Johnny Still Receives Spam SMS: Assessing the Robustness of SMS Spam Detection

arXiv:2609.01171 · cs.CR · Submitted 2026-09-01 · Read on arXiv

cs.CR

Submitted: 2026-09-01

Updated: 2026-09-01

Code: https://github.com/researchsms203-hub/sms_attack_research

Terminology

• Robustness — 103× in this paper · explained in 5 episodes
• Accuracy — 62× in this paper · explained in 1 episode
• Adversarial Attacks — 36× in this paper · explained in 1 episode
• Adversarial Training — 30× in this paper · explained in 1 episode
• Adversarial Examples — 19× in this paper · explained in 2 episodes
• Generalization — 11× in this paper · explained in 13 episodes
• Tokenization — 7× in this paper · explained in 2 episodes
• Embeddings — 6× in this paper · explained in 2 episodes
• Ensemble Approach — 6× in this paper · explained in 3 episodes
• Transferability — 6× in this paper · explained in 4 episodes
• Adversarial Robustness — 5× in this paper · explained in 3 episodes
• Adam — 4× in this paper · explained in 2 episodes
• Concept Drift — 4× in this paper · explained in 4 episodes
• Hybrid Models — 4× in this paper · explained in 2 episodes
• Security and Privacy — 4× in this paper
• Transformer — 4× in this paper · explained in 2 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Ensemble Learning — 3× in this paper · explained in 2 episodes
• False Negative Rate — 3× in this paper
• False Positive Rate — 3× in this paper
• Frustration — 3× in this paper · explained in 2 episodes
• True Negative Rate — 3× in this paper
• Adversarial Training (AT) — 2× in this paper · explained in 1 episode
• Core — 2× in this paper · explained in 2 episodes
• F1 Score — 2× in this paper · explained in 3 episodes
• Transfer Learning — 2× in this paper · explained in 10 episodes
• True Positive Rate — 2× in this paper
• Adaptability — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Contextual Understanding — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• End Call Flow of Short Message Service — 1× in this paper
• Rich Communication Services — 1× in this paper
• Right-to-Left Override — 1× in this paper
• Short Message Service Center — 1× in this paper
• Verification — 1× in this paper · explained in 2 episodes

Sources

• SpamDam: Towards Privacy-Preserving and Adversary-Resistant SMS Spam Detection
• UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
• TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP
• Addressing machine learning concept drift reveals declining vaccine sentiment during the COVID-19 pandemic
• Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
• Spam Detection Using BERT
• MPNet: Masked and Permuted Pre-training for Language Understanding
• Universal Spam Detection using Transfer Learning of BERT Model
• On the Transferability of Adversarial Attacksagainst Neural Text Classifier

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