
2023
Closest in time.
mrd0x, “Browser in the Browser: Phishing Attack,”
2023
Closest in time.
Cofense, “Global polymorphic phishing attack 2022,”
2023
Closest in time.
Adobe, “Responsive web design,”
2023
Closest in time.
Bootstrap, “Bootstrap,”
2023
Closest in time.
Foundation, “Foundation,”
2023
Closest in time.
——, “Gpt-4 technical report,” 2023
2023
Closest in time.
OpenPhish, “Phishing activity tracked by openphish,” 2023. [Online]. Available:
2023
Closest in time.
X. Sun, L. Tu, J. Zhang, J. Cai, B. Li, and Y. Wang, “Assbert: Active and semi-supervised bert for smart contract vulnerability detection,”
2023
Closest in time.