@article {ElHaddouti2022575,
	title = {A Secure and Trusted Fog Computing Approach based on Blockchain and Identity Federation for a Granular Access Control in IoT Environments},
	journal = {International Journal of Advanced Computer Science and Applications},
	volume = {13},
	number = {3},
	year = {2022},
	note = {cited By 0},
	pages = {575-584},
	abstract = {Fog computing is a new computing paradigm that is an extension of the standard cloud computing model, which can be adopted as a cost effective strategy for managing connected objects, by enabling real-time computing and communication for analytical and decision making. Nonetheless, even though Fog-based Internet of Things networks optimize the standard architecture by moving computing, storage, communication, and control decision closer to the edge network, the technology becomes open to malicious attackers and remains many business risks that are not yet resolved. In fact, access control, privacy as well as trust risks present major challenges in Internet of Things environments based on Fog computing due to the large scale distributed nature of devices at the Fog layer. In addition, the traditional authentication methods are not adequate in Fog-based Internet of Things contexts since they consume significantly more computation power and incur high latency. To deal with these gaps, we present in this paper a secure and trusted Fog Computing approach based on Blockchain and Identity Federation technologies for a granular access control in IoT environments. The proposed scheme uses Smart Contract concept and Attribute-Based Access Control model to ensure the level of security and scalability required for data integrity without resorting to a central authority to make an access decision {\textcopyright} 2022. International Journal of Advanced Computer Science and Applications.All Rights Reserved.},
	keywords = {Access control, Block-chain, Cloud-computing, Computing model, Computing paradigm, Cost effective strategies, Cost effectiveness, Decision making, Decisions makings, Digital storage, Fog, Fog computing, Identity federation, Internet of things, IOT, Real-time communication, Real-time computing, Smart contract, Trusted computing},
	doi = {10.14569/IJACSA.2022.0130368},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129902962\&doi=10.14569\%2fIJACSA.2022.0130368\&partnerID=40\&md5=65966293c50d57a061513c913c7b5bb3},
	author = {El Haddouti, S. and El Kettani, M.D.E.-C.}
}
@article {Lamrhari2022,
	title = {A social CRM analytic framework for improving customer retention, acquisition, and conversion},
	journal = {Technological Forecasting and Social Change},
	volume = {174},
	year = {2022},
	note = {cited By 4},
	abstract = {Social Customer Relationship Management (social CRM) has become one of the central points for many companies seeking to improve their customer experience. It comprises a set of processes that allows decision-makers to analyze customer data, in order to launch an efficient, customer-centric, and cost-effective marketing strategy. Nonetheless, the inclusion of social media data in CRM introduces new challenges, as it requires advanced analytical approaches to extract actionable insight from such a huge amount of data. Thus, in this paper, we propose a social CRM analytic framework, which includes various analytical approaches, aiming at improving customer retention, acquisition, and conversion. This framework has been tested on various datasets and extensively evaluated based on several performance metrics. The obtained results suggest that the proposed framework can effectively extract relevant information and support decision-making processes. From an academics perspective, the study contributes to an understanding of customers{\textquoteright} experiences throughout their engagement on social media and focuses on long-term relationships with customers. From a managerial perspective, companies should leverage the insight generated through every customer engagement on social media to drive effective marketing strategies. {\textcopyright} 2021},
	keywords = {Acquisition, Conversion, Cost effectiveness, Customer acquisition, Customer conversion, Customer relationship management, Customer retention, Customer satisfaction, Customers{\textquoteright} satisfaction, Decision making, Digital storage, Machine learning, management, marketing, Public relations, Sales, Sentiment analysis, Social CRM, social media, Social networking (online), Strategic planning},
	doi = {10.1016/j.techfore.2021.121275},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118116967\&doi=10.1016\%2fj.techfore.2021.121275\&partnerID=40\&md5=10ffdb7f551bf1e135c01fb362d1a559},
