@inproceedings{seth2017multimodal,
  title={Multimodal spam classification using deep learning techniques},
  author={Seth, Shikhar and Biswas, Sagar},
  booktitle={2017 13th International Conference on Signal-Image Technology \& Internet-Based Systems (SITIS)},
  pages={346--349},
  year={2017},
  organization={IEEE}
}

@inproceedings{wu2017twitter,
  title={Twitter spam detection based on deep learning},
  author={Wu, Tingmin and Liu, Shigang and Zhang, Jun and Xiang, Yang},
  booktitle={Proceedings of the australasian computer science week multiconference},
  pages={1--8},
  year={2017}
}
@article{wu2018twitter,
  title={Twitter spam detection: Survey of new approaches and comparative study},
  author={Wu, Tingmin and Wen, Sheng and Xiang, Yang and Zhou, Wanlei},
  journal={Computers \& Security},
  volume={76},
  pages={265--284},
  year={2018},
  publisher={Elsevier}
}
@article{ranganayakulu2013detecting,
  title={Detecting malicious URLs in E-mail--An implementation},
  author={Ranganayakulu, Dhanalakshmi and Chellappan, C},
  journal={AASRI Procedia},
  volume={4},
  pages={125--131},
  year={2013},
  publisher={Elsevier}
}
@article{jain2018spam,
  title={Spam detection on social media using semantic convolutional neural network},
  author={Jain, Gauri and Sharma, Manisha and Agarwal, Basant},
  journal={International Journal of Knowledge Discovery in Bioinformatics (IJKDB)},
  volume={8},
  number={1},
  pages={12--26},
  year={2018},
  publisher={IGI Global}
}
@article{jain2019optimizing,
  title={Optimizing semantic LSTM for spam detection},
  author={Jain, Gauri and Sharma, Manisha and Agarwal, Basant},
  journal={International Journal of Information Technology},
  volume={11},
  number={2},
  pages={239--250},
  year={2019},
  publisher={Springer}
}
@article{madisetty2018neural,
  title={A neural network-based ensemble approach for spam detection in Twitter},
  author={Madisetty, Sreekanth and Desarkar, Maunendra Sankar},
  journal={IEEE Transactions on Computational Social Systems},
  volume={5},
  number={4},
  pages={973--984},
  year={2018},
  publisher={IEEE}
}
@incollection{sharaff2016comparative,
  title={Comparative study of classification algorithms for spam email detection},
  author={Sharaff, Aakanksha and Nagwani, Naresh Kumar and Dhadse, Abhishek},
  booktitle={Emerging research in computing, information, communication and applications},
  pages={237--244},
  year={2016},
  publisher={Springer}
}
@inproceedings{pennington2014glove,
  author = {Jeffrey Pennington and Richard Socher and Christopher D. Manning},
  booktitle = {Empirical Methods in Natural Language Processing (EMNLP)},
  title = {GloVe: Global Vectors for Word Representation},
  year = {2014},
  pages = {1532--1543},
  url = {http://www.aclweb.org/anthology/D14-1162},
}
@InProceedings{mrksic:2016:naacl,
  author    = {Nikola Mrk\v{s}i\'c and Diarmuid {\'O S\'eaghdha} and Blaise Thomson and Milica Ga\v{s}i\'c 
  			   and Lina Rojas-Barahona and Pei-Hao Su and David Vandyke and Tsung-Hsien Wen and Steve Young},
  title     = {Counter-fitting Word Vectors to Linguistic Constraints},
  booktitle = {Proceedings of HLT-NAACL},
  year      = {2016},
}


%Reports
@misc{ThreatLa54:online,
author = {Symantec},
title = {Threat Landscape Trends – Q1 2020 | Symantec Blogs},
source  ={ https://symantec-enterprise-blogs.security.com/blogs/threat-intelligence/threat-landscape-q1-2020},
month = {},
year = {2020},
lastaccessed = {07/13/2020}
}
%% Related works
%BERT-ATTACK
@article{li2020bert,
  title={Bert-attack: Adversarial attack against bert using bert},
  author={Li, Linyang and Ma, Ruotian and Guo, Qipeng and Xue, Xiangyang and Qiu, Xipeng},
  journal={arXiv preprint arXiv:2004.09984},
  year={2020}
}
%%DeepWordBug
@inproceedings{gao2018black,
  title={Black-box generation of adversarial text sequences to evade deep learning classifiers},
  author={Gao, Ji and Lanchantin, Jack and Soffa, Mary Lou and Qi, Yanjun},
  booktitle={2018 IEEE Security and Privacy Workshops (SPW)},
  pages={50--56},
  year={2018},
  organization={IEEE}
