[J1] Y. Nasser and M. Nassar, “Toward hardware-assisted malware detection utilizing
explainable machine learning: A survey,” IEEE Access, 2023.
[J2] S. A. H. Ibrahim and M. Nassar, “On the security of deep learning novelty detection,”
Expert Systems with Applications, vol. 207, p. 117964, 2022.
[J3] E. Chicha, B. A. Bouna, M. Nassar, R. Chbeir, R. A. Haraty, M. Oussalah, D. Benslimane,
and M. N. Alraja, “A user-centric mechanism for sequentially releasing graph datasets
under blowfish privacy,” ACM Transactions on Internet Technology (TOIT), vol. 21,
no. 1, pp. 1–25, 2021.
[C1] M. Mekni, S. Atilho, B. Greenfield, B. Placzek, and M. Nassar, “Real-time smart
parking integration in intelligent transportation systems (its),” in Proceedings of
the Future Technologies Conference, pp. 212–236, Springer, 2023.
[C2] C. Barone, M. Mekni, and M. Nassar, “Gargoyle guard: Enhancing cybersecurity
with artificial intelligence techniques,” in The Third Intelligent Cybersecurity Conference
(ICSC2023), https://www.icsc-conference.org/2023/index.php, 2023.
[C3] K. Samrouth, M. Nassar, and H. Harb, “Revisiting attack trees for modeling machine
pwning in training environments,” in The Third Intelligent Cybersecurity Conference
(ICSC2023), https://www.icsc-conference.org/2023/index.php, 2023.
[C4] C. S. Jayaramireddy, S. Naraharisetti, S. S. Veera Venkata, M. Nassar, and M.
Mekni, “A survey of reinforcement learning toolkits for gaming: Applications, challenges
and trends,” in Proceedings of the Future Technologies Conference, pp. 165–184, Springer,
Cham, 2023.
[C5] K. L. Pasala, C. S. Jayaramireddy, S. Naraharisetti, S. S. Veera Venkata, S.
Atilho, B. Greenfield, B. Placzek, M. Nassar, and M. Mekni, “Smart parking system
(sps): An intelligent imageprocessing based parking solution,” in Conference on Sustainable
Urban Mobility, pp. 291–299, Springer, 2022.
[C6] T. Edwards, S. McCullough, M. Nassar, and I. Baggili, “On exploring the subdomain
of artificial intelligence (ai) model forensics,” in EAI ICDF2C, https://icdf2c.eaiconferences.
org/2021/, 2021.
[C7] D. Al Bared and M. Nassar, “Segmentation fault: A cheap defense against adversarial
machine learning,” in 2021 3rd IEEE Middle East and North Africa COMMunications Conference
(MENACOMM), pp. 37–42, IEEE, 2021.
[C8] S. Hajj Ibrahim and M. Nassar, “Hack the box: Fooling deep learning abstraction-based
monitors,” in The 2nd Workshop on Artificial Intelligence for Anomalies and Novelties
(AI4AN 2021), co-located with IJCAI 2021, 2021.
[C9] M. Nassar, J. Khoury, A. Erradi, and E. Bou-Harb, “Game theoretical model for
cybersecurity risk assessment of industrial control systems,” in 2021 11th IFIP International
Conference on New Technologies, Mobility and Security (NTMS), pp. 1–7, IEEE, 2021.
[C10] N. M. Farroukh, M. Nassar, S. Elbassuoni, and H. Safa, “Keep it flat (kif):
Resource management in integrated cloud-fog networks,” in ICWMC 2021, The Seventeenth
International Conference on Wireless and Mobile Communications, no. ISBN: 978-1-61208-878-5,
IARIA, 2021.
[C11] M. Nassar, E. Chicha, B. A. Bouna, and R. Chbeir, “Vip blowfish privacy in communication
graphs,” in Proceedings of the 17th International Joint Conference on e-Business and
Telecommunications, fICETEg, vol. 2, pp. 459–467, Lieusaint, Paris, France, July 8-10,
2020, 2020.
[C12] J. Khoury and M. Nassar, “A hybrid game theory and reinforcement learning approach
for cyber-physical systems security,” in NOMS 2020-2020 IEEE/IFIP Network Operations
and Management Symposium, pp. 1–9, IEEE, 2020.
[C13] M. Nassar, A. Itani, M. Karout, M. El Baba, and O. A. S. Kaakaji, “Shoplifting
smart stores using adversarial machine learning,” in AICCSA, 2019.
