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A. Zafar

5 papers hereh-index 18944 citations76 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author3

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • cs.CR2
same name
  • A. Zafar — 248 papers, h 43
  • A. Zafar — 117 papers, h 20
  • A. Zafar — 3 papers, h 8
  • A. Zafar — 3 papers, h 12
  • A. Zafar — 1 paper, h 3
  • A. Zafar — 1 paper, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20212024
most citedUtilizing XAI technique to improve autoencoder based model for computer network anomaly detection with shapley additive explanation(SHAP)

82 citations · 112 across the 4 of their papers we have counts for

collaborators
Showing cs.LGShow all

3 papers · 1 filter

cs.LG2023

Untargeted White-box Adversarial Attack with Heuristic Defence Methods in Real-time Deep Learning based Network Intrusion Detection System

Khushnaseeb Roshan, Aasim Zafar, Sheikh Burhan Ul Haque

Network Intrusion Detection System (NIDS) is a key component in securing the computer network from various cyber security threats and network attacks. However, consider an unfortun…

cs.LG2023

Using Kernel SHAP XAI Method to optimize the Network Anomaly Detection Model

Khushnaseeb Roshan, Aasim Zafar

Anomaly detection and its explanation is important in many research areas such as intrusion detection, fraud detection, unknown attack detection in network traffic and logs. It is…

cs.LG2021★ 82 cited

Utilizing XAI technique to improve autoencoder based model for computer network anomaly detection with shapley additive explanation(SHAP)

Khushnaseeb Roshan, Aasim Zafar

Machine learning (ML) and Deep Learning (DL) methods are being adopted rapidly, especially in computer network security, such as fraud detection, network anomaly detection, intrusi…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.