Chinese entrepreneurship in context: specialization, localization and their impact on Italian industrial districts

Chinese migration flows represent a relatively new phenomenon in Italy. Its entrepreneurial nature is reflected in massive flows Chinese businessman employed both in manufacturing and commercial activities, with a dense concentration in correspondence of some industrial districts. The aim of the paper is to shed some light on current Chinese specialization of economic activities and localization across Italian regions and industrial districts, to test interpretative research hypothesis on Chinese entrepreneurship models and identify agglomeration forces underlying the emergence of so-called Chinese ethnic businesses. Some reflections on the manufacturing and commercial attitude of Chinese entrepreneurship will also be considered. The utilization of native-Chinese entrepreneurs as unit of observation represents an innovative methodological contribution based on ASIA-ISTAT archives. The exercise of explorative analysis based on data processing and spatial analysis will finally highlight business migration patterns, which represent new socio-economic challenges for Italian industrial districts

Some Results on Colored Network Contraction

Networks are pervasive in computer science and in real world applications. It is often useful to leverage distinctive node features to regroup such data in clusters, by making use of a single representative node per cluster. Such contracted graphs can help identify features of the original networks that were not visible before. As an example, we can identify contiguous nodes having the same discrete property in a social network. Contracting a graph allows a more scalable analysis of the interactions and structure of the network nodes. This paper delves into the problem of contracting possibly large colored networks into smaller and more easily manageable representatives. It also describes a simple but effective algorithm to perform this task. Extended performance plots are given for a range of graphs and results are detailed and discussed with the aim of providing useful use cases and application scenarios for the approach

Polarization of a quasi two-dimensional repulsive Fermi gas with Rashba spin-orbit coupling: a variational study

Motivated by the remarkable experimental control of synthetic gauge fields in ultracold atomic systems, we investigate the effect of an artificial Rashba spin-orbit coupling on the spin polarization of a two-dimensional repulsive Fermi gas. By using a variational many-body wavefunction, based on a suitable spinorial structure, we find that the polarization properties of the system are indeed controlled by the interplay between spin-orbit coupling and repulsive interaction. In particular, two main effects are found: 1) The Rashba coupling determines a gradual increase of the degree of polarization beyond the critical repulsive interaction strength, at variance with conventional 2D Stoner instability. 2) The critical interaction strength, above which finite polarization is developed, shows a dependence on the Rashba coupling, i.e. it is enhanced in case the Rashba coupling exceeds a critical value. A simple analytic expression for the critical interaction strength is further derived in the context of our variational formulation, which allows for a straightforward and insightful analysis of the present problem.Comment: 7 pages, 3 figure

On SRv6 Security

SRv6 is a routing architecture that can provide hybrid cooperation between a centralized network controller and network nodes: IPv6 routers maintain the multi-hop ECMP-aware segments, whereas the controller, responsible for the Traffic Engineering policy, combines them to form a source-routed path through the network. Since the state of the flow is defined at the ingress to the network and then is contained in a specific packet header, called Segment Routing Header (SRH), the importance of such a header itself is vital. Motivated by the increasing success and widespread deployment of such approaches and technologies, this paper introduces the context and discusses some of the issues tied to possible tampering with the Segment Routing Header content. Finally, some details of an experimental testbed aimed at evaluating the above issues are provided

Onion under Microscope: An in-depth analysis of the Tor network

Tor is an anonymity network that allows offering and accessing various kinds of resources, known as hidden services, while guaranteeing sender and receiver anonymity. The Tor web is the set of web resources that exist on the Tor network, and Tor websites are part of the so-called dark web. Recent research works have evaluated Tor security, evolution over time, and thematic organization. Nevertheless, few information are available about the structure of the graph defined by the network of Tor websites. The limited number of Tor entry points that can be used to crawl the network renders the study of this graph far from being simple. In this paper we aim at better characterizing the Tor Web by analyzing three crawling datasets collected over a five-month time frame. On the one hand, we extensively study the global properties of the Tor Web, considering two different graph representations and verifying the impact of Tor's renowned volatility. We present an in depth investigation of the key features of the Tor Web graph showing what makes it different from the surface Web graph. On the other hand, we assess the relationship between contents and structural features. We analyse the local properties of the Tor Web to better characterize the role different services play in the network and to understand to which extent topological features are related to the contents of a service

ALTERDROID: eifferential fault analysis of obfuscated smartphone malware

Malware for smartphones has rocketed over the last years. Market operators face the challenge of keeping their stores free from malicious apps, a task that has become increasingly complex as malware developers are progressively using advanced techniques to defeat malware detection tools. One such technique commonly observed in recent malware samples consists of hiding and obfuscating modules containing malicious functionality in places that static analysis tools overlook (e.g., within data objects). In this paper, we describe ALTERDROID, a dynamic analysis approach for detecting such hidden or obfuscated malware components distributed as parts of an app package. The key idea in ALTERDROID consists of analyzing the behavioral differences between the original app and a number of automatically generated versions of it, where a number of modifications (faults) have been carefully injected. Observable differences in terms of activities that appear or vanish in the modified app are recorded, and the resulting differential signature is analyzed through a pattern-matching process driven by rules that relate different types of hidden functionalities with patterns found in the signature. A thorough justification and a description of the proposed model are provided. The extensive experimental results obtained by testing ALTERDROID over relevant apps and malware samples support the quality and viability of our proposal.This work was partially supported by the MINECO grant TIN2013-46469-R (SPINY: Security and Privacy in the Internet of You) and the CAM Grant S2013/ICE-3095 (CIBERDINE: Cybersecurity, Big Data, and Risks)

A technical characterization of APTs by leveraging public resources

Advanced persistent threats (APTs) have rocketed over the last years. Unfortunately, their technical characterization is incomplete—it is still unclear if they are advanced usages of regular malware or a different form of malware. This is key to develop an effective cyberdefense. To address this issue, in this paper we analyze the techniques and tactics at stake for both regular and APT-linked malware. To enable reproducibility, our approach leverages only publicly available datasets and analysis tools. Our study involves 11,651 regular malware and 4686 APT-linked ones. Results show that both sets are not only statistically different, but can be automatically classified with F1 > 0.8 in most cases. Indeed, 8 tactics reach F1 > 0.9. Beyond the differences in techniques and tactics, our analysis shows thats actors behind APTs exhibit higher technical competence than those from non-APT malwares.This work has been partially supported by grant DEPROFAKE-CM-UC3M funded by UC3M and the Government of Madrid (CAM); by CAM through Project CYNAMON, Grant No. P2018/TCS-4566-CM, co-funded with ERDF; by Ministry of Science and Innovation of Spain by grant PID2019-111429RB-C21; by TRUSTaWARE Project EU HORIZON 2020 Research and Innovation Programme GA No 101021377 trustaware.eu; and by TAILOR Project EU HORIZON 2020 Research and Innovation Programme GA No 952215 tailor-network.eu. Funding for APC: Universidad Carlos III de Madrid (Read & Publish Agreement CRUE-CSIC 2023)