[C14] N. Khan and M. Nassar, “A look into privacy-preserving blockchains,” in 2019
IEEE/ACS 16th International Conference on Computer Systems and Applications (AICCSA),
pp. 1–6, IEEE, 2019.
[C15] M. Nassar, H. Safa, A. A. Mutawa, A. Helal, and I. Gaba, “Chi squared feature
selection over apache spark,” in Proceedings of the 23rd International Database Applications
& Engineering Symposium, pp. 1–5, 2019.
[C16] M. A. Kadri, M. Nassar, and H. Safa, “Transfer learning for malware multi-classification,”
in Proceedings of the 23rd International Database Applications & Engineering Symposium,
p. 19, ACM, 2019.
[C17] M. Nassar, B. Rawda, and M. Mardini, “select: Secure election as a service,”
in Proceedings of the 23rd International Database Applications & Engineering Symposium,
2019.
[C18] H. Safa, M. Nassar, and W. A. R. Al Orabi, “Benchmarking convolutional and recurrent
neural networks for malware classification,” in 2019 15th International Wireless Communications
& Mobile Computing Conference (IWCMC), pp. 561–566, IEEE, 2019. Mohamad Nassar Page
6 of 12
[C19] M. Nassar, Q. Malluhi, and T. Khan, “A scheme for three-way secure and verifiable
e-voting,” in 15th ACS/IEEE International Conference on Computer Systems and Applications
(AICCSA 2018), 2018.
[C20] M. Nassar and H. Safa, “Throttling malware families in 2d,” in 12th International
Conference on Autonomous Infrastructure, Management and Security (IFIP AIMS 2018),
http://www.aims-conference.org/2018/program.html, 2018.
[C21] Y. Awad, M. Nassar, and H. Safa, “Modeling malware as a language,” in 2018 IEEE
International Conference on Communications (ICC), pp. 1–6, IEEE, 2018.
[C22] H. Bou-Ammar, M. Jaber, and M. Nassar, “Correctness-by-learning of infinite-state
component-based systems,” in International Conference on Formal Aspects of Component
Software, pp. 162–178, Springer, Cham, 2017.
[C23] M. Jaber, M. Nassar, W. A. R. Al Orabi, B. A. Farraj, M. O. Kayali, and C. Helwe,
“Reconfigurable and adaptive spark applications.,” in CLOSER - 7th International Conference
on Cloud Computing and Services Science, pp. 84–91, 2017.
[C24] M. Nassar, N. Wehbe, and B. Al Bouna, “K-nn classification under homomorphic
encryption: application on a labeled eigen faces dataset,” in 2016 IEEE Intl Conference
on Computational Science and Engineering (CSE) and IEEE Intl Conference on Embedded
and Ubiquitous Computing (EUC) and 15th Intl Symposium on Distributed Computing and
Applications for Business Engineering (DCABES), pp. 546–552, IEEE, 2016.
[C25] S. Barakat, B. A. Bouna, M. Nassar, and C. Guyeux, “On the evaluation of the
privacy breach in disassociated set-valued datasets,” in Proceedings of the 13th International
Joint Conference on e-Business and Telecommunications (ICETE 2016), SECRYPT, Lisbon,
Portugal,, vol. 4, 2016.
[C26] M. Nassar, A. Erradi, and Q. M. Malluhi, “Paillier’s encryption: Implementation
and cloud applications,” in 2015 International Conference on Applied Research in Computer
Science and Engineering (ICAR), pp. 1–5, IEEE, 2015.
[C27] M. Nassar, A. A.-R. Orabi, M. Doha, and B. Al Bouna, “An sql-like query tool
for data anonymization and outsourcing,” in 2015 International Conference on Cyber
Situational Awareness, Data Analytics and Assessment (CyberSA), pp. 1–3, IEEE, 2015.
[C28] M. Nassar, A. Erradi, and Q. M. Malluhi, “A domain specific language for secure
outsourcing of computation to the cloud,” in 2015 IEEE 19th International Enterprise
Distributed Object Computing Conference, pp. 134–141, IEEE, 2015.
[C29] F. Sabry, A. Erradi, M. Nassar, and Q. M. Malluhi, “Automatic generation of
optimized workflow for distributed computations on large-scale matrices,” in International
Conference on Service-Oriented Computing, pp. 79–92, Springer, 2014.
