Alaa Oqaily

dblp:248/7995 · DBLP profile ↗
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5ranked-venue papers
3as first author
2since 2021 · last 2025
0009-0008-0332-8059ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 3 · 2 first-author · 2 since 2021
YearPublicationVenuePosition
2025 Cross-Level Security Verification for Network Functions Virtualization (NFV)
abstract
Network Functions Virtualization (NFV) is a popular solution for providing multi-tenant network services on top of existing cloud infrastructures in an agile and cost-effective manner. However, as NFV employs multiple levels of virtualization, it also introduces novel security challenges, such as cloud-level security breaches that are invisible to NFV-level tenants. Towards verifying the security of NFV across all the levels (a.k.a. cross-level security verification), existing solutions are mostly insufficient, as each such solution typically only focuses on one specific level (e.g., cloud, SDN, or SFC), and verifying every level separately would be expensive or even infeasible. In this paper, we propose an efficient and practical system,NFVGuard+, for cross-level security verification for NFV. Particularly, the efficiency ofNFVGuard+is achieved by first performing the costly security verification at one level, and then extrapolating the verification result to other levels through conducting relatively lightweight consistency checks. Additionally, the practicality ofNFVGuard+is ensured by automating the essential steps (e.g., identifying security properties, collecting verification data, and conducting verification) based on a novel Entity-Relationship (ER) model of NFV stack, integrating the approach with OpenStack/Tacker (a popular choice for an NFV deployment), and finally evaluating its effectiveness using both synthetic and real data.
Alaa Oqaily, Mohammad Ekramul Kabir, Lingyu Wang 0001, Yosr Jarraya, Suryadipta Majumdar, Makan Pourzandi, Mourad Debbabi, Sudershan Lakshmanan Thirunavukkarasu, Mengyuan Zhang 0001
IEEE Trans. Dependable Secur. Comput.1
2022 MLFM: Machine Learning Meets Formal Method for Faster Identification of Security Breaches in Network Functions Virtualization (NFV)
Alaa Oqaily, Yosr Jarraya, Lingyu Wang 0001, Makan Pourzandi, Suryadipta Majumdar
ESORICS (3)1
2020 NFVGuard: Verifying the Security of Multilevel Network Functions Virtualization (NFV) Stack
abstract
Network Functions Virtualization (NFV) enables agile and cost-effective deployment of multi-tenant network services on top of a cloud infrastructure. However, the multi-tenant and multilevel nature of NFV may lead to novel security challenges, such as stealthy attacks exploiting potential inconsistencies between different levels of the NFV stacks. Consequently, the security compliance of a multilevel NFV stack cannot be sufficiently established using existing solutions, which typically focus on one level. Moreover, the naive approach of separately verifying every level could be expensive or even infeasible. In this paper, we propose, NFVGuard, the first multilevel approach to the formal security verification of NFV stacks. Our key idea is to conduct the security verification at only one level, and then assure that verification result for other levels by verifying the consistency between adjacent levels. We integrate NFVGuard with OpenStack/Tacker, a popular platform for the NFV deployment, and experimentally evaluate its effectiveness.
Alaa Oqaily, Sudershan Lakshmanan Thirunavukkarasu, Yosr Jarraya, Suryadipta Majumdar, Mengyuan Zhang 0001, Makan Pourzandi, Lingyu Wang 0001, Mourad Debbabi
CloudCom1
2019 Modeling NFV Deployment to Identify the Cross-Level Inconsistency Vulnerabilities
abstract
By providing network functions through software running on standard hardware, Network Functions Virtualization (NFV) brings many benefits, such as increased agility and flexibility with reduced costs, as well as additional security concerns. Although existing works have examined various security issues of NFV, such as vulnerabilities in VNF software and DoS, there has been little effort on a security issue that is intrinsic to NFV, i.e., as an NFV environment typically involves multiple abstraction levels, the inconsistency that may arise between different levels can potentially be exploited for security attacks. In this paper, we propose the first NFV deployment model to capture the deployment aspects of NFV at different abstraction levels, which is essential for an in-depth study of the inconsistencies between such levels. Based on the model and an implemented NFV testbed, we present concrete attack scenarios in which the inconsistencies are exploited to attack the network functions in a stealthy manner. Finally, we study the feasibility of detecting the inconsistencies through verification.
Sudershan Lakshmanan Thirunavukkarasu, Mengyuan Zhang 0001, Alaa Oqaily, Gagandeep Singh Chawla, Lingyu Wang 0001, Makan Pourzandi, Mourad Debbabi
CloudCom3
2019 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 0001, Mourad Debbabi
ESORICS (2)4