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2022 ◽  
Vol 25 (1) ◽  
pp. 1-26
Author(s):  
Fabio Pagani ◽  
Davide Balzarotti

Despite a considerable number of approaches that have been proposed to protect computer systems, cyber-criminal activities are on the rise and forensic analysis of compromised machines and seized devices is becoming essential in computer security. This article focuses on memory forensics, a branch of digital forensics that extract artifacts from the volatile memory. In particular, this article looks at a key ingredient required by memory forensics frameworks: a precise model of the OS kernel under analysis, also known as profile . By using the information stored in the profile, memory forensics tools are able to bridge the semantic gap and interpret raw bytes to extract evidences from a memory dump. A big problem with profile-based solutions is that custom profiles must be created for each and every system under analysis. This is especially problematic for Linux systems, because profiles are not generic : they are strictly tied to a specific kernel version and to the configuration used to build the kernel. Failing to create a valid profile means that an analyst cannot unleash the true power of memory forensics and is limited to primitive carving strategies. For this reason, in this article we present a novel approach that combines source code and binary analysis techniques to automatically generate a profile from a memory dump, without relying on any non-public information. Our experiments show that this is a viable solution and that profiles reconstructed by our framework can be used to run many plugins, which are essential for a successful forensics investigation.


Author(s):  
Xiaoqing Gu ◽  
Kaijian Xia ◽  
Yizhang Jiang ◽  
Alireza Jolfaei

Text sentiment classification is an important technology for natural language processing. A fuzzy system is a strong tool for processing imprecise or ambiguous data, and it can be used for text sentiment analysis. This article proposes a new formulation of a multi-task Takagi-Sugeno-Kang fuzzy system (TSK FS) modeling, which can be used for text sentiment image classification. Using a novel multi-task fuzzy c-means clustering algorithm, the common (public) information among all tasks and the individual (private) information for each task are extracted. The information about clustering, for example, cluster centers, can be used to learn the antecedent parameters of multi-task TSK fuzzy systems. With the common and individual antecedent parameters obtained, a corresponding multi-task learning mechanism for learning consequent parameters is devised. Accordingly, a multi-task fuzzy clustering–based multi-task TSK fuzzy system (MTFCM-MT-TSK-FS) is proposed. When the proposed model is built, the information conveyed by the fuzzy rules formed is two-fold, including (1) common fuzzy rules representing the inter-task correlation information and (2) individual fuzzy rules depicting the independent information of each task. The experimental results on several text sentiment datasets demonstrate the validity of the proposed model.


2022 ◽  
pp. 144078332110669
Author(s):  
Sharyn Roach Anleu ◽  
George Sarantoulias

Responses to the Covid-19 pandemic include the generation of new norms and shifting expectations about everyday, ordinary behaviour, management of the self, and social interaction. Central to the amalgam of new norms is the way information and instructions are communicated, often in the form of simple images and icons in posters and signs that are widespread in public settings. This article combines two sociological concerns – social control and visual research – to investigate the ways social interaction is being recalibrated during the pandemic. It focuses on some of the imagery relied on in public information about the coronavirus and investigates the form and content of various signs, instructions, and notices for their normative underpinnings, their advice and directives which attempt to modify and regulate diverse activities.


