Detecting Hijacked Journals by Using Classification Algorithms.

Invalid journals are recent challenges in the academic world and many researchers are unacquainted with the phenomenon. The number of victims appears to be accelerating. Researchers might be suspicious of predatory journals because they have unfamiliar names, but hijacked journals are imitations of well-known, reputable journals whose websites have been hijacked. Hijacked journals issue calls for papers via generally laudatory emails that delude researchers into paying exorbitant page charges for publication in a nonexistent journal. This paper presents a method for detecting hijacked journals by using a classification algorithm. The number of published articles exposing hijacked journals is limited and most of them use simple techniques that are limited to specific journals. Hence we needed to amass Internet addresses and pertinent data for analyzing this type of attack. We inspected the websites of 104 scientific journals by using a classification algorithm that used criteria common to reputable journals. We then prepared a decision tree that we used to test five journals we knew were authentic and five we knew were hijacked.

Identity Theft in the Academic World Leads to Junk Science.

In recent years, identity theft has been growing in the academic world. Cybercriminals create fake profiles for prominent scientists in attempts to manipulate the review and publishing process. Without permission, some fraudulent journals use the names of standout researchers on their editorial boards in the effort to look legitimate. This opinion piece, highlights some of the usual types of identity theft and their role in spreading junk science. Some general guidelines that editors and researchers can use against such attacks are presented.

Autonomy and paternalism in medical e-commerce.

One of the overriding interests of the literature on health care economics is to discover where personal choice in market economies end and corrective government intervention should begin. Our study addresses this question in the context of John Stuart Mill's utilitarian principle of harm. Our primary objective is to determine whether public policy interventions concerning more than 35,000 online pharmacies worldwide are necessary and efficient compared to traditional market-oriented approaches. Secondly, we seek to determine whether government interference could enhance personal  utility maximization, despite its direct and indirect (unintended) costs on medical e-commerce. This study finds that containing the negative externalities of medical e-commerce provides the most compelling raison d'etre of government interference. It asserts that autonomy and paternalism need not be mutually exclusive, despite their direct and indirect consequences on individual choice and decision-making processes. Valuable insights derived from Mill's principle should enrich theory-building in health care economics and policy.

False identification use among college students increases the risk for alcohol use disorder: results of a longitudinal study.

BACKGROUND: It is well known that using false identification (ID) is a common method by which underage youth in the United States obtain alcohol. While false ID use is associated with high-risk drinking patterns, its association with alcohol use disorder (AUD), independent of other risk factors, has not been firmly established. METHODS: Participants were 1,015 college students recruited from 1 university and assessed annually during their first 4 years of college. Latent variable growth curve modeling was used to identify significant predictors of false ID use and test the hypothesis that false ID use increased the risk for AUD, by increasing the frequency and/or quantity of alcohol use. Several other hypothesized risk factors for AUD were accounted for, including demographics (sex, race, living situation, religiosity, socioeconomic status), individual characteristics (childhood conduct problems, sensation-seeking, age at first drink), high school behaviors (high school drinking frequency, drug use), family factors (parental monitoring, parental alcohol problems), perception of peer drinking norms, and other factors related to false ID use. RESULTS: False IDs were used by almost two-thirds (66.1%) of the sample. False ID use frequency was positively associated with baseline quantity and frequency of alcohol use, independent of all other factors tested. False ID use was not directly related to AUD risk, but indirectly predicted increases in AUD risk over time through its association with greater increases in alcohol use frequency over time. Several predictors of false ID use frequency were also identified. CONCLUSIONS: False ID use may contribute to AUD risk by facilitating more frequent drinking. If replicated, these findings highlight the potential public health significance of policies that enforce sanctions against false ID use. Students who use false IDs represent an important target population for alcohol prevention activities.

Online handwritten signature verification using neural network classifier based on principal component analysis.

One of the main difficulties in designing online signature verification (OSV) system is to find the most distinctive features with high discriminating capabilities for the verification, particularly, with regard to the high variability which is inherent in genuine handwritten signatures, coupled with the possibility of skilled forgeries having close resemblance to the original counterparts. In this paper, we proposed a systematic approach to online signature verification through the use of multilayer perceptron (MLP) on a subset of principal component analysis (PCA) features. The proposed approach illustrates a feature selection technique on the usually discarded information from PCA computation, which can be significant in attaining reduced error rates. The experiment is performed using 4000 signature samples from SIGMA database, which yielded a false acceptance rate (FAR) of 7.4% and a false rejection rate (FRR) of 6.4%.