}
@inproceedings{ebrahimi-etal-2018-hotflip,
    title = "{H}ot{F}lip: White-Box Adversarial Examples for Text Classification",
    author = "Ebrahimi, Javid  and
      Rao, Anyi  and
      Lowd, Daniel  and
      Dou, Dejing",
    booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
    month = jul,
    year = "2018",
    address = "Melbourne, Australia",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/P18-2006",
    doi = "10.18653/v1/P18-2006",
    pages = "31--36",
    abstract = "We propose an efficient method to generate white-box adversarial examples to trick a character-level neural classifier. We find that only a few manipulations are needed to greatly decrease the accuracy. Our method relies on an atomic flip operation, which swaps one token for another, based on the gradients of the one-hot input vectors. Due to efficiency of our method, we can perform adversarial training which makes the model more robust to attacks at test time. With the use of a few semantics-preserving constraints, we demonstrate that HotFlip can be adapted to attack a word-level classifier as well.",
}
%% TextFooler
@article{jin2019bert,
  title={Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment},
  author={Jin, Di and Jin, Zhijing and Tianyi Zhou, Joey and Szolovits, Peter},
  journal={arXiv},
  pages={arXiv--1907},
  year={2019}
}
%%TEXTBUGGER
@article{li2018textbugger,
  title={Textbugger: Generating adversarial text against real-world applications},
  author={Li, Jinfeng and Ji, Shouling and Du, Tianyu and Li, Bo and Wang, Ting},
  journal={arXiv preprint arXiv:1812.05271},
  year={2018}
}
%%TEXTATTACK
@misc{morris2020textattack,
      title={TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP}, 
      author={John X. Morris and Eli Lifland and Jin Yong Yoo and Jake Grigsby and Di Jin and Yanjun Qi},
      year={2020},
      eprint={2005.05909},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
% Alzantot
@article{alzantot2018generating,
  title={Generating natural language adversarial examples},
  author={Alzantot, Moustafa and Sharma, Yash and Elgohary, Ahmed and Ho, Bo-Jhang and Srivastava, Mani and Chang, Kai-Wei},
  journal={arXiv preprint arXiv:1804.07998},
  year={2018}
}
%%IGA
@article{wang2019natural,
  title={Natural language adversarial attacks and defenses in word level},
  author={Wang, Xiaosen and Jin, Hao and He, Kun},
  journal={arXiv preprint arXiv:1909.06723},
  year={2019}
}
% DancIN
@article{wong2017dancin,
  title={Dancin seq2seq: Fooling text classifiers with adversarial text example generation},
  author={Wong, Catherine},
  journal={arXiv preprint arXiv:1712.05419},
  year={2017}
}
%Target Models
@inproceedings{lai2015recurrent,
  title={Recurrent convolutional neural networks for text classification},
  author={Lai, Siwei and Xu, Liheng and Liu, Kang and Zhao, Jun},
  booktitle={Twenty-ninth AAAI conference on artificial intelligence},
  year={2015}
}
@article{zhou2016text,
  title={Text classification improved by integrating bidirectional LSTM with two-dimensional max pooling},
  author={Zhou, Peng and Qi, Zhenyu and Zheng, Suncong and Xu, Jiaming and Bao, Hongyun and Xu, Bo},
  journal={arXiv preprint arXiv:1611.06639},
  year={2016}
}
@inproceedings{zhang2015character,
  title={Character-level convolutional networks for text classification},
  author={Zhang, Xiang and Zhao, Junbo and LeCun, Yann},
  booktitle={Advances in neural information processing systems},
  pages={649--657},
  year={2015}
}
@article{kim2014convolutional,
  title={Convolutional neural networks for sentence classification},
  author={Kim, Yoon},
  journal={arXiv preprint arXiv:1408.5882},
  year={2014}
}
@misc{dongjunL40,
author = {Dongjun Lee},
title = {dongjun-Lee/text-classification-models-tf: Tensorflow implementations of Text Classification Models.},
url={https://github.com/dongjun-Lee/text-classification-models-tf},
lastaccessed = {09/03/2020}
}
% Background Paper
@inproceedings{biggio2018wildpatterns,
author = {Biggio, Battista and Roli, Fabio},
title = {Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning},
