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Honeypot security technique can also stop attacks in natural language processing


Honeypot security technique can also stop attacks in natural language processing
Borrowing a technique commonly used in cybersecurity to defend against these universal trigger-based attacks, researchers at the Penn State College of Information Sciences and Technology have developed a machine learning framework that can proactively defend against the same types of attacks in natural language processing applications 99% of the time.
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Honeypot security technique can also stop attacks in natural language processing
Jessica Hallman
July 28, 2021
UNIVERSITY PARK, Pa. As online fake news detectors and spam filters become more sophisticated, so do attackers’ methods to trick them including attacks through the “universal trigger.” In this learning-based method, an attacker uses a phrase or set of words to fool an indefinite number of inputs. A successful attack could mean more fake news appearing in your social media feed or spam reaching ....

Dongwon Lee , International Joint Conference On Natural Language Processing , Penn State College Of Information Sciences , Yonsei University , Meeting Of The Association For Computational Linguistics , National Science Foundation , Penn State College , Information Sciences , Noseong Park , Joint Conference , Annual Meeting , Computational Linguistics , International Joint Conference , Natural Language Processing , National Science , சர்வதேச கூட்டு மாநாடு ஆன் இயற்கை மொழி ப்ரோஸெஸிஂக் , பென் நிலை கல்லூரி ஆஃப் தகவல் அறிவியல் , சந்தித்தல் ஆஃப் தி சங்கம் க்கு கணக்கீட்டு மொழியியல் , தேசிய அறிவியல் அடித்தளம் , பென் நிலை கல்லூரி , தகவல் அறிவியல் , கூட்டு மாநாடு , ஆண்டு சந்தித்தல் , கணக்கீட்டு மொழியியல் , சர்வதேச கூட்டு மாநாடு , இயற்கை மொழி ப்ரோஸெஸிஂக் ,