[How do adolescents in Germany define cyberbullying? A focus-group study of adolescents from a German major city]. / Wie definieren Jugendliche in Deutschland Cybermobbing? Eine Fokusgruppenstudie unter Jugendlichen einer deutschen Großstadt.

A steadily growing number of empirical research on cyberbullying exists retaining the traditional definition of bullying. However, whether this scientific and theoretical definition represents youths' perceptions and experiences with cyberbullying is a subject of further investigation. Scenarios of cyberbullying incidents were used and later discussed in three focus groups with 20 adolescents (55 % boys, 45 % girls, 11-16 years old). Thematic and content analyses laid focus on the following questions: (1) Which terms are used by the adolescents to describe the behaviors in the incidents? (2) What are the roles of traditional bullying definition criteria (i. e. intention, repetition, and power imbalance) and two additional cyberbullying-specific criteria (i. e. anonymity and publicity)? (3) How are the behaviors perceived in comparison to each other? Results show that German adolescents perceive "cybermobbing" as the best term to describe the presented incidents. Impersonation was not perceived as cyberbullying by the adolescents, but rather viewed as a criminal act. In addition, adolescents perceived the intent to harm, the impact on the victim, and repetition relevant for defining cyberbullying. Moreover, analyses revealed an interdependence between criteria which suggests that anonymity and publicity have an effect on the severity of the behavior, however they were not essential for the definition of cyberbullying.

Non-strategic detection of identity-threatening information: Epistemic validation and identity defense may share a common cognitive basis.

Readers use prior knowledge to evaluate the validity of statements and detect false information without effort and strategic control. The present study expands this research by exploring whether people also non-strategically detect information that threatens their social identity. Participants (N = 77) completed a task in which they had to respond to a "True" or "False" probe after reading true, false, identity-threatening, or non-threatening sentences. Replicating previous studies, participants reacted more slowly to a positive probe ("True") after reading false (vs. true) sentences. Notably, participants also reacted more slowly to a positive probe after reading identity-threatening (vs. non-threatening) sentences. These results provide first evidence that identity-threatening information, just as false information, is detected at a very early stage of information processing and lends support to the notion of a routine, non-strategic identity-defense mechanism.

Out of control? Using STAMP to model the control and feedback mechanisms surrounding identity crime in darknet marketplaces.

Darknet marketplaces have emerged as a facilitator of identity crime and trading. This study aimed to (1) understand the entities and control and feedback mechanisms that influence identity crime prevention and occurrence on the darknet in the Australian system and to (2) comprehensively identify the implications of control failures across all system levels. The Systems-Theoretic Accident Model and Processes (STAMP) was used to develop an identity crime control structure in consultation with subject matter experts and then the Systems-Theoretic Process Analysis (STPA) was applied. The STPA identified 310 risk states, resulting from control failures and which were associated with the range of agencies, organisations, and individuals present across system levels. As darknet marketplaces rapidly evolve, alignment between these entities is necessary to enable agile system responses. STAMP and STPA have promise in understanding the potential for intervention across all system levels in preventing societal issues such as identity crime.

A generic construction for revocable identity-based encryption with subset difference methods.

To deal with dynamically changing user's credentials in identity-based encryption (IBE), providing an efficient key revocation method is a very important issue. Recently, Ma and Lin proposed a generic method of designing a revocable IBE (RIBE) scheme that uses the complete subtree (CS) method by combining IBE and hierarchical IBE (HIBE) schemes. In this paper, we propose a new generic method for designing an RIBE scheme that uses the subset difference (SD) method instead of using the CS method. In order to use the SD method, we generically design an RIBE scheme by combining IBE, identity-based revocation (IBR), and two-level HIBE schemes. If the underlying IBE, IBR, and HIBE schemes are adaptively (or selectively) secure, then our RIBE scheme is also adaptively (or selectively) secure. In addition, we show that the layered SD (LSD) method can be applied to our RIBE scheme and a chosen-ciphertext secure RIBE scheme also can be designed generically.