Sec-Lib: Protecting Scholarly Digital Libraries From Infected Papers Using Active Machine Learning Framework

Researchers from academia and the corporate-sector rely on scholarly digital libraries to access articles. Attackers take advantage of innocent users who consider the articles' files safe and thus open PDF-files with little concern. In addition, researchers consider scholarly libraries a reliable, trusted, and untainted corpus of papers. For these reasons, scholarly digital libraries are an attractive-target and inadvertently support the proliferation of cyber-attacks launched via malicious PDF-files. In this study, we present related vulnerabilities and malware distribution approaches that exploit the vulnerabilities of scholarly digital libraries. We evaluated over two-million scholarly papers in the CiteSeerX library and found the library to be contaminated with a surprisingly large number (0.3-2%) of malicious PDF documents (over 55% were crawled from the IPs of US-universities). We developed a two layered detection framework aimed at enhancing the detection of malicious PDF documents, Sec-Lib, which offers a security solution for large digital libraries. Sec-Lib includes a deterministic layer for detecting known malware, and a machine learning based layer for detecting unknown malware. Our evaluation showed that scholarly digital libraries can detect 96.9% of malware with Sec-Lib, while minimizing the number of PDF-files requiring labeling, and thus reducing the manual inspection efforts of security-experts by 98%

Scholarly digital libraries as a platform for malware distribution

Researchers from academic institutions and the corporate sector rely heavily on scholarly digital libraries for accessing journal articles and conference proceedings. Primarily downloaded in the form of PDF files, there is a risk that these documents may be compromised by attackers. PDF files have many capabilities that have been widely used for malicious operations. Attackers increasingly take advantage of innocent users who open PDF files with little or no concern, mistakenly considering these files safe and relatively non-threatening. Researchers also consider scholarly digital libraries reliable and home to a trusted corpus of papers and untainted by malicious files. For these reasons, scholarly digital libraries are an attractive target for cyber-attacks launched via PDF files. In this study, we present several vulnerabilities and practical distribution attack approaches tailored for scholarly digital libraries. To support our claim regarding the attractiveness of scholarly digital libraries as an attack platform, we evaluated more than two million scholarly papers in the CiteSeerX library that were collected over 8 years and found it to be contaminated with a surprisingly large number (0.3%-2%) of malicious scholarly PDF documents, the origin of which is 46 different countries spread worldwide. More than 55% of the malicious papers in CiteSeerX were crawled from IP's belonging to USA universities, followed by those belonging to Europe (33.6%). We show how existing scholarly digital libraries can be easily leveraged as a distribution platform both for a targeted attack and in a worldwide manner. On average, a certain malicious paper caused high impact damage as it was downloaded 167 times in 5 years by researchers from different countries worldwide. In general, the USA and Asia downloaded the most malicious scholarly papers, 40.15% and 27.9%, respectively. The top malicious scholarly document downloaded is a malicious version of a popular paper in the computer forensics domain, with 2213 downloads in a worldwide coverage of 108 different countries. Finally, we suggest several concrete solutions for mitigating such attacks, including simple deterministic solutions and also advanced machine learning-based frameworks

“Trapped in an Empty Waiting Room”—The Existential Human Core of Loneliness in Old Age: A Meta-Synthesis

Loneliness in old age has a negative influence on quality of life, health and survival. To understand the phenomenon of loneliness in old age, the voices of lonely older adults should be heard. Therefore, the purpose of this meta-synthesis was to synthesize scientific studies of older adults’ experiences of loneliness. Eleven qualitative articles that met the inclusion criteria were analyzed and synthesized according to Noblit and Hare’s meta-ethnographic approach. The analysis revealed the overriding meaning of the existential human core of loneliness in old age expressed through the metaphor "trapped in an empty waiting room". Four interwoven themes were found: 1) the negative emotions of loneliness, 2) the loss of meaningful interpersonal relationships, 3) the influence of loneliness on self-perception and 4) the older adults’ endeavors to deal with loneliness. The joint contribution of family members, health care providers, and volunteers is necessary to break the vicious circle of loneliness

Examining the Link Between Domestic Violence Victimization and Loneliness in a Dutch Community Sample: A Comparison Between Victims and Nonvictims by Type D Personality

The current study investigated whether differences in loneliness scores between individuals with a distressed personality type (type D personality) and subjects without such a personality varied by domestic violence victimization. Participants (N = 625) were recruited by random sampling from the Municipal Basic Administration of the Dutch city of ‘s-Hertogenbosch and were invited to fill out a set of questionnaires on health status. For this study, only ratings for domestic violence victimization, type D personality, feelings of loneliness, and demographics were used. Statistical analyses yielded main effects on loneliness for both type D personality and history of domestic violence victimization. Above and beyond these main effects, their interaction was significantly associated with loneliness as well. However, this result seemed to apply to emotional loneliness in particular. Findings were discussed in light of previous research and study limitations