year = {2018},
isbn = {9781450356930},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3243734.3264418},
doi = {10.1145/3243734.3264418},
booktitle = {Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security},
pages = {2154–2156},
numpages = {3},
keywords = {deep learning, adversarial machine learning, adversarial examples, training data poisoning, evasion attacks},
location = {Toronto, Canada},
series = {CCS ’18}
}
@book{sutton2018reinforcement,
  title={Reinforcement learning: An introduction},
  author={Sutton, Richard S and Barto, Andrew G},
  year={2018},
  publisher={MIT press}
}
@inproceedings{wang2018deep,
  title={Deep reinforcement learning for NLP},
  author={Wang, William Yang and Li, Jiwei and He, Xiaodong},
  booktitle={Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts},
  pages={19--21},
  year={2018}
}
@article{grondman2012survey,
  title={A survey of actor-critic reinforcement learning: Standard and natural policy gradients},
  author={Grondman, Ivo and Busoniu, Lucian and Lopes, Gabriel AD and Babuska, Robert},
  journal={IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)},
  volume={42},
  number={6},
  pages={1291--1307},
  year={2012},
  publisher={IEEE}
}
@article{sallab2017deep,
  title={Deep reinforcement learning framework for autonomous driving},
  author={Sallab, Ahmad EL and Abdou, Mohammed and Perot, Etienne and Yogamani, Senthil},
  journal={Electronic Imaging},
  volume={2017},
  number={19},
  pages={70--76},
  year={2017},
  publisher={Society for Imaging Science and Technology}
}
@article{zhang2020adversarial,
  title={Adversarial attacks on deep-learning models in natural language processing: A survey},
  author={Zhang, Wei Emma and Sheng, Quan Z and Alhazmi, Ahoud and Li, Chenliang},
  journal={ACM Transactions on Intelligent Systems and Technology (TIST)},
  volume={11},
  number={3},
  pages={1--41},
  year={2020},
  publisher={ACM New York, NY, USA}
}
%Hide no Seek
@inproceedings{fass2019hidenoseek,
  title={Hidenoseek: Camouflaging malicious javascript in benign asts},
  author={Fass, Aurore and Backes, Michael and Stock, Ben},
  booktitle={Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security},
  pages={1899--1913},
  year={2019}
}

%%%%%%%DATASETS%%%%%%%%%%%%%%%%%%%%%
%%SMS
@online{SMSSpam:online,
author = {Kaggle},
title = {SMS Spam Collection Dataset | Kaggle},
url = {https://www.kaggle.com/uciml/sms-spam-collection-dataset},
lastaccessed = {07/20/2020}
}

@misc{machinel97,
author = {StackOverflow},
title = {machine learning - a general measure of data-set imbalance - Cross Validated},
url = {https://stats.stackexchange.com/questions/239973/a-general-measure-of-data-set-imbalance},
lastaccessed = {08/31/2020}
}
@online{YelpData30:online,
author = {Yelp},
title = {Yelp Dataset},
url = {https://www.yelp.com/dataset/download},
lastaccessed = {08/18/2020}
}
@online{FakeNews89:online,
author = {Kaggle},
title = {Fake News, Kaggle},
url = {https://www.kaggle.com/c/fake-news/data},
year={2018},
lastaccessed = {08/18/2020}
}
@online{ToxicCom95:online,
author = {Kaggle},
title = {Toxic Comment Classification Challenge , Kaggle},
url= {https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge},
year={2018},
lastaccessed = {08/18/2020}
}
@online{Twitter-spam:online,
author = {Kaggle},
title = {UtkMl's Twitter Spam Detection Competition , Kaggle},
url={https://www.kaggle.com/c/twitter-spam},
year={2019},
lastaccessed = {Accessed on 07/20/2020}
}
@online{youtubedata,
author = {UCI Machine Learning},
title = {UCI Machine Learning Repository: YouTube Spam Collection Data Set},
url = {http://archive.ics.uci.edu/ml/datasets/YouTube+Spam+Collection#},
lastaccessed = {07/20/2020}
}
@online{SpamDatasets,
author = {ACL Wiki},
title = {Spam filtering datasets },
url = {https://aclweb.org/aclwiki/Spam_filtering_datasets},
lastaccessed = {(Accessed on 07/20/2020)}
}
@online{IWSPAAPd24:online,
author = {IWSPA-AP 2018},
title = {IWSPA-AP: First Security and Privacy Analytics Anti-Phishing Shared Task},