	author = {Lamrhari, S. and Ghazi, H.E. and Oubrich, M. and Faker, A.E.}
}
@conference {Mouchfiq2021,
	title = {Blockchain-based Model Against selfish Attacks in Mobile ad hoc Networks},
	booktitle = {Proceedings - 4th International Conference on Advanced Communication Technologies and Networking, CommNet 2021},
	year = {2021},
	note = {cited By 0},
	abstract = {Over the past several decades, the importance of security has been increasing, in particular in the area of research addressing the Internet of Things (IoT) and, implicitly, ad hoc networks since they are part of it. Researchers have adopted blockchain as an interesting and trendy research topic in the wireless ad hoc environment. Due to its strong characteristics, such as consensus, immutability, finality and provenance, it{\textquoteright}s used not only as a secure data storage for critical data, but also as a platform that facilitates trustless data exchange between independent parties. However, the main challenge of applying blockchain in an ad hoc network is what kind of nodes should be involved in the validation process and how to adopt the heavy computational complexity of block validation in an appropriate way while maintaining its authentic characteristics. In this paper, we propose a new blockchain-based model against selfish attacks in ad hoc networks and optimize it in this context, to this end, we investigate the presence of MPR nodes to adapt and integrate the blockchain principle in MANETs and based on this we conduct a security analysis to evaluate our model by discussing the ability of our model to meet major security issues related to confidentiality, integrity, availability, non-repudiation, and vulnerability to attacks. {\textcopyright} 2021 IEEE.},
	keywords = {Ad hoc environment, Ad-hoc networks, Block-chain, Blockchain, Digital storage, Electronic data interchange, Internet of things, Mobile ad hoc networks, Mobile ad-hoc networks, Mobile security, MPR, Network security, Research topics, Secure data storage, Security, Selfish attack, Wireless ad hoc},
	doi = {10.1109/CommNet52204.2021.9641959},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124026049\&doi=10.1109\%2fCommNet52204.2021.9641959\&partnerID=40\&md5=83605288b49be75af72d459c6e278bdd},
	author = {Mouchfiq, N. and Habbani, A. and Benjbara, C. and Berradi, H.}
}
@conference {Bouamama2021560,
	title = {Cloud key management using trusted execution environment},
	booktitle = {Proceedings of the 18th International Conference on Security and Cryptography, SECRYPT 2021},
	year = {2021},
	note = {cited By 0},
	pages = {560-567},
	abstract = {Cloud storage represents a primordial component in most information technology infrastructures. Using cloud instead of on-premise storage raises several security issues, especially when secret keys are stored on the cloud. In such a setting, a robust cloud key management system is a must. Using traditional key management systems (KMS) in the cloud suffers from performance and scalability limitations. This paper, proposes an efficient and secure cloud KMS based on Trusted Execution Environment, precisely Intel SGX. The suggested system (KMSGX), while being deployed on the cloud, is fully controlled by the end-user. Therefore, KMSGX allows running on-premise software key management securely on the cloud provider side, protecting the exchanged and stored data. The security properties of the suggested design have been formalized using the Applied Pi Calculus and proved with ProVerif. The experimental results have demonstrated the system{\textquoteright}s high performance in terms of the upload and download durations and the limited overhead compared to the plain design. Copyright {\textcopyright} 2021 by SCITEPRESS {\textendash} Science and Technology Publications, Lda. All rights reserved},
	keywords = {Applied pi calculus, Calculations, Cloud providers, Cryptography, Digital storage, Information technology infrastructure, Key management systems, Performance and scalabilities, Security issues, Security properties, Trusted computing, Trusted execution environments},
	doi = {10.5220/0010558905600567},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111807187\&doi=10.5220\%2f0010558905600567\&partnerID=40\&md5=2745b5f1ad6970111bb700c309eea488},
	author = {Bouamama, J. and Hedabou, M. and Erradi, M.}
}
@article {AitTemghart2021335,
	title = {Game Theoretic Approaches to Mitigate Cloud Security Risks: An Initial Insight},
	journal = {Lecture Notes in Business Information Processing},
	volume = {416 LNBIP},
	year = {2021},
	note = {cited By 1},
	pages = {335-347},
