Author:
Vorakulpipat Chalee,Visoottiviseth Vasaka,Siwamogsatham Siwaruk
Subject
Law,General Computer Science
Reference27 articles.
1. The information security digital divide between information security managers and users;Albrechtsen;Computers & Security,2009
2. Almeida TA, Yamakami A. “Content-based spam filtering,” The 2010 International Joint Conference on Neural Networks (IJCNN), July 2010.
3. Androutsopoulos I, Koutsias J, Chandrinos K, Spyropoulos CD. “An experimental comparison of naive bayesian and keyword-based anti-spam filterng with personal email message,” The 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, New York, USA, 2000.
4. Boykin PO, Roychowdhury V. “Personal email networks: an effective anti-spam tool,” MIT spam conference, Cambridge, MA, USA, 2005.
5. Spam filtering using statistical data compression models;Bratko;Journal of Machine Learning Research,2006
Cited by
9 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Safeguarding Devices and Edge Computing: A Responsive Anti-Scam Approach;2023 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech);2023-11-14
2. An Intelligent Framework Based on Deep Learning for SMS and e-mail Spam Detection;Applied Computational Intelligence and Soft Computing;2023-09-20
3. A Novel Traceback Technology for E-mail Sender Verification : Type of submission: Regular Research Paper / Most relevant symposium: CSCI-ISCW;2021 International Conference on Computational Science and Computational Intelligence (CSCI);2021-12
4. A semantic-based classification approach for an enhanced spam detection;Computers & Security;2020-07
5. Deep learning to filter SMS Spam;Future Generation Computer Systems;2020-01