5 research outputs found
An immunization scheme for ransomware
In recent years, as the popularity of anonymous currencies such as Bitcoin has made the tracking of ransomware attackers more difficult, the amount of ransomware attacks against personal computers and enterprise production servers is increasing rapidly. The ransomware has a wide range of influence and spreads all over the world. It is affecting many industries including internet, education, medical care, traditional industry, etc. This paper uses the idea of virus immunity to design an immunization solution for ransomware viruses to solve the problems of traditional ransomware defense methods (such as anti-virus software, firewalls, etc.), which cannot meet the requirements of rapid detection and immediate prevention of new outbreaks attacks. Our scheme includes two parts: server and client. The server provides an immune configuration file and configuration file management functions, including a configuration file module, a cryptography algorithm module, and a display module. The client obtains the immunization configuration file from server in real time, and performs the corresponding operations according to the configuration file to make the computer have an immune function for a specific ransomware, including an update module, a configuration file module, a cryptography algorithm module, a control module, and a log module. This scheme controls mutexes, services, files and registries respectively, to destroy the triggering conditions of the virus and finally achieve the purpose of immunizing a computer from a specific ransomware
A Comprehensive Bibliometric Analysis on Social Network Anonymization: Current Approaches and Future Directions
In recent decades, social network anonymization has become a crucial research
field due to its pivotal role in preserving users' privacy. However, the high
diversity of approaches introduced in relevant studies poses a challenge to
gaining a profound understanding of the field. In response to this, the current
study presents an exhaustive and well-structured bibliometric analysis of the
social network anonymization field. To begin our research, related studies from
the period of 2007-2022 were collected from the Scopus Database then
pre-processed. Following this, the VOSviewer was used to visualize the network
of authors' keywords. Subsequently, extensive statistical and network analyses
were performed to identify the most prominent keywords and trending topics.
Additionally, the application of co-word analysis through SciMAT and the
Alluvial diagram allowed us to explore the themes of social network
anonymization and scrutinize their evolution over time. These analyses
culminated in an innovative taxonomy of the existing approaches and
anticipation of potential trends in this domain. To the best of our knowledge,
this is the first bibliometric analysis in the social network anonymization
field, which offers a deeper understanding of the current state and an
insightful roadmap for future research in this domain.Comment: 73 pages, 28 figure
Privacy Intelligence: A Survey on Image Sharing on Online Social Networks
Image sharing on online social networks (OSNs) has become an indispensable
part of daily social activities, but it has also led to an increased risk of
privacy invasion. The recent image leaks from popular OSN services and the
abuse of personal photos using advanced algorithms (e.g. DeepFake) have
prompted the public to rethink individual privacy needs when sharing images on
OSNs. However, OSN image sharing itself is relatively complicated, and systems
currently in place to manage privacy in practice are labor-intensive yet fail
to provide personalized, accurate and flexible privacy protection. As a result,
an more intelligent environment for privacy-friendly OSN image sharing is in
demand. To fill the gap, we contribute a systematic survey of 'privacy
intelligence' solutions that target modern privacy issues related to OSN image
sharing. Specifically, we present a high-level analysis framework based on the
entire lifecycle of OSN image sharing to address the various privacy issues and
solutions facing this interdisciplinary field. The framework is divided into
three main stages: local management, online management and social experience.
At each stage, we identify typical sharing-related user behaviors, the privacy
issues generated by those behaviors, and review representative intelligent
solutions. The resulting analysis describes an intelligent privacy-enhancing
chain for closed-loop privacy management. We also discuss the challenges and
future directions existing at each stage, as well as in publicly available
datasets.Comment: 32 pages, 9 figures. Under revie
An iteration-based differentially private social network data release
© 2018 CRL Publishing Ltd. Online social networks provide an unprecedented opportunity for researchers to analysis various social phenomena. These network data is normally represented as graphs, which contain many sensitive individual information. Publish these graph data will violate users' privacy. Differential privacy is one of the most influential privacy models that provides a rigorous privacy guarantee for data release. However, existing works on graph data publishing cannot provide accurate results when releasing a large number of queries. In this paper, we propose a graph update method transferring the query release problem to an iteration process, in which a large set of queries are used as update criteria. Compared with existing works, the proposed method enhances the accuracy of query results. The extensive experiment proves that the proposed solution outperforms two state-of-the-art methods, the Laplace method and the correlated method, in terms of Mean Absolute Value. It means our methods can retain more utility of the queries while preserving the privacy