	abstract = {Cloud computing is one of the most promising innovations impacting data storage and processing. And with it, clients rely on the IT solutions offered by an external provider instead of on-premise applications. Despite its enormous impacts, customers are still reluctant to outsource their business processes because of security concerns. As data is typically stored and governed by cloud vendors, users need to deal with security issues linked to the loss of control over their sensitive data. Cloud providers need to implement the appropriate security measures that might attract more clients while making the minimum investment. While used in various disciplines, game theory has recently expanded to investigate the effect of the defenders{\textquoteright} and attackers{\textquoteright} behaviors on strategic decision-making. This study aims to develop insights into how game theory can develop better security policies in cloud computing. First, we perform threat modeling to identify the potential threats facing cloud. Second, we identify the limitations of existing game based solutions and then suggest an improved model define an adequate strategy that would figure out the right balance between the required security level and the profit margins. Besides, we present future directions that can be explored to build highly reliable and optimal strategies for cloud services. {\textcopyright} 2021, Springer Nature Switzerland AG.},
	keywords = {Business Process, Cloud computing, Cloud securities, Computation theory, Computer games, Data privacy, Decision making, Decision theory, Digital storage, Game theory, Information analysis, Optimal strategies, Potential threats, Security issues, Security measure, Security policy, Strategic decision making},
	doi = {10.1007/978-3-030-76508-8_24},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111082922\&doi=10.1007\%2f978-3-030-76508-8_24\&partnerID=40\&md5=1619b858093bfb251eb24a3209534772},
	author = {Ait Temghart, A. and Ait Omar, D. and Outanoute, M. and Marwan, M.}
}
@article {Meshram2021131336,
	title = {IBOOST: A Lightweight Provably Secure Identity-Based Online/Offline Signature Technique Based on FCM for Massive Devices in 5G Wireless Sensor Networks},
	journal = {IEEE Access},
	volume = {9},
	year = {2021},
	note = {cited By 7},
	pages = {131336-131347},
	abstract = {The fifth-generation (5G) wireless network is commercialized. The need to integrate massive devices in 5G and wireless sensor networks (WSN) to provide several convenient services for network users becomes imperative. However, there are growing concerns that 5G-WSNs pose new security threats to sensitive user information. User authentication and key agreement have been provided for secure end-to-end communication. However, stricter security techniques are required as billions of massive devices are being networked to collect and process complex user data in real-time. Therefore, anonymous authentication and authorization are highly coveted for privacy preservation and prevention of unlawful exploitation of user data. However, guaranteeing data integrity, authentication, and non-repudiation require special-purpose identity-based signature techniques that are quite difficult to design in practice. In order to address this problem, this paper proposes a lightweight, provably secure identity-based online/offline signature technique (IBOOST) and its extension for massive devices in 5G-WSNs using fractional chaotic maps. The IBOOST scheme achieves multi-time use of offline storage at a lower processing time. Therefore, the signer can reuse the offline pre-stored information in a polynomial time. This makes our IBOOST superior to the existing online/offline signature techniques that allow only a single signature. Additionally, the new technique enables the pre-registration process with a secret key, and no secret key is required in the offline stage. Also, the proposed IBOOST proves to be secure in the random oracle unforgeability under the chosen message attack (UF-IBS-CMA). Finally, the IBOOST and its enhanced version (A-IBOOST) give the lowest computational costs compared to several contending techniques. Therefore, the proposed IBOOST shows superior security and performance with better computational overhead than the preliminary techniques. {\textcopyright} 2013 IEEE.},
	keywords = {5G mobile communication systems, 5g wireless sensor network system, Authentication, Chaotic communications, Chaotic map, Chaotic systems, Communication system security, Cryptography, Digital storage, Fractional chaotic map, Identity-based signature scheme, Lyapunov methods, Network security, Offline signatures, Polynomial approximation, Provably secure, Secure communication, Security, Sensor network systems, Wireless sensor networks},