Author(s):  
Modesto Escobar ◽  
Elena Gil Moreno ◽  
Cristina Calvo López

Las redes sociales online se han ido convirtiendo en uno de los principales vehículos de comunicación y una de las mayores fuentes de información de actualidad. Esta creciente popularidad deja en evidencia la importancia de que los científicos sociales seamos capaces de analizar, interpretar y comprender en profundidad este nuevo tipo de herramientas. Este artículo tiene como objetivo mostrar los diversos métodos de análisis de la información pública obtenida a partir de una de estas redes, Twitter. Para ello tomamos como ejemplificación explicativa el caso #Cuéntalo, un episodio de narrativa compartida iniciado en esta red entre los días 26 y 28 de abril de 2018 tras la conocida sentencia de “La Manada”. A través de este caso se presentan aquí distintas metodologías para el estudio de los contenidos transmitidos, que van desde los análisis descriptivos más elementales hasta los análisis de contenido, pasando por la clasificación de actores relevantes y el descubrimiento de la estructura de las relaciones entre los protagonistas y sus mensajes. Los resultados muestran cómo esta polémica sentencia derivó en una conversación digital viral donde distintas usuarias (en especial periodistas, escritoras y activistas feministas) comenzaron a compartir sus relatos de situaciones de violencia sexual vividas por las participantes o sus conocidas usando esta etiqueta, siendo capaces de identificar a las principales protagonistas, las distintas relaciones que establecieron entre ellas y sus mensajes y los principales temas que se conformaron en torno a ellos. Online social networks have become one of the main communication vehicles and one of the greatest sources of current information. This growing popularity shows the importance of social scientists being able to analyze, interpret and understand in depth this new type of tools. This article aims to show the diverse methods of analysis of public information obtained from one of these networks, Twitter. To do this, we take as an explanatory example the case of #Cuéntalo, an episode of shared narrative that began on this network between April 26 and 28, 2018 after the well-known sentence of “La Manada”. Through this case, we present different methodologies for the study of broadcasted content, ranging from the most elementary descriptive tools to content analysis, passing through the classification of relevant actors and the discovery of the structure of the relationships amongst their protagonists and their messages. The results show how this controversial sentence led to a viral digital conversation where different users (especially journalists, writers, feminists and influencers) began to share their stories of situations of sexual violence experienced by the participants or their acquaintances using this label. Through this analysis, it was possible to identify the main protagonists, the different relationships that they established between them and their messages and the main themes that were formed around them.


2022 ◽  
Vol 8 ◽  
pp. e810
Author(s):  
Abdallah Qusef ◽  
Hamzeh Alkilani

The Internet’s emergence as a global communication medium has dramatically expanded the volume of content that is freely accessible. Through using this information, open-source intelligence (OSINT) seeks to meet basic intelligence requirements. Although open-source information has historically been synonymous with strategic intelligence, today’s consumers range from governments to corporations to everyday people. This paper aimed to describe open-source intelligence and to show how to use a few OSINT resources. In this article, OSINT (a combination of public information, social engineering, open-source information, and internet information) was examined to define the present situation further, and suggestions were made as to what could happen in the future. OSINT is gaining prominence, and its application is spreading into different areas. The primary difficulty with OSINT is separating relevant bits from large volumes of details. Thus, this paper proposed and illustrated three OSINT alternatives, demonstrating their existence and distinguishing characteristics. The solution analysis took the form of a presentation evaluation, during which the usage and effects of selected OSINT solutions were reported and observed. The paper’s results demonstrate the breadth and dispersion of OSINT solutions. The mechanism by which OSINT data searches are returned varies greatly between solutions. Combining data from numerous OSINT solutions to produce a detailed summary and interpretation involves work and the use of multiple disjointed solutions, both of which are manual. Visualization of results is anticipated to be a potential theme in the production of OSINT solutions. Individuals’ data search and analysis abilities are another trend worth following, whether to optimize the productivity of currently accessible OSINT solutions or to create more advanced OSINT solutions in the future.


2022 ◽  
pp. 155-170

To make ends meet as a freelancer, people have to build a serious and credible skillset (through formal education, credentialing, deep practice) and offer sufficient public information to draw the attention of potential clients. Depending on their particular expertise, they have to have social contacts in the field, and they have to be active on various platforms to bid for work. Freelancers have a variety of social media platforms that they may socialize on for mutual support and advice sharing. Sometimes, to build their credibility, freelancers will create and share peer-to-peer teaching and learning resources. These individuals and teams have to share relevant information without giving away any competitive advantage, given the sparsity of paid jobs and projects. To consider generosity and stinginess of social advice sharing, this work explores some peer-shared teaching and learning resources on the Social Web surrounding freelance work, including a set of 126 slideshows on a popular social slide-sharing site and 16 video transcripts from a popular video-sharing site.


2022 ◽  
Vol 9 (1) ◽  
Author(s):  
P. Brañas-Garza ◽  
D. Jorrat ◽  
A. Alfonso ◽  
A. M. Espín ◽  
T. García Muñoz ◽  
...  