url ={https://github.com/BarathiGanesh-HB/IWSPA-AP/tree/master/data},
lastaccessed = {07/20/2020}
}
@online{TREC:online,
author = {uwaterloo},
title = {TREC 2005 Spam Public Corpora},
url = {https://plg.uwaterloo.ca/cgi-bin/cgiwrap/gvcormac/foo},
lastaccessed = {Accessed on 07/20/2020}
}
@misc{Linguist48:online,
author = {Spacy},
title = {Linguistic Features · spaCy Usage Documentation},
url= {https://spacy.io/usage/linguistic-features#aligning-tokenization},
lastaccessed = {(Accessed on 08/18/2020)}
}
@misc{symspell:online,
author = {Wolf Garbe},
title = {wolfgarbe/SymSpell: SymSpell: 1 million times faster through Symmetric Delete spelling correction algorithm},
url = {https://github.com/wolfgarbe/SymSpell},
month = {},
year = {},
lastaccessed = {08/18/2020}
}
@misc{language27:online,
author = {PYPI},
title = {language-tool-python · PyPI},
url = {https://pypi.org/project/language-tool-python/},
lastaccessed = {08/18/2020}
}
@misc{stable-baselines,
  author = {Hill, Ashley and Raffin, Antonin and Ernestus, Maximilian and Gleave, Adam and Kanervisto, Anssi and Traore, Rene and Dhariwal, Prafulla and Hesse, Christopher and Klimov, Oleg and Nichol, Alex and Plappert, Matthias and Radford, Alec and Schulman, John and Sidor, Szymon and Wu, Yuhuai},
  title = {Stable Baselines},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  url = {https://github.com/hill-a/stable-baselines},
}
@online{sklearnf17:online,
author = {sklearn},
title = {sklearn.feature\_extraction.text.CountVectorizer — scikit-learn 0.23.2 documentation},
url = {https://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html},
month = {},
year = {},
lastaccessed = {08/13/2020}
}
@article{goodfellow2014explaining,
  title={Explaining and harnessing adversarial examples},
  author={Goodfellow, Ian J and Shlens, Jonathon and Szegedy, Christian},
  journal={arXiv preprint arXiv:1412.6572},
  year={2014}
}
@misc{zhao2018generating,
      title={Generating Natural Adversarial Examples}, 
      author={Zhengli Zhao and Dheeru Dua and Sameer Singh},
      year={2018},
      eprint={1710.11342},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}
@article{cer2018universal,
      title={Universal Sentence Encoder}, 
      author={Daniel Cer and Yinfei Yang and Sheng-yi Kong and Nan Hua and Nicole Limtiaco and Rhomni St. John and Noah Constant and Mario Guajardo-Cespedes and Steve Yuan and Chris Tar and Yun-Hsuan Sung and Brian Strope and Ray Kurzweil},
      year={2018},
      eprint={1803.11175},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

@article{devlin2018bert,
  title={Bert: Pre-training of deep bidirectional transformers for language understanding},
  author={Devlin, Jacob and Chang, Ming-Wei and Lee, Kenton and Toutanova, Kristina},
  journal={arXiv preprint arXiv:1810.04805},
  year={2018}
}

@inproceedings{srivastava2020noisy,
  title={Noisy Text Data: Achilles’ Heel of BERT},
  author={Srivastava, Ankit and Makhija, Piyush and Gupta, Anuj},
  booktitle={Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020)},
  pages={16--21},
  year={2020}
}
@inproceedings{florian2003named,
  title={Named entity recognition through classifier combination},
  author={Florian, Radu and Ittycheriah, Abe and Jing, Hongyan and Zhang, Tong},
  booktitle={Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003},
  pages={168--171},
  year={2003}
}
@article{tang2020implementing,
  title={Implementing action mask in proximal policy optimization (PPO) algorithm},
  author={Tang, Cheng-Yen and Liu, Chien-Hung and Chen, Woei-Kae and You, Shingchern D},
  journal={ICT Express},
  year={2020},
  publisher={Elsevier}
}
@article{schulman2017proximal,
  title={Proximal policy optimization algorithms},
  author={Schulman, John and Wolski, Filip and Dhariwal, Prafulla and Radford, Alec and Klimov, Oleg},
  journal={arXiv preprint arXiv:1707.06347},
  year={2017}
}
@online{RFC3986U96:online,
lastaccessed = {(Accessed on 02/24/2020)},
author={Internet Engineering Task Force},
url = {https://tools.ietf.org/html/rfc3986},
title = {{RFC 3986 - Uniform Resource Identifier (URI): Generic Syntax}}
}