[C30] M. Nassar, A. Erradi, F. Sabry, and Q. M. Malluhi, “A model driven framework
for secure outsourcing of computation to the cloud,” in 2014 IEEE 7th International
Conference on Cloud Computing, pp. 968–969, IEEE, 2014.
[C31] M. Nassar, B. al Bouna, and Q. Malluhi, “Secure outsourcing of network flow
data analysis,” in 2013 IEEE International Congress on Big Data, pp. 431–432, IEEE,
2013.
[C32] S. Wang, M. Nassar, M. Atallah, and Q. Malluhi, “Secure and private outsourcing
of shapebased feature extraction,” in International conference on information and
communications security, pp. 90–99, Springer, Cham, 2013. Mohamad Nassar Page 7 of
12
[C33] M. Nassar, A. Erradi, and Q. M. Malluhi, “Practical and secure outsourcing of
matrix computations to the cloud,” in 2013 IEEE 33rd International Conference on Distributed
Computing Systems Workshops, pp. 70–75, IEEE, 2013.
[C34] M. Nassar, A. Erradi, F. Sabri, and Q. M. Malluhi, “Secure outsourcing of matrix
operations as a service,” in 2013 IEEE Sixth International Conference on Cloud Computing,
pp. 918–925, IEEE, 2013.
[C35] M. Wang, S. B. Handurukande, and M. Nassar, “Rpig: A scalable framework for
machine learning and advanced statistical functionalities,” in 4th IEEE International
Conference on Cloud Computing Technology and Science Proceedings, pp. 293–300, IEEE,
2012.
[C36] M. Nassar, S. Martin, G. Leduc, and O. Festor, “Using decision trees for generating
adaptive spit signatures,” in Proceedings of the 4th international conference on Security
of information and networks, pp. 13–20, ACM, 2011.
[C37] R. Do Carmo, M. Nassar, and O. Festor, “Artemisa: An open-source honeypot back-end
to support security in voip domains,” in 12th IFIP/IEEE International Symposium on
Integrated Network Management (IM 2011) and Workshops, pp. 361–368, IEEE, 2011.
[C38] M. Nassar, O. Dabbebi, R. Badonnel, and O. Festor, “Risk management in voip
infrastructures using support vector machines,” in 2010 International Conference on
Network and Service Management, pp. 48–55, IEEE, 2010.
[C39] M. Nassar, R. State, and O. Festor, “A framework for monitoring sip enterprise
networks,” in 2010 Fourth International Conference on Network and System Security,
pp. 1–8, IEEE, 2010.
[C40] M. Nassar, R. State, and O. Festor, “Labeled voip data-set for intrusion detection
evaluation,” Networked Services and Applications-Engineering, Control and Management,
pp. 97–106, 2010.
[C41] M. Nassar, R. State, and O. Festor, “Voip malware: Attack tool & attack scenarios,”
in 2009 IEEE International Conference on Communications, pp. 1–6, IEEE, 2009.
[C42] M. Nassar, R. State, and O. Festor, “Monitoring sip traffic using support vector
machines,” in Recent Advances in Intrusion Detection, pp. 311–330, Springer, 2008.
[C43] M. Nassar, S. Niccolini, R. State, and T. Ewald, “Holistic voip intrusion detection
and prevention system,” in Proceedings of the 1st international conference on Principles,
systems and applications of IP telecommunications, pp. 1–9, 2007.
[C44] M. Nassar, O. Festor, et al., “Ibgp confederation provisioning,” in IFIP International
Conference on Autonomous Infrastructure, Management and Security, pp. 25–34, Springer,
Berlin, Heidelberg, 2007.
[C45] M. Nassar, O. Festor, et al., “Voip honeypot architecture,” in Integrated Network
Management, 2007. IM’07. 10th IFIP/IEEE International Symposium on, pp. 109–118, IEEE,
2007.
[C46] M. Nassar, R. State, and O. Festor, “Intrusion detection mechanisms for voip
applications,” in Third annual VoIP security workshop (VSW’06), 2006.
[B1] Y. Rebahi, R. Ruppelt, M. Nassar, and O. Festor, “Scamstop: A platform for mitigating
fraud in voip environments,” in Network and Traffic Engineering in Emerging Distributed
Computing Applications, pp. 302–325, IGI Global, 2013.
[B2] M. Nassar, “A practical scheme for two-party private linear least squares,” arXiv
preprint arXiv:1901.09281, 2019.
