scholarly journals Abnormal User Detection Based on the Correlation Probabilistic Model

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xiaohui Yang ◽  
Ying Sun
Keyword(s):  
Probabilistic Model ◽  
User Behavior ◽  
Detection Algorithm ◽  
Malicious Nodes ◽  
Markov Logic ◽  
Correlation Degree ◽  
User Groups ◽  
Measurement Algorithm ◽  
And Behavior ◽  
User Security

As an important part of the new generation of information technology, the Internet of Things (IoT), which is developing rapidly, requires high user security. However, malicious nodes located in an IoT network can influence user security. Abnormal user detection and correlation probability analysis are fundamental and challenging problems. In this paper, the probabilistic model of the correlation between abnormal users (PMCAU) is proposed. First, the concept of user behavior correlation degree is proposed, which is defined as two parts: user attribute similarity degree and behavior interaction degree; the attribute similarity measurement algorithm and behavior correlation measurement algorithm are constructed, respectively, and the spontaneous and interactive behaviors of users were analyzed to determine the abnormal correlated users. Second, first-order logic grammar is used to express the before and after connection of user behavior and to deduce the probabilistic of occurrence of the correlation of behavior and determine the abnormal user groups. Experimental results show that, compared with the traditional anomaly detection algorithm and Markov logic network, this model can identify the users correlated with anomalies, make probabilistic inferences on the possible associations, and identify the potential abnormal user groups, thus achieving higher accuracy and predictability in the IoT.

scholarly journals User Audit Model Based on Attribute Measurement and Similarity Measurement

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Xiaohui Yang ◽  
Ying Sun
Keyword(s):  
Information Dissemination ◽  
Similarity Measurement ◽  
Levenshtein Distance ◽  
Malicious Nodes ◽  
Model Based ◽  
Hierarchical Decision ◽  
Secure Networks ◽  
Measurement Algorithm ◽  
Hierarchical Decision Model ◽  
And Behavior

The Internet of Things (IoT) is an open network. And, there are a large number of malicious nodes in the network. These malicious nodes may tamper with the correct data and pass them to other nodes. The normal nodes will use the wrong data for information dissemination due to a lack of ability to verify the correctness of the messages received, resulting in the dissemination of false information on medical, social, and other networks. Auditing user attributes and behavior information to identify malicious user nodes is an important way to secure networks. In response to the user nodes audit problem, a user audit model based on attribute measurement and similarity measurement (AM-SM-UAM) is proposed. Firstly, the user attribute measurement algorithm is constructed, using a hierarchical decision model to construct a judgment matrix to analyze user attribute data. Secondly, the blog similarity measurement algorithm is constructed, evaluating the similarity of blog posts published by different users based on the improved Levenshtein distance. Finally, a user audit model based on a security degree is built, and malicious users are defined by security thresholds. Experimental results show that this model can comprehensively analyze the attribute and behavior data of users and have more accurate and stable performance in the practical application of the network platforms.

scholarly journals The Effects of Explicit and Implicit Interaction on User Experiences in a Mixed Reality Installation: The Synthetic Oracle

2009 ◽  
Vol 18 (4) ◽  
pp. 277-285 ◽  
Author(s):  
Sergi Bermúdez i Badia ◽  
Aleksander Valjamae ◽  
Fabio Manzi ◽  
Ulysses Bernardet ◽  
Anna Mura ◽  
...  
Keyword(s):  
Mixed Reality ◽  
User Behavior ◽  
Activity Level ◽  
Online Behavior ◽  
User Experiences ◽  
Motion Data ◽  
Interaction Mode ◽  
Arm Motion ◽  
And Behavior ◽  
Full Body

Virtual and mixed reality environments (VMRE) often imply full-body human-computer interaction scenarios. We used a public multimodal mixed reality installation, the Synthetic Oracle, and a between-groups design to study the effects of implicit (e.g., passively walking) or explicit (e.g., pointing) interaction modes on the users' emotional and engagement experiences, and we assessed it using questionnaires. Additionally, real-time arm motion data was used to categorize the user behavior and to provide interaction possibilities for the explicit interaction group. The results show that the online behavior classification corresponded well to the users' interaction mode. In addition, contrary to the explicit interaction, the engagement ratings from implicit users were positively correlated with a valence but were uncorrelated with arousal ratings. Interestingly, arousal levels were correlated with different behaviors displayed by the visitors depending on the interaction mode. Hence, this study confirms that the activity level and behavior of users modulates their experience, and that in turn, the interaction mode modulates their behavior. Thus, these results show the importance of the selected interaction mode when designing users' experiences in VMRE.

Time, money, or convenience: what determines Chinese consumers’ continuance usage intention and behavior of using tourism mobile apps?

