@article {Iraqi2022, title = {Communizer: A collaborative cloud-based self-protecting software communities framework - Focus on the alert coordination system}, journal = {Computers and Security}, volume = {117}, year = {2022}, note = {cited By 0}, abstract = {Popular software has always been appealing to adversaries, as related vulnerabilities are synonymous with millions of exposed businesses. Collaborative intrusion detection, as well as software self-protection, try to alleviate this situation. However, they lack either autonomy and adaptation, or Internet-scale oversight and mitigation. In this work, we present Communizer: a collaborative cloud-based framework that creates communities of self-protecting software across organizations. It allows community members to turn their common weaknesses into collaborative and proactive self-protection, empowering them to detect intrusions, exchange alerts, and anticipate attacks. We start by integrating multiple autonomic MAPE-K loops through cloud-based coordination, and a novel hierarchical, regional coordination pattern (HRCP), optimizing scalability, resiliency, accuracy and privacy. Then, we design a trust-based multi-level alert coordination system (TMACS), as well as a lightweight alert coordination message exchange format (ACMEF). At its core, TMACS aggregates, validates, and shares security alerts among community members while fostering agreement and managing trust. It also addresses insider attacks by detecting and blacklisting rogue members. Moreover, TMACS identifies and neutralizes selfish members through a specifically designed probabilistic model. The analysis, optimization, and evaluation of TMACS show a good trade-off between the precision and recall of untrustworthy and selfish members detection. More importantly, we demonstrate a drastic reduction of monitoring loads on community members while ensuring a high collaborative attack detection and anticipation rate, even for small-scope attacks. {\textcopyright} 2022 Elsevier Ltd}, keywords = {Autonomic Computing, collaboration, Coordination systems, Economic and social effects, Intrusion detection, Mape, MAPE-K, Self protecting, Self-protecting software, Selfishness, Software community, Trust, Trusted computing}, doi = {10.1016/j.cose.2022.102692}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127747467\&doi=10.1016\%2fj.cose.2022.102692\&partnerID=40\&md5=246bfc07692396ec6709a73d31126fb6}, author = {Iraqi, O. and Bakkali, H.E.} } @conference {Mrabet2021, title = {Dependable Decentralized Reputation Management System for Vehicular Ad Hoc Networks}, booktitle = {Proceedings - 4th International Conference on Advanced Communication Technologies and Networking, CommNet 2021}, year = {2021}, note = {cited By 0}, abstract = {Reputation management systems are essential for establishing trust among network users. They are tools for reinforcing cooperation and sanctioning malicious behavior. Their importance becomes a requirement in highly mobile and volatile environments, such as vehicular ad-hoc networks (VANET). In the present work, we propose a dynamic and decentralized reputation system that fits VANET characteristics like dynamism and volatility without conceding on security. The novel system uses blockchain for reputation information aggregation and storage and secure multiparty computation (SMC) to achieve privacy. Unlike previous VANET reputation systems, our system does not rely on a central authority to evaluate trustworthiness. Instead, it limits its role to maintaining the blockchain and system integrity leaving reputation evaluation to peers. It preserves feedback privacy in the presence of up to n - 2 dishonest parties and shows good performance. Remarkably, our system takes advantage of the infrastructure of VANET when vehicles are nearby while remaining fully functional in extra-urban areas. {\textcopyright} 2021 IEEE.}, keywords = {Block-chain, Blockchain, Cryptography, Decentralised, Management systems, Network security, Privacy, reputation, Reputation management, Secure multi-party computation, Security, Trust, Vehicular ad hoc networks, Vehicular Adhoc Networks (VANETs)}, doi = {10.1109/CommNet52204.2021.9641962}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124029681\&doi=10.1109\%2fCommNet52204.2021.9641962\&partnerID=40\&md5=2f6bc5d0b3cdbf224ab74c6a02d48c13}, author = {Mrabet, K. and El Bouanani, F. and Ben-Azza, H.} } @article {10115338520131101, title = {A New Feedback-Analysis based Reputation Algorithm for E-Commerce Communities.}, journal = {E-Ti: E-Review in Technologies Information}, number = {7}, year = {2013}, pages = {46 - 58}, abstract = {Dealing with the ever-growing content generated by users in the e-commerce applications, Trust Reputation Systems (TRS) are widely used online to provide the trust reputation of each product using the customers{\textquoteright} ratings. However, there is also a good number of online customer reviews and feedback that must be used by the TRS. As a result, we propose in this work a new architecture for TRS in e-commerce application which includes feedback{\textquoteright} mining in order to calculate reputation scores. This architecture is based on an intelligent layer that proposes to each user (i.e. {\guillemotleft}feedback provider{\guillemotright}) who has already given his recommendation, a collection of prefabricated feedback to like or dislike. Then the proposed reputation algorithm calculates the trust degree of the user, the feedback{\textquoteright}s trustworthiness and generates the global reputation score of the product according to his {\guillemotleft}likes{\guillemotright} and {\guillemotleft}dislikes{\guillemotright}. In this work, we present also a state of the art of text mining tools and algorithms that can}, keywords = {Algorithms, analyse de sentiment, e-commerce, Electronic commerce, La confiance, le e-commerce, le textmining, les feedback textuels, les syst{\`e}mes de r{\'e}putation, Reliability (Personality trait), Sentiment analysis, text mining, Text mining (Information retrieval), textual feedback, Trust, Trust Reputation Systems, Virtual communities}, issn = {11148802}, url = {http://search.ebscohost.com/login.aspx?direct=true\&db=iih\&AN=101153385\&site=ehost-live}, author = {Rahimi, Hasnae and El Bakkali, Hanan} }