2 citations · 6 across the 19 of their papers we have counts for
7 papers · 1 filter
Proving DNSSEC Correctness: A Formal Approach to Secure Domain Name Resolution
Qifan Zhang, Zilin Shen, Imtiaz Karim +2
The Domain Name System Security Extensions (DNSSEC) are critical for preventing DNS spoofing, yet its specifications contain ambiguities and vulnerabilities that elude traditional…
Zero-Trust Strategies for O-RAN Cellular Networks: Principles, Challenges and Research Directions
Charalampos Katsis, Imtiaz Karim, Elisa Bertino
Cellular networks are foundational to modern communication, supporting a broad range of applications, from civilian use to enterprise systems and military tactical networks. The ad…
Future-Proofing Authentication Against Insecure Bootstrapping for 5G Networks: Feasibility, Resiliency, and Accountability
Saleh Darzi, Mirza Masfiqur Rahman, Imtiaz Karim +3
The 5G protocol lacks a robust base station (BS) authentication mechanism during the initial bootstrapping phase, leaving it susceptible to fake BSs, spoofed broadcasts, and large-…
VWAttacker: A Systematic Security Testing Framework for Voice over WiFi User Equipments
Imtiaz Karim, Hyunwoo Lee, Hassan Asghar +4
We present VWAttacker, the first systematic testing framework for analyzing the security of Voice over WiFi (VoWiFi) User Equipment (UE) implementations. VWAttacker includes a comp…
LLMalMorph: On The Feasibility of Generating Variant Malware using Large-Language-Models
Md Ajwad Akil, Adrian Shuai Li, Imtiaz Karim +4
Large Language Models (LLMs) have transformed software development and automated code generation. Motivated by these advancements, this paper explores the feasibility of LLMs in mo…
Standing Firm in 5G: A Single-Round, Dropout-Resilient Secure Aggregation for Federated Learning
Yiwei Zhang, Rouzbeh Behnia, Imtiaz Karim +2
Federated learning (FL) is well-suited to 5G networks, where many mobile devices generate sensitive edge data. Secure aggregation protocols enhance privacy in FL by ensuring that i…
How Feasible is Augmenting Fake Nodes with Learnable Features as a Counter-strategy against Link Stealing Attacks?
Mir Imtiaz Mostafiz, Imtiaz Karim, Elisa Bertino
Graph Neural Networks (GNNs) are widely used and deployed for graph-based prediction tasks. However, as good as GNNs are for learning graph data, they also come with the risk of pr…