2019 ◽  
Vol 13 (3) ◽  
pp. 288-302 ◽  
Author(s):  
Feng Xu ◽  
Songshan (Sam) Huang ◽  
Shuaishuai Li
Keyword(s):  
User Behavior ◽  
Mobile Apps ◽  
Equation Modeling ◽  
Chinese Society ◽  
Chinese Consumers ◽  
Time Saving ◽  
Content Type ◽  
Continuance Usage ◽  
And Behavior ◽  
Continuance Usage Intention

Purpose This study aims to examine the effects of three aspects of perceived advantage (i.e. time-saving, money-saving and convenience) on Chinese consumers’ continuance usage intention and behavior of using tourism mobile applications (apps) in the context of Chinese society and culture. Design/methodology/approach Survey data were collected at 20 key tourist attractions in Jinan, China from tourists who visit the attractions. Structural equation modeling was applied to test the hypothetical model. Findings Empirical findings revealed that time-saving directly affected consumers’ continuance usage intention but did not influence user behavior; on the contrary, money-saving had a direct effect on user behavior, but not on intention. Convenience was found to affect both intention and behavior and had a much stronger total effect on user behavior than time-saving and money-saving. Research limitations/implications The study findings offer insights into the further development of tourism mobile apps. While money-saving can be an effective marketing offer for user adoption of tourism mobile apps, tourism mobile apps operators should further tap into the value of time and convenience in designing and developing tourism mobile apps. Originality/value The study expands on practical knowledge of Chinese consumers’ behavior toward using tourism apps.

Multimedia detection algorithm of malicious nodes in intelligent grid based on fuzzy logic

2019 ◽  
Vol 78 (17) ◽  
pp. 24011-24022 ◽  
Author(s):  
Mingming Gao ◽  
Yue Wu ◽  
Jingchang Nan ◽  
Shuyang Cui
Keyword(s):  
Fuzzy Logic ◽  
Detection Algorithm ◽  
Malicious Nodes ◽  
Grid Based

scholarly journals ECG Multilead QT Interval Estimation Using Support Vector Machines

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Jhosmary Cuadros ◽  
Nelson Dugarte ◽  
Sara Wong ◽  
Pablo Vanegas ◽  
Villie Morocho ◽  
...  
Keyword(s):  
Support Vector Machines ◽  
Interval Estimation ◽  
Software Tool ◽  
Detection Algorithm ◽  
Support Vector ◽  
Interval Measurement ◽  
Ecg Signals ◽  
Percent Error ◽  
Vector Machines ◽  
Measurement Algorithm

This work reports a multilead QT interval measurement algorithm for a high-resolution digital electrocardiograph. The software enables off-line ECG processing including QRS detection as well as an accurate multilead QT interval detection algorithm using support vector machines (SVMs). Two fiducial points (Qini and Tend) are estimated using the SVM algorithm on each incoming beat. This enables segmentation of the current beat for obtaining the P, QRS, and T waves. The QT interval is estimated by updating the QT interval on each lead, considering shifting techniques with respect to a valid beat template. The validation of the QT interval measurement algorithm is attained using the Physionet PTB diagnostic ECG database showing a percent error of 2.60±2.25 msec with respect to the database annotations. The usefulness of this software tool is also tested by considering the analysis of the ECG signals for a group of 60 patients acquired using our digital electrocardiograph. In this case, the validation is performed by comparing the estimated QT interval with respect to the estimation obtained using the Cardiosoft software providing a percent error of 2.49±1.99 msec.

scholarly journals SmartMal: A Service-Oriented Behavioral Malware Detection Framework for Mobile Devices

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Chao Wang ◽  
Zhizhong Wu ◽  
Xi Li ◽  
Xuehai Zhou ◽  
Aili Wang ◽  
...  
Keyword(s):  
Anomaly Detection ◽  
Mobile Devices ◽  
Service Oriented Architecture ◽  
Malware Detection ◽  
Detection Algorithm ◽  
Main Task ◽  
Detection Algorithms ◽  
Usage Patterns ◽  
Service Oriented ◽  
And Behavior

This paper presents SmartMal—a novel service-oriented behavioral malware detection framework for vehicular and mobile devices. The highlight of SmartMal is to introduce service-oriented architecture (SOA) concepts and behavior analysis into the malware detection paradigms. The proposed framework relies on client-server architecture, the client continuously extracts various features and transfers them to the server, and the server’s main task is to detect anomalies using state-of-art detection algorithms. Multiple distributed servers simultaneously analyze the feature vector using various detectors and information fusion is used to concatenate the results of detectors. We also propose a cycle-based statistical approach for mobile device anomaly detection. We accomplish this by analyzing the users’ regular usage patterns. Empirical results suggest that the proposed framework and novel anomaly detection algorithm are highly effective in detecting malware on Android devices.

