M. Miraz, M. Ali, P. S. Excell, and R. Picking, "A review of internet of things (iot), internet of everything (ioe) and internet of nano things (iont), " in Internet Technologies and Application, pp. 219-224, IEEE, 2015.
F. Hussain, "Internet of everything, " in Internet of Things, pp. 1-11, Springer, 2017.
R. Montasari and H. Richard, "Next generation digital forensics; challenges and future paradigms, " in International Conference on Global Security, Safety and Sustainability, pp. 205-212, IEEE, 2019.
S. Garfinkel, "Digital forensic research: The next 10 years, " Digital Investigation, vol. 7, pp. 64-73, 2010.
L. Caviglione, S. Wendzel, and W. Mazurczyk, "The future of digital forensics: Challenges and the road ahead, " IEEE Security&Privacy, vol. 15, no. 6, pp. 12-16, 2017.
B. Carrier and E. Spafford, "An event-based digital forensic investigation framework, " in Digital Forensic Research Workshop (DFRWS USA), DFRWS, 2004.
G. Hong, J. Bo, and Q. Wei, "Analysis of email header for forensics purpose, " in International Conference on Communication Systems and Network Technologies (CSNT), 2013.
D. Miyamoto, H. Hazeyama, and Y. Kadobayashi, "Detecting methods of virus email based on mail header and encoding anomaly, " in Advances in Neuro-Information Processing (ICONIP), 2008.
K. Morovati and S. S. Kadam, "Detection of phishing emails with email forensic analysis and machine learning techniques, " International Journal of Cyber-Security and Digital Forensics (IJCSDF), vol. 8, no. 2, pp. 98-107, 2019.
I. Santos, C. Laorden, X. Ugarte-Pedrero, B. Sanz, and P. G. Bringas, "Spam filtering through anomaly detection, " in Communications in Computer and InformationInternational Conference on E-Business and Telecommunication, vol. 314, pp. 203-216, Springer, 2012.
J. Aparna and S. Dija, "Detection of spoofed mails, " in IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), IEEE, 2015.
S. Sanjeev, M. Manoj, and V. Gaurav, "Identification of spoofed emails by applying email forensics and memory forensics, " in 10th International Conference on Communication and Network Security, pp. 109-114, ACM Digital Library, 2020.
K. Muhammad, C. Chatwin, and R. Young, "A framework for post-event timeline reconstruction using neural networks, " Digital Investigation, vol. 4, no. 3-4, pp. 146-157, 2007.
M. Khan, "Performance analysis of Bayesian networks and neural networks in classification of file system activities, " Digital Investigation, vol. 4, no. 3-4, pp. 146-157, 2012.
E. D. Liddy, "Natural language processing, " Encyclopedia of Library and Information Science, vol. 2, 2001.
G. Chowdhury, "Natural language processing, " Annual Review of Information Science and Technology, vol. 37, pp. 51-89, 2003.
H. Studiawan, F. Sohel, and C. Payne, "Sentiment analysis in a forensic timeline, " IEEE Access, vol. 8, pp. 60664-60675, 2020.
T. N. Kipf and M. Welling, "Variational graph auto-encoder, " in Neural Information Processing Systems (NeurIPS), 2016, arXiv preprint arXiv: 1312. 6114, 2016.
S.-C. Wang, "Artificial neural network, " Interdisciplinary Computing in Java Programming, pp. 81-100, 2003.
A. D. Dongare, A. A. Kharde, and A. D. Karchi, "Introduction to artificial neural network, " International Journal of Engineering and Innovative Technology (IJEIT), vol. 2, no. 1, pp. 189-194, 2012.
S. Youngjoo, D. Michaël, V. Pierre, and B. Xavier, "Structured sequence modeling with graph convolutional recurrent networks, " in International Conference on Neural Information Processing, pp. 362-373, Springer, Cham, 2018.
A. M. Noora, B. Joanne, N. F. Virginia, and M. Andrew, "Forensic investigation of cyberstalking cases using behavioural evidence analysis, " in Proceedings of the Third Annual DFRWS Europe (DFRWS), vol. 16, pp. S96-S103, Elsevier, 2016.
H. Rachid, D. Mourad, L. Hakim, I. Farkhund, S. Adam, and B. Djamel, "Towards an integrated e-mail forensic analysis framework, " Digital Investigation, vol. 5, no. 3-4, pp. 124-137, 2009.
P. Wu, F. Yan, and H. Guo, "Holmes: An efficient and lightweight semantic based anomalous email detector, " International Journal of Network Security and its Application, 2011.
J. Jennifer, "Computer forensics: Intellectual property investigations and the ccfe, " Digital Forensics, 2018.
T. M. Banday, "Techniques and tools for forensic investigation of emails, " International Journal of Network Security and its Application, vol. 3, no. 6, p. 227, 2011.
Mrityunjay, U. Chauhan, and S. Gupta, "Novel approach for email forensics, " International Journal of Engineering Research & Technology (IJERT), vol. 5, no. 10, pp. 1-6, 2017.
