Reconceptualizing the Public Spaces of New Urban Areas in Hanoi: The End or the New of Public-Making?

Public spaces are designed and managed in many different ways. In Hanoi, after the Doi moi policy in 1986, the transfer of the public spaces creation at the neighborhood-level to the private sector has prospered nature of public and added a large amount of public space for the city, directly impacting on citizen's daily life, creating a new trend, new concept of public spaces. This article looks forward to understanding the public spaces-making and operating in KDTMs (Khu Do Thi Moi - new urban areas) in Hanoi to answer the question of whether ‘socialization’/privatization of these public spaces will put an end to the urban public or the new means of public-making trend. Based on the comparison and literature review of studies in the world on public spaces privatization with domestic studies to see the differences in the Vietnamese context leading to differences in definitions and roles and the concept of public spaces in KDTMs of Hanoi. Through adducing and analyzing practical cases, the article also mentions the trends, the issues, the ways and the technologies of public-making and public-spaces-making in KDTMs of Hanoi. Win/loss and the relationship of the three most important influential actors in this process (municipality, KDTM owners, inhabitants/citizens) is also considered to reconceptualize the public spaces of KDTMs in Hanoi

Evolution of Commercial Facilities in New Urban Areas of Hanoi: Potential of Sustainable Neighborhood-level Third Place Making

Shopping contributes largely to how people feel part of and enjoy KDTMs (Khu Do Thi Moi - new urban areas) - the carefully planned new sites, well provided with infrastructure, and very attractive of Hanoi in the market economy. Among the three facilities that are rated as most important by KDTM’s residents - education, health care, and shopping, the third is considered a pure civil space. This space clearly reflects the changes of politico-economic context and decision-making actors. Participation of the private sector in the newly formed market economy after a long period under State-run subvention and the consumerism entailed various ways to develop neighborhood-level commercial facilities. This paper aims to analyze and discuss on: firstly, the neighborhood-level commercial facilities have ‘promptly’ updated the changes in Vietnam's political-economic; secondly, the classify of KDTMs has resulted in a corresponding differentiation of commercial facilities according to the will of the project owners and the target consumer-resident; finally, facing the global ‘death’ of shopping malls, the KDTMs malls are trying to find themselves a new ‘vitality’: they are being ‘publicized’ to (re)create the third places in KDTM, that encourage social interaction in the limited spaces - intersperse public and private practices

Fed-LSAE: Thwarting Poisoning Attacks against Federated Cyber Threat Detection System via Autoencoder-based Latent Space Inspection

The significant rise of security concerns in conventional centralized learning has promoted federated learning (FL) adoption in building intelligent applications without privacy breaches. In cybersecurity, the sensitive data along with the contextual information and high-quality labeling in each enterprise organization play an essential role in constructing high-performance machine learning (ML) models for detecting cyber threats. Nonetheless, the risks coming from poisoning internal adversaries against FL systems have raised discussions about designing robust anti-poisoning frameworks. Whereas defensive mechanisms in the past were based on outlier detection, recent approaches tend to be more concerned with latent space representation. In this paper, we investigate a novel robust aggregation method for FL, namely Fed-LSAE, which takes advantage of latent space representation via the penultimate layer and Autoencoder to exclude malicious clients from the training process. The experimental results on the CIC-ToN-IoT and N-BaIoT datasets confirm the feasibility of our defensive mechanism against cutting-edge poisoning attacks for developing a robust FL-based threat detector in the context of IoT. More specifically, the FL evaluation witnesses an upward trend of approximately 98% across all metrics when integrating with our Fed-LSAE defense