	doi = {10.1109/ACCESS.2021.3114287},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115720532\&doi=10.1109\%2fACCESS.2021.3114287\&partnerID=40\&md5=7998ce2d4092c9f49d84029f3c9d35cd},
	author = {Meshram, C. and Imoize, A.L. and Elhassouny, A. and Aljaedi, A. and Alharbi, A.R. and Jamal, S.S.}
}
@article {Majdoubi2021,
	title = {SmartMedChain: A Blockchain-Based Privacy-Preserving Smart Healthcare Framework},
	journal = {Journal of Healthcare Engineering},
	volume = {2021},
	year = {2021},
	note = {cited By 6},
	abstract = {Nowadays, the adoption of Internet of Things (IoT) technology worldwide is accelerating the digital transformation of healthcare industry. In this context, smart healthcare (s-healthcare) solutions are ensuring better and innovative opportunities for healthcare providers to improve patients{\textquoteright} care. However, these solutions raise also new challenges in terms of security and privacy due to the diversity of stakeholders, the centralized data management, and the resulting lack of trustworthiness, accountability, and control. In this paper, we propose an end-to-end Blockchain-based and privacy-preserving framework called SmartMedChain for data sharing in s-healthcare environment. The Blockchain is built on Hyperledger Fabric and stores encrypted health data by using the InterPlanetary File System (IPFS), a distributed data storage solution with high resiliency and scalability. Indeed, compared to other propositions and based on the concept of smart contracts, our solution combines both data access control and data usage auditing measures for both Medical IoT data and Electronic Health Records (EHRs) generated by s-healthcare services. In addition, s-healthcare stakeholders can be held accountable by introducing an innovative Privacy Agreement Management scheme that monitors the execution of the service in respect of patient preferences and in accordance with relevant privacy laws. Security analysis and experimental results show that the proposed SmartMedChain is feasible and efficient for s-healthcare environments. Copyright {\textcopyright} 2021 Driss El Majdoubi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.},
	keywords = {Access control, adult, Article, Block-chain, Blockchain, Centralised, controlled study, Data Management, Delivery of Health Care, Digital storage, Digital transformation, Distributed ledger, electronic health record, Electronic Health Records, Health care, health care delivery, Health care providers, Healthcare environments, Healthcare industry, human, Humans, Information management, information processing, information storage, Internet of things, Internet of things technologies, Network security, patient care, patient preference, Privacy, Privacy preserving, Privacy-preserving techniques, Security and privacy, Smart contract},
	doi = {10.1155/2021/4145512},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121960725\&doi=10.1155\%2f2021\%2f4145512\&partnerID=40\&md5=0f8afcea0c53e46d9f3863d4ed04b5b8},
	author = {Majdoubi, D.E. and Bakkali, H.E. and Sadki, S.}
}
@article {Yatribi2020226,
	title = {An Efficient and Secure Forward Error Correcting Scheme for DNA Data Storage},
	journal = {Advances in Intelligent Systems and Computing},
	volume = {942},
	year = {2020},
	note = {cited By 0},
	pages = {226-237},
	abstract = {In this paper, a new efficient error correcting scheme for DNA archival digital data storage is proposed. We devise a double protection scheme for DNA oligos, aiming to ensure the protection of both information and indexing header data from both symbol flipping and erasure-burst errors, using two different cyclic ternary difference-set codes, which are known to be completely orthogonalisable and very easy to decode using a simple majority-logic decoding algorithm. We show that the proposed scheme is efficient and easily scalable, and provides a coding potential of 1.97 bit per nucleotide, and a reasonable net information density of 0.75 bit/nt under the considered experimental conditions, with relatively a lower decoding complexity and costs compared to other DNA data storage approaches. {\textcopyright} 2020, Springer Nature Switzerland AG.},
	keywords = {Bioinformatics, Decoding, Decoding complexity, Difference sets, Digital storage, DNA, Error correcting scheme, Errors, Experimental conditions, Forward error correcting, Gene encoding, Information density, Majority logic, Pattern recognition, Protection schemes, Simple majority, Soft computing},
	doi = {10.1007/978-3-030-17065-3_23},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064931520\&doi=10.1007\%2f978-3-030-17065-3_23\&partnerID=40\&md5=215574899d2a75166c0a2fc343cb673e},
	author = {Yatribi, A. and Belkasmi, M. and Ayoub, F.}