M. Uma and B. Nikkath, "Machine learning forensics to gauge the likelihood of fraud in emails, " in International Conference on Communication and Electronics Systems (ICCES-2021), pp. 1567-1572, IEEE, 2021.
W. H. DuBay, "The principles of readability, " Online Submission, 2004.
A. Emad, E. A. Alaa, M. Bsoul, A. D. Essam, and A. F. Otoom, "Simplified features for email authorship identification, " International Journal of Security and Networks, vol. 8, no. 2, pp. 72-81, 2019.
P. S. Bogawar and K. K. Bhoyar, "A novel approach for the identification of writing traits on email database, " in 2016 1st India International Conference on Information Processing (IICIP), pp. 1-6, 2016.
I. Farkhund, H. Rachid, C. F. Benjamin, and D. Mourad, "A novel approach of mining write-prints for authorship attribution in e-mail forensics, " Digital Investigation, vol. 5, pp. 42-51, 2008.
E. Loper and S. Bird, "Nltk: The natural language toolkit, " in In Proceedings of the ACL Workshop on Effective Tools and Methodologies for Teaching Natural Language Processing and Computational Linguistics, arXiv preprint cs/0205028 (2002), 2002.
S. T. Dumais, "Latent semantic indexing (lsi) and trec-2, " Nist Special Publication, vol. Sp, pp. 105-105, 1994.
T. Hoffman, "Probabilistic latent semantic indexing, " in 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 50-57, ACM Digital Library, 1999.
D. M. Blei, N. Y. Andrew, and M. I. Jordan, "Latent dirichlet allocation, " Journal of Machine Learning Research, vol. 3, pp. 993-1022, 2003.
X. Wei, L. Xin, and G. Yihong, "Document clustering based on nonnegative matrix factorization, " in 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, vol. 51, ACM Digital Library, 2003.
D. Kingma and M. Welling, "Auto-encoding variational bayes, " in International Conference on Learning Representations (ICLR), 2013.
S. Weidman, Deep Learning from Scratch. O'Reilly, 2019.
R. Hurbans, Grokking Artificial Intelligence Algorithms. Manning, 2020.
T. N. Kipf and M. Welling, "Semi-supervised classification with graph convolution networks, " in ICLR 2017, arXiv preprint arXiv: 1609. 02907, 2017.
C. Zhengdao, "Graph convolutional networks for graphs with multidimensionally weighted edges, " arXiv preprint arXiv: 1808. 06099, 2020.
T. Mikolov, K. Martin, B. Lukas, C. Jan, and K. Sanjeev, "Recurrent neural network based language model, " Interspeech, vol. 2, no. 3, pp. 1045-1048, 2010.
c. e. A. Kyunghyun, "Learning phrase representations using rnn encoderdecoder for statistical machine translation, " in 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1724-1734, arXiv preprint arXiv: 1406. 1078, 2010.
E. Hajiramezanali, A. Hasanzadeh, K. Narayanan, N. Duffield, M. Zhou, and X. Qian, "Variational graph recurrent neural networks, " Advances in neural information processing systems, vol. 32, pp. 1049-5258, 2019.
C. Junyoung, K. Kyle, D. Laurent, G. Kratarth, C. Aaron, and B. Yoshua, "A recurrent latent variable model for sequential data, " Advances in neural information processing systems, vol. 28, pp. 2980-2988, 2015.
S. Pranav and R. R. Nihar, "Comparison between lda & nmf for event detection from large text stream data, " in 3rd International Conference on Computational Intelligence and Communication Technology (IEEECICT 2017), pp. 1-5, IEEE, 2017.
R. Albalawi, T. H. Yeap, and M. Benyoucef, "Using topic modeling methods for short-text data: A comparative analysis, " Frontier in Artificial Intelligence, vol. 3, no. 42, 2020.
Y. Chen, H. Zhang, R. Liu, Z. Ye, and L. Jianying, "Experimental explorations on short text topic mining between lda and nmf based schemes, " Knowledge-Based Systems, vol. 163, pp. 1-13, 2019.
M. Röder, A. Both, and A. Hinneburg, "Exploring the space of topic coherence measures, " in Proceedings of the Eighth ACM International Conference on Web Search and Data Mining, pp. 399-408, ACM Digital Library, 2015.
D. Kingma and J. Ba, "Adam: A method for stochastic optimization, " in International Conference for Learning Representations (ICLR), arXiv preprint arXiv: 1412. 6980, 2014.
A. P. Bradley, "The use of the area under the roc curve in the evaluation of machine learning algorithms, " Pattern Recognition, vol. 30, pp. 1145-1159, 1997.
E. Zhang and Y. Zhang, "Average precision, " Encyclopedia of Database Systems, 2009.
C. Tianfeng and R. R. Draxler, "Root mean square error (rmse) or mean absolute error (mae), " Geoscientific Model Development Discussions, vol. 7, pp. 1525-1534, 2014.