Bedside theatre performance and its effects on hospitalised children's well-being

This article reports on practice-based pilot research being undertaken at Birmingham Children's Hospital in England on the impact of bedside theatre performance on hospitalised children's well-being. It discusses the process of creating theatre for sick children, connecting with the hospital and working within the hospital tight routines, dealing with ethics, working with theatre artists and performing to children bedside. It also reports on evidence collected by questionnaire and interviews about the perceived benefits of bedside theatre by children and their parent/carers. This emphasis on the process is appropriate for theatre practitioners, arts therapists and clinical staff who work with hospitalised children

Multiple Imputation Ensembles (MIE) for dealing with missing data

Missing data is a significant issue in many real-world datasets, yet there are no robust methods for dealing with it appropriately. In this paper, we propose a robust approach to dealing with missing data in classification problems: Multiple Imputation Ensembles (MIE). Our method integrates two approaches: multiple imputation and ensemble methods and compares two types of ensembles: bagging and stacking. We also propose a robust experimental set-up using 20 benchmark datasets from the UCI machine learning repository. For each dataset, we introduce increasing amounts of data Missing Completely at Random. Firstly, we use a number of single/multiple imputation methods to recover the missing values and then ensemble a number of different classifiers built on the imputed data. We assess the quality of the imputation by using dissimilarity measures. We also evaluate the MIE performance by comparing classification accuracy on the complete and imputed data. Furthermore, we use the accuracy of simple imputation as a benchmark for comparison. We find that our proposed approach combining multiple imputation with ensemble techniques outperform others, particularly as missing data increases

An ant colony-based semi-supervised approach for learning classification rules

Semi-supervised learning methods create models from a few labeled instances and a great number of unlabeled instances. They appear as a good option in scenarios where there is a lot of unlabeled data and the process of labeling instances is expensive, such as those where most Web applications stand. This paper proposes a semi-supervised self-training algorithm called Ant-Labeler. Self-training algorithms take advantage of supervised learning algorithms to iteratively learn a model from the labeled instances and then use this model to classify unlabeled instances. The instances that receive labels with high confidence are moved from the unlabeled to the labeled set, and this process is repeated until a stopping criteria is met, such as labeling all unlabeled instances. Ant-Labeler uses an ACO algorithm as the supervised learning method in the self-training procedure to generate interpretable rule-based models—used as an ensemble to ensure accurate predictions. The pheromone matrix is reused across different executions of the ACO algorithm to avoid rebuilding the models from scratch every time the labeled set is updated. Results showed that the proposed algorithm obtains better predictive accuracy than three state-of-the-art algorithms in roughly half of the datasets on which it was tested, and the smaller the number of labeled instances, the better the Ant-Labeler performance

Correlates of loneliness among university students

Background The purpose of this study was to investigate level of loneliness, essential needs during university education, and relationships between loneliness, essential needs, and characteristics of university students. A sample comprising 721 students participated in the study. The mean age was 21.58 (SD = 1.73) with a range from 18 to 25. The majority of the students were female (70.6%) and were living in students' dormitory (67.5%) with low (87.8%) income, away from their parents. Methods The UCLA-R loneliness scale and sociodemographic questionnaire which includes an open-ended question on essential needs during university education were administered. Pearson-Product-Moment correlations were used to explore the relationships between participants' loneliness, needs, and characteristics. Results It was found that 60.2% of the participants experienced loneliness. Economical support (81.6%), social interaction (46.9%) and psychosocial support (35%) were the essential needs during university education reported by the participants. The study findings indicate that there were significant relationships between the needs of economical support, social interaction, and loneliness level of university students. Results also show that there were significant relationships among romantic relationship, parents' status and loneliness. Participants' loneliness levels were relatively higher who had not any romantic relationship and were not from married families. Conclusion The findings of this study provided essential information, about Turkish university students, concerning: level of loneliness and relationships that exist among loneliness, needs and sociodemographic characteristics. The findings also suggest implications for psychosocial practice. Because of the mean of loneliness were found to be high (45.49 ± 10.07), for this study, professionals need to pay attention to Turkish university students' psychosocial state, and need to empower them in establishing social relations

Tourism as connectedness.

Late modernity in developed nations is characterized by changing social and psychological conditions, including individualization, processes of competition and loneliness. Remaining socially connected is becoming increasingly important. In this situation, travel provides meaning through physical encounters, inclusion in traveller Gemeinschaft based on shared norms, beliefs and interests, and social status in societies increasingly defined by mobilities. As relationships are forged and found in mobility, travel is no longer an option, rather a necessity for sociality, identity construction, affirmation or alteration. Social contexts and the underlying motivations for tourism have changed fundamentally in late modernity: non-tourism has become a threat to self-conceptions. By integrating social and psychological perspectives, this paper expands and deepens existing travel and mobilities discussions to advance the understanding of tourism as a mechanism of social connectedness, and points to implications for future tourism research