}
@conference {Iraqi202024,
	title = {Immunizer: A Scalable Loosely-Coupled Self-Protecting Software Framework using Adaptive Microagents and Parallelized Microservices},
	booktitle = {Proceedings of the Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises, WETICE},
	volume = {2020-September},
	year = {2020},
	note = {cited By 2},
	pages = {24-27},
	abstract = {IT professionals are overwhelmed by rapidly-changing technology and growing complexity. Additional challenges are introduced by cyber-security. Self-protecting software tries to alleviate this situation by combining principles and techniques from both autonomic computing and software security. However, this combination creates scalability issues, as well as cross-cutting concerns. In this work, we present Immunizer: A Scalable Loosely-Coupled Self-Protecting Software Framework. Immunizer extends our Application-level Unsupervised Outlier-based Intrusion Detection and Prevention Framework by leveraging the architectural building blocks of autonomic computing, and adopting a microagent/microservice architectural model, augmented with distributed cluster computing, for maximum scalability and separation of concerns. More specifically, we design each of the Monitor, Analyze, Plan and Execute functions of the autonomic MAPE-K control loop as a parallelized microservice, while we model its Knowledge function as a data streaming, caching and storage infrastructure. Moreover, we design the Sensor and Effector touchpoint modules as adaptive lightweight runtime application instrumentation microagents. {\textcopyright} 2020 IEEE.},
	keywords = {Architectural buildings, Architectural modeling, Cluster computing, Computer programming, Control systems, Cross-cutting concerns, Digital storage, Distributed clusters, Immunization, Intrusion detection, Intrusion detection and prevention, Scalability, Separation of concerns, Software frameworks, Storage infrastructure},
	doi = {10.1109/WETICE49692.2020.00013},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100768767\&doi=10.1109\%2fWETICE49692.2020.00013\&partnerID=40\&md5=8dd6bb02a0433738b505ad00e964a1af},
	author = {Iraqi, O. and El Bakkali, H.}
}
@conference {Fellir2020377,
	title = {A multi-Agent based model for task scheduling in cloud-fog computing platform},
	booktitle = {2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020},
	year = {2020},
	note = {cited By 9},
	pages = {377-382},
	abstract = {The Internet-of-Things (IoT) is a network of physical objects that communicate and exchange data between them over the Internet. These objects, or things, generate a massive amount of data that require powerful analytics approaches and data storage platforms - this is where cloud computing may well come into play. The classic cloud computing paradigm, however, faces several serious issues, due to centralization, such as low performance, latency issues, security issues, bandwidth obstacle, etc.. The Fog (Edge) computing paradigm has been proposed to improve the performance and to address other weaknesses, by providing IoT data processing and storage capabilities locally at the edges (IoT devices), instead of sending all the data to the centralized cloud. Whether in cloud or in fog computing, with billions of devices and a huge number of simultaneous requests, managing limited resources becomes essential. One of the important steps in resource management is task scheduling. In this paper, we consider task scheduling in a cloud-fog computing platform, we propose a multi-agent based model that aims at serving the most important task first, taking into consideration the task priority, its wait time, its status and the resources required to complete it successfully. Furthermore, in the scheduling process, we first propose an update to the priority value of the task, while taking into consideration its dependencies to other tasks and their priorities. Simulation results show that our proposed model can lead to better resource utilization and improve performance. {\textcopyright} 2020 IEEE.},
	keywords = {Autonomous agents, Computational methods, Computing paradigm, Computing platform, Data handling, Digital storage, Fog, Fog computing, Improve performance, Internet of thing (IOT), Internet of things, Multi agent systems, Multi-agent based modeling, Multitasking, Resource Management, Resource utilizations, Scheduling, Scheduling algorithms, Simulation platform, Storage capability},
	doi = {10.1109/ICIoT48696.2020.9089625},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085496418\&doi=10.1109\%2fICIoT48696.2020.9089625\&partnerID=40\&md5=4ee0e2ab76422fc76603ec3b6f6942cb},
	author = {Fellir, F. and El Attar, A. and Nafil, K. and Chung, L.}
}
