Azadeh Tabiban

Publications

• Measuring and Improving the Security Posture of IEC 61850 Substations against Supply Chain Attacks
  Onur Duman, Azadeh Tabiban, Lingyu Wang and Mourad Debbabi
  IEEE Transactions on Instrumentation and Measurement, Accepted, 2024

• Signaling Storm in O-RAN: Challenges and Research Opportunities
  Azadeh Tabiban, Hyame Assem Alameddine, Mohammad A. Salahuddin and Raouf Boutaba
  IEEE Communication Magazine (ComMag) (impact factor 11.2), 2023 PDF

  O-RAN enables agile network architecture through programmable disaggregated units. However, the complexity and disaggregation of O-RAN may increase the risk of security incidents. Signaling storm is one of such incidents that disrupts network services through excessive control signals. This article conducts the first survey on signaling storm in O-RAN. Specifically, we discuss different threat models and existing signaling storm solutions and their applicability to O-RAN with respect to its properties, and perform a preliminary experiment on the impact of signaling storm on disaggregated RAN. We also provide insights and future reserach directions on leveraging key benefits of O-RAN to address signaling storms.

  

• ProvTalk: Towards Interpretable Multi-level Provenance Analysis in Networking Functions Virtualization (NFV)
  Azadeh Tabiban, Heyang Zhao, Yosr Jarraya, Makan Pourzandi, Mengyuan Zhang and Lingyu Wang
  Proc. the Network and Distributed System Security Symposium (NDSS 2022) (Acceptance ratio 16.2%) PDF Slides Talk

  • Featured in Ericsson Blog

  How can we effectively analyze the events across different levels of NFV (e.g., events affecting a virtual IDS or its underlying virtual machine) while reducing our reliance on human expertise? In a nutshell, ProvTalk increases the interpretability of provenance graphs by leveraging the already existing dependencies between different visualizations of the same components (e.g., underlying VMs visualized as a virtual IDS at the top) to assign high-level semantics to low-level events. Next, it discards irrelevant events and aggregates nodes with the same semantics to decrease the size of analyses.

  

• VinciDecoder: Automatically Interpreting Provenance Graphs into Textual Forensic Reports with Application to OpenStack
  Azadeh Tabiban, Heyang Zhao, Yosr Jarraya, Makan Pourzandi and Lingyu Wang
  Proc. the 27th Nordic Conference on Secure IT Systems (NordSec 2022) (Acceptance ratio 20/89≈22.47%) PDF Slides
  • US Provisional Patent Application

  VinciDecoder leverages a novel combination of provenance analysis, natural language translation, and machine-learning techniques to automatically generate forensic reports. By reducing the reliance on human analysts to interpret and document provenance graphs, we avoid the limitations, human error, and delay that are natural to such manual efforts, and allow for more timely incident-response.

  
  
  

• Catching Falling Dominoes: Cloud Management-Level Provenance Analysis with Application to OpenStack
  Azadeh Tabiban, Yosr Jarraya, Mengyuan Zhang, Makan Pourzandi, Lingyu Wang and Mourad Debbabi
  Proc. the 8th IEEE Conference on Communications and Network Security (CNS 2020) PDF Slides
  Selected as a best paper candidate

• PERMON: An OpenStack Middleware for Runtime Security Policy Enforcement in Clouds
  Azadeh Tabiban, Suryadipta Majumdar, Lingyu Wang and Mourad Debbabi
  Proc. the 4th IEEE Workshop on Security and Privacy in the Cloud (SPC 2018) PDF Demo

• Proactivizer: Transforming Existing Verification Tools into Efficient Solutions for Runtime Security Enforcement
  Suryadipta Majumdar, Azadeh Tabiban, Meisam Mohammady, Alaa Oqaily, Yosr Jarraya, Makan Pourzandi, Lingyu Wang and Mourad Debbabi
  Proc. the 24th European Symposium on Research in Computer Security (ESORICS 2019) PDF

• Learning Probabilistic Dependencies among Events for Proactive Security Auditing in Clouds
  Suryadipta Majumdar, Azadeh Tabiban, Yosr Jarraya, Momen Oqaily, Amir Alimohammadifar, Makan Pourzandi, Lingyu Wang and Mourad Debbabi
  Journal of Computer Security (JCS), Vol. 27, No. 2, March 2019, pages 165-202 PDF
  

• Multi-Level Proactive Security Auditing for Cloud
  Suryadipta Majumdar, Azadeh Tabiban, Meisam Mohammady, Alaa Oqaily, Yosr Jarraya, Makan Pourzandi, Lingyu Wang and Mourad Debbabi
  Proc. the IEEE Conference on Dependable and Secure Computing (DSC 2019), Hangzhou, China, November 18-20, 2019

• Cloud Security Auditing (Book)
  Suryadipta Majumdar, Taous Madi, Yushun Wang, Azadeh Tabiban, Momen Oqaily, Amir Alimohammadifar, Yosr Jarraya, Makan Pourzandi, Lingyu Wang and Mourad Debbabi
  Springer, 2019, ISBN 978-3-030-23127-9
  

• Under Review
• DominoBlocker: Preventing Recurring Security Incidents in Clouds via Management-level Provenance Analysis
  Azadeh Tabiban, Mohammad Ekramul Kabir, Makan Pourzandi, Yosr Jarraya, Mengyuan Zhang, Lingyu Wang and Mourad Debbabi
  Submitted to the IEEE Transactions on Dependable and Secure Computing (TDSC)