Detection of Phishing Attacks
| Title | Detection of Phishing Attacks |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Baykara, Muhammet, Gürel, Zahit Ziya |
| Conference Name | 2018 6th International Symposium on Digital Forensic and Security (ISDFS) |
| Date Published | mar |
| Publisher | IEEE |
| ISBN Number | 978-1-5386-3449-3 |
| Keywords | Anti Phishing Simulator, attachments, attacker, Bayes methods, Bayesian algorithm, Classification algorithms, communication mediums, Computer crime, cyber attack, detection problem, digital simulation, e-mail, e-mails harm victims, Electronic mail, Filtering, Human Behavior, human factor, identity theft, Information security, Intrusion detection, Intrusion Detection Systems, login credentials, mail contents, malicious links, money loss, official person, phishing, phishing attacks, phishing emails, Postal services, pubcrawl, spam mails, spam words, Uniform resource locators, unsolicited e-mail |
| Abstract | Phishing is a form of cybercrime where an attacker imitates a real person / institution by promoting them as an official person or entity through e-mail or other communication mediums. In this type of cyber attack, the attacker sends malicious links or attachments through phishing e-mails that can perform various functions, including capturing the login credentials or account information of the victim. These e-mails harm victims because of money loss and identity theft. In this study, a software called "Anti Phishing Simulator'' was developed, giving information about the detection problem of phishing and how to detect phishing emails. With this software, phishing and spam mails are detected by examining mail contents. Classification of spam words added to the database by Bayesian algorithm is provided. |
| URL | https://ieeexplore.ieee.org/document/8355389 |
| DOI | 10.1109/ISDFS.2018.8355389 |
| Citation Key | baykara_detection_2018 |
- Phishing
- information security
- Intrusion Detection
- Intrusion Detection Systems
- login credentials
- mail contents
- malicious links
- money loss
- official person
- identity theft
- phishing attacks
- phishing emails
- Postal services
- pubcrawl
- spam mails
- spam words
- Uniform resource locators
- unsolicited e-mail
- detection problem
- attachments
- attacker
- Bayes methods
- Bayesian algorithm
- Classification algorithms
- communication mediums
- Computer crime
- cyber attack
- Anti Phishing Simulator
- digital simulation
- e-mails harm victims
- Electronic mail
- Filtering
- Human behavior
- human factor