110 Publications (Page 2 of 5)
2023
Log-related Coding Patterns to Conduct Postmortems of Attacks in Supervised Learning-based Projects. ACM Transactions on Privacy and Security
. | Journal Article
Practitioner Perceptions of Ansible Test SmellsZhang, Y.⋅Wu, F. and Rahman, A.(pp. 325-327)
Quality Assurance for Infrastructure Orchestrators: Emerging Results from AnsibleZhang, Y.⋅Rahman, M.⋅Wu, F. and Rahman, A.(pp. 322-324)
Security Misconfigurations in Open Source Kubernetes Manifests: An Empirical Study. ACM Transactions on Software Engineering and Methodology
. | Journal Article
Software Supply Chain Vulnerabilities Detection in Source Code: Performance Comparison between Traditional and Quantum Machine Learning AlgorithmsAkter, M.S.⋅Faruk, Md.J.H.⋅Anjum, N.⋅Masum, M.⋅Shahriar, H.⋅Rahman, A.⋅Wu, F. and Cuzzocrea, A.
Survey - Ansible Test Smell
Teaching DevOps Security Education with Hands-on Labware: Automated Detection of Security Weakness in PythonAkter, M.S.⋅Rodriguez-Cardenas, J.⋅Rahman, M.M.⋅Shahriar, H. and Wu, F.
2022
A Novel Machine Learning Based Framework for Bridge Condition AnalysisMasum, M.⋅Anjum, N.⋅Hossain Faruk, M.J.⋅Shahriar, H.⋅Sakib, N.⋅Valero, M.⋅Karim, M.A.⋅Rahman, A.⋅Wu, F. and Cuzzocrea, A.(pp. 5530-5535)
As Code Testing: Characterizing Test Quality in Open Source Ansible DevelopmentHassan, M.M. and Rahman, A.(pp. 208-219)
Benefits, Challenges, and Research Topics: A Multi-vocal Literature Review of KubernetesShamim, S.I.⋅Gibson, J.A.⋅Morrison, P. and Rahman, A.
Bie Vote: A Biometric Identification Enabled Blockchain-Based Secure and Transparent Voting FrameworkFaruk, M.J.H.⋅Islam, M.⋅Alam, F.⋅Shahriar, H. and Rahman, A.(pp. 253-258)
Can We use Authentic Learning to Educate Students about Secure Infrastructure as Code Development?Rahman, A.⋅Shamim, S.I.⋅Shahriar, H. and Wu, F.(pp. 631)
Detecting and Characterizing Propagation of Security Weaknesses in Puppet-based Infrastructure ManagementRahman, A. and Parnin, C.
Development of Blockchain-based e-Voting System: Requirements, Design and Security PerspectiveFaruk, M.J.H.⋅Saha, B.⋅Islam, M.⋅Alam, F.⋅Shahriar, H.⋅Valero, M.⋅Rahman, A.⋅Wu, F. and Alam, Z.(pp. 959-967)
Empirical Study of Security Misconfigurations in Kubernetes Manifests
Evolution of Quantum Computing: A Systematic Survey on the Use of Quantum Computing ToolsUpama, P.B.⋅Faruk, M.J.H.⋅Nazim, M.⋅Masum, M.⋅Shahriar, H.⋅Uddin, G.⋅Barzanjeh, S.⋅Ahamed, S.I. and Rahman, A.(pp. 520-529)
Evolution of Quantum Computing: A Systematic Survey on the Use of Quantum Computing ToolsUpama, P.B.⋅Faruk, J.H.⋅Nazim, M.⋅Masum, M.⋅Shahriar, H.⋅Uddin, G.⋅Barzanjeh, S.⋅Ahamed, S.I. and Rahman, A.
Investigating Novel Approaches to Defend Software Supply Chain AttacksHossain Faruk, M.J.⋅Tasnim, M.⋅Shahriar, H.⋅Valero, M.⋅Rahman, A. and Wu, F.(pp. 283-288)
Lessons from Research to Practice on Writing Better Quality Puppet ScriptsRahman, A. and Sharma, T.(pp. 63-67)
Malware Detection and Prevention using Artificial Intelligence TechniquesFaruk, M.J.H.⋅Shahriar, H.⋅Valero, M.⋅Barsha, F.L.⋅Sobhan, S.⋅Khan, M.A.⋅Whitman, M.⋅Cuzzocrea, A.⋅Lo, D.⋅Rahman, A. and Wu, F.
Quantum Machine Learning for Software Supply Chain Attacks: How Far Can We Go?Masum, M.⋅Nazim, M.⋅Jobair Hossain Faruk, Md.⋅Shahriar, H.⋅Valero, M.⋅Abdullah Hafiz Khan, Md.⋅Uddin, G.⋅Barzanjeh, S.⋅Saglamyurek, E.⋅Rahman, A. and Ahamed, S.I.
Quantum Machine Learning for Software Supply Chain Attacks: How Far Can We Go?Masum, M.⋅Nazim, M.⋅Faruk, M.J.H.⋅Shahriar, H.⋅Valero, M.⋅Khan, M.A.H.⋅Uddin, G.⋅Barzanjeh, S.⋅Saglamyurek, E.⋅Rahman, A. and Ahamed, S.I.(pp. 530-538)
Shifting Left for Machine Learning: An Empirical Study of Security Weaknesses in Supervised Learning-based ProjectsBhuiyan, F.A.⋅Prowell, S.⋅Shahriar, H.⋅Wu, F. and Rahman, A.(pp. 798-808)
Software Supply Chain Vulnerabilities Detection in Source Code: Performance Comparison between Traditional and Quantum Machine Learning AlgorithmsAkter, M.S.⋅Faruk, M.J.H.⋅Anjum, N.⋅Masum, M.⋅Shahriar, H.⋅Sakib, N.⋅Rahman, A.⋅Wu, F. and Cuzzocrea, A.(pp. 5639-5645)