We report data from an online experiment which allows us to study how generosity changed over a 6-day period during the initial explosive growth of the COVID-19 pandemic in Andalusia, Spain, while the country was under a strict lockdown. Participants ( n = 969) could donate a fraction of a €100 prize to an unknown charity. Our data are particularly rich in the age distribution and we complement them with daily public information about COVID-19-related deaths, infections and hospital admissions. We find correlational evidence that donations decreased in the period under study, particularly among older individuals. Our analysis of the mechanisms behind the detected decrease in generosity suggests that expectations about others' behaviour, perceived mortality risk and (alarming) information play a key—but independent—role for behavioural adaptation. These results indicate that social behaviour is quickly adjusted in response to the pandemic environment, possibly reflecting some form of selective prosociality.


2022 ◽  
pp. 631-645
Author(s):  
Pin-Yu Chu ◽  
Hsien-Lee Tseng ◽  
Yu-Jui Chen

Facebook, the most popular social media in the world, has changed the ways of citizen involvement in governance. Politicians and (elected) public administrators worldwide have adopted Facebook as an important approach to connect with citizens. This study explores whether the Facebook phenomenon can improve the process of online political communication and citizen participation. The study adapts a content analysis method and proposes six strategies for analyzing Facebook page posts of Taiwanese legislators. The authors compare Facebook posts during both election and regular sessions to see the difference in patterns of these posts and communication strategies adopted by the legislators. The findings reveal that a percentage of e-participation achieves an acceptable rate, but most communication of legislator Facebook is one way. The results indicate that legislators' Facebook is another platform to distribute public information to citizens, and many have potential to create more public values.


2021 ◽  
Vol 2 (6) ◽  
Author(s):  
Zhiming Gong

The investment concept, reflecting the investor's investment purpose and willingness, is a value that embodies the investor's investment personality characteristics, prompts investors to carry out investment analysis, judgment, decision-making, and guides investor behaviors. Due to different maturity of the capital market in China and Western countries, there are many differences in the regulatory level, cultural and behavioral patterns of the supervision and management departments of the capital market between Chinese and Western investment philosophy. This article analyzes the differences in investment ideas between Chinese and Western investors from the culture perspective. This thesis studies on the basis of four cultural differences: "The Golden Mean" and "Interest Maximization"; the face-culture and individualism; rule of man and rule of law; and gambler psychology and adventure spirit. Based on these four aspects of cultural differences, four different investment concepts of Chinese and Western investors are analyzed: long-term investments and short-term speculation; "Herd Effect" and independent decision; grapevines and public information; and leveraged trading and allocation of funds. This thesis adopts several cases to analyze the differences between Chinese and Western investors in financial products such as stocks, gold, and futures, and in investment behavior such as the long-term investment, short-term speculation, leveraged trading, and investment portfolios. With cultural differences between China and the West probed into, the differences between Chinese and Western investors' investment concepts are justified. It is hoped that this effort will help investors deepen the understanding of the capital markets in China and the West, enable Chinese investors to learn the Western mature investment concepts, and facilitate the regulators to manage the capital market effectively.


Cryptography ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Jongkil Kim ◽  
Yang-Wai Chow ◽  
Willy Susilo ◽  
Joonsang Baek ◽  
Intae Kim

We propose a new functional encryption for pattern matching scheme with a hidden string. In functional encryption for pattern matching (FEPM), access to a message is controlled by its description and a private key that is used to evaluate the description for decryption. In particular, the description with which the ciphertext is associated is an arbitrary string w and the ciphertext can only be decrypted if its description matches the predicate of a private key which is also a string. Therefore, it provides fine-grained access control through pattern matching alone. Unlike related schemes in the literature, our scheme hides the description that the ciphertext is associated with. In many practical scenarios, the description of the ciphertext cannot be public information as an attacker may abuse the message description to identify the data owner or classify the target ciphertext before decrypting it. Moreover, some data owners may not agree to reveal any ciphertext information since it simply gives greater advantage to the adversary. In this paper, we introduce the first FEPM scheme with a hidden string, such that the adversary cannot get any information about the ciphertext from its description. The security of our scheme is formally analyzed. The proposed scheme provides both confidentiality and anonymity while maintaining its expressiveness. We prove these security properties under the interactive general Diffie–Hellman assumption (i-GDH) and a static assumption introduced in this paper.


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