Spam detection
31 papers with code • 1 benchmarks • 2 datasets
Most implemented papers
Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers
Although various techniques have been proposed to generate adversarial samples for white-box attacks on text, little attention has been paid to black-box attacks, which are more realistic scenarios.
Evading classifiers in discrete domains with provable optimality guarantees
We introduce a graphical framework that (1) generalizes existing attacks in discrete domains, (2) can accommodate complex cost functions beyond $p$-norms, including financial cost incurred when attacking a classifier, and (3) efficiently produces valid adversarial examples with guarantees of minimal adversarial cost.
Stronger Data Poisoning Attacks Break Data Sanitization Defenses
In this paper, we develop three attacks that can bypass a broad range of common data sanitization defenses, including anomaly detectors based on nearest neighbors, training loss, and singular-value decomposition.
GANs for Semi-Supervised Opinion Spam Detection
Online reviews have become a vital source of information in purchasing a service (product).
Cost-Aware Robust Tree Ensembles for Security Applications
There are various costs for attackers to manipulate the features of security classifiers.
Weight Poisoning Attacks on Pre-trained Models
We show that by applying a regularization method, which we call RIPPLe, and an initialization procedure, which we call Embedding Surgery, such attacks are possible even with limited knowledge of the dataset and fine-tuning procedure.
Deep convolutional forest: a dynamic deep ensemble approach for spam detection in text
The increase in people's use of mobile messaging services has led to the spread of social engineering attacks like phishing, considering that spam text is one of the main factors in the dissemination of phishing attacks to steal sensitive data such as credit cards and passwords.
An Automated Text Categorization Framework based on Hyperparameter Optimization
The compared datasets include several problems like topic and polarity classification, spam detection, user profiling and authorship attribution.
Natural Language Processing: State of The Art, Current Trends and Challenges
Natural language processing (NLP) has recently gained much attention for representing and analysing human language computationally.
EMFET: E-mail Features Extraction Tool
EMFET is an open source and flexible tool that can be used to extract a large number of features from any email corpus with emails saved in EML format.