Personalized Spatio-Temporal OLAP Queries Suggestion Based on User Behavior and a New Similarity Measure

2019 ◽  
pp. 105-128
Author(s):  
Olfa Layouni ◽  
Jalel Akaichi
Keyword(s):  
Probabilistic Model ◽  
User Behavior ◽  
Search Behavior ◽  
Relevant Information ◽  
Current User ◽  
Data Cube ◽  
Temporal Data ◽  
Query Suggestion ◽  
Spatio Temporal ◽  
User Search Behavior

Spatio-temporal data warehouses store enormous amount of data. They are usually exploited by spatio-temporal OLAP systems to extract relevant information. For extracting interesting information, the current user launches spatio-temporal OLAP (ST-OLAP) queries to navigate within a geographic data cube (Geo-cube). Very often choosing which part of the Geo-cube to navigate further, and thus designing the forthcoming ST-OLAP query, is a difficult task. So, to help the current user refine his queries after launching in the geo-cube his current query, we need a ST-OLAP queries suggestion by exploiting a Geo-cube. However, models that focus on adapting to a specific user can help to improve the probability of the user being satisfied. In this chapter, first, the authors focus on assessing the similarity between spatio-temporal OLAP queries in term of their GeoMDX queries. Then, they propose a personalized query suggestion model based on users' search behavior, where they inject relevance between queries in the current session and current user' search behavior into a basic probabilistic model.

Mobile Phones and Libraries/Information Centres

2015 ◽  
pp. 287-296
Author(s):  
Jerome Idiegbeyan-Ose ◽  
Goodluck Ifijeh ◽  
Chidi D. Isiakpona
Keyword(s):  
Mobile Phone ◽  
Mobile Phones ◽  
User Behavior ◽  
Information Services ◽  
Negative Behaviors ◽  
Mobile Phone Use ◽  
Library Users ◽  
And Behavior ◽  
Mobile Use ◽  
User Education

This chapter examines mobile phone use and behavior among users in library and information centres. It discusses both observed and perceived mobile phone behaviors among library users and advocates the control of identified negative trends in libraries. It recommends that user education should be intensified; law and legislations on mobile use in libraries should be enacted and guarded jealously. The chapter concludes that, though the use of mobile phones has revolutionized library and information services, it also redefined user behavior. Negative behaviors associated with the use of mobile phones among users will stop or at least reduce while libraries and librarians will continue to evolve ways and means to curb ugly trends.

Relationship of Credit Attitude and Debt to Self-Esteem and Locus of Control in College-Age Consumers

2004 ◽  
Vol 94 (3_suppl) ◽  
pp. 1405-1418 ◽  
Author(s):  
Mary Beth Pinto ◽  
Phylis M. Mansfield ◽  
Diane H. Parente
Keyword(s):  
College Students ◽  
Locus Of Control ◽  
Psychological Factors ◽  
Credit Card ◽  
Credit Cards ◽  
Self Esteem ◽  
College Age ◽  
Significant Difference ◽  
User Groups ◽  
And Behavior

College-age consumers are one of the groups most highly targeted by credit card marketers. While some college students use their credit cards wisely, others are unable to control their spending. The objective of this study was to investigate differences in attitude toward credit cards and the psychological factors of self-esteem and locus of control among college students who possess one or more credit cards. Attitude was operationalized to include three underlying components: cognitive, affective, and behavioral. We separated credit users into subcategories based on amount of installment debt. Convenience users were defined as those consumers who paid the credit-card balance in full each month. Installment users were classified as consumers who carried a balance month-to-month. Convenience users were compared to mild and heavy installment users to assess significance of differences in attitudinal and psychological factors. There were no significant differences in the psychological factors across the credit-card user groups. In addition, there was a statistically significant difference on each of the attitude components (knowledge/beliefs, affect, and behavior) across user groups; convenience users, mild installment, and heavy installment users.

scholarly journals Call Duration Characteristics based on Customers Location

2014 ◽  
Vol 5 (1) ◽  
pp. 67-73
Author(s):  
Karolis Žvinys ◽  
Darius Guršnys
Keyword(s):  
Rural Areas ◽  
Mobile Network ◽  
Small Towns ◽  
Base Stations ◽  
Call Duration ◽  
The People ◽  
User Groups ◽  
Characteristic Features ◽  
And Behavior ◽  
Site Types

Abstract Nowadays a lot of different researches are performed based on call duration distributions (CDD) analysis. However, the majority of studies are linked with social relationships between the people. Therefore the scarcity of information, how the call duration is associated with a user's location, is appreciable. The goal of this paper is to reveal the ties between user's voice call duration and the location of call. For this reason we analyzed more than 5 million calls from real mobile network, which were made over the base stations located in rural areas, roads, small towns, business and entertainment centers, residential districts. According to these site types CDD’s and characteristic features for call durations are given and discussed. Submitted analysis presents the users habits and behavior as a group (not an individual). The research showed that CDD’s of customers being them in different locations are not equal. It has been found that users at entertainment, business centers are tend to talk much shortly, than people being at home. Even more CDD can be distorted strongly, when machinery calls are evaluated. Hence to apply a common CDD for a whole network it is not recommended. The study also deals with specific parameters of call duration for distinguished user groups, the influence of network technology for call duration is considered.

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