Phishing based model
Webb14 aug. 2024 · The contributions of this research are as follows: . We conducted a systematic study of the effectiveness of deep learning algorithm architectures for phishing website detection. More specifically, our effort is targeted toward closing the gap of understanding the efficacy of deep learning-based models and hyperparameter … Webb9 apr. 2024 · Malicious actors often reuse code to deploy their malware, phishing website or CNC server. As a result, similiaries can be found on URLs path by inspecting internet traffic. Moreover, deep learning models or even regular ML model do not fit for inline deployment in terms of running performance. However, regexes ( or YARA rules ) can be …
Phishing based model
Did you know?
Webb18 maj 2024 · This paper proposed CCBLA, a lightweight phishing detection model based on a combination of CNN, BiLSTM, and attention mechanism. CCBLA first divides the URL strings into five parts of equal length. Then, the CNN and BiLSTM frameworks … WebbAmong that, phishing attack is the most common one. Phishing is an act carried by an individual or a group to access personal information such as credit card details, passwords etc for financial gain and other fraudulent activities. Thus, a new method is proposed named as "An Antipishing framework based on visual cryptography" to solve phishing ...
Webb13 apr. 2024 · An enhanced model for phishing URL detection based on Natural Language Processing and Deep Learning#utm3MT #pgssutm. Webb14 juli 2024 · This study analyzed two public datasets for phishing URLs detection in order to evaluate the performance of the proposed hybrid rule-based model. These datasets are available on the UCI repository. The first dataset, hereafter referred to as …
Webb6 okt. 2024 · In this paper, we proposed a LSTM based phishing detection method for big email data. The new method includes two important stages, sample expansion stage and testing stage under sufficient samples. WebbThe MPSPM model is mainly used for phishing susceptibility prediction and mainly considers 5 categories of decision factors that affect the susceptibility related to phishing sites, including demographics, personality, cognitive processes, knowledge and …
Webb13 apr. 2024 · Phishing, a social engineering crime which has been existing for more than two decades, has gained significant research attention to find better solutions to face against the very dynamic strategies of phishing. The financial sector is the primary target of phishing, and there are many different approaches to combat phishing attacks.
Webb15 sep. 2024 · Phishing is the easiest way to use cybercrime with the aim of enticing people to give accurate information such as account IDs, bank details, and passwords. This type of cyberattack is usually... dave and busters orange clip artWebbThe goal of an email service provider company is to send out a large number of emails to help its clients realise successful email marketing activities. Thousands of emails sent every minute need to be analysed in real time to reduce spam or phishing. The paper describes a method that uses real-time tracking of key campaign metrics such as the … black and decker electric teapotWebbWhile antiphishing techniques have evolved over the years, phishing remains one of the most threatening attacks on current network security. This is because phishing exploits one of the weakest links in a network system—people. The purpose of this research is to predict the possible phishing victims. In this study, we propose the multidimensional … dave and busters orange countyWebb14 juni 2024 · For phishing-based attacks, ML models can be trained to identify patterns and language in emails, SMS, malicious links, and even calls using natural language processing (NLP) [58,71]. However, the continuous evolution of phishing characteristics can be a concern for ML-based methods. dave and busters orlando florida couponsWebb25 juli 2024 · The experimental results show that the BLSTM-based phishing detection model is prominent in ensuring the network security by generating a recognition rate of 95.47% compared to the conventional RF-based model that generates a recognition rate … dave and busters oregonWebbbe used to develop deep learning-based phishing detection models. • Scenario-based Techniques: Different scenarios are used to detect the attacks. • Hybrid Techniques: A combination of different approaches is used to create a better model in terms of accuracy and precision. From the machine learning perspective, the phishing dave and busters orange outletsWebb31 mars 2024 · Advanced persistent threat attackers are using targeted emails, phishing websites and social engineering techniques to reach their goals. Deceptive Phishing targets confidential information using social engineering thefts online identity and uses … dave and busters origin