Classification of logical vulnerability based on group attacking method

New advancement in the field of e-commerce software technology has also brought many benefits, at the same time developing process always face different sort of problems from design phase to implement phase. Software faults and defects increases the issues of reliability and security, that’s reason why a solution of this problem is required to fortify these issues. The paper addresses the problem associated with lack of clear component-based web application related classification of logical vulnerabilities through identifying Attack Group Method by categorizing two different types of vulnerabilities in component-based web applications. A new classification scheme of logical group attack method is proposed and developed by using a Posteriori Empirically methodology

Proposing a secure component-based-application logic and system’s integration testing approach

Software engineering moved from traditional methods of software enterprise applications to com-ponent based development for distributed system’s applications. This new era has grown up forlast few years, with component-based methods, for design and rapid development of systems, butfact is that , deployment of all secure software features of technology into practical e-commercedistributed systems are higher rated target for intruders. Although most of research has been con-ducted on web application services that use a large share of the present software, but on the otherside Component Based Software in the middle tier ,which rapidly develops application logic, alsoopen security breaching opportunities .This research paper focus on a burning issue for researchersand scientists ,a weakest link in component based distributed system, logical attacks, that cannotbe detected with any intrusion detection system within the middle tier e-commerce distributed ap-plications. We proposed An Approach of Secure Designing application logic for distributed system,while dealing with logically vulnerability issue

Authorization algorithms for permission-role assignments

Permission-role assignments (PRA) is one important process in Role-based access control (RBAC) which has been proven to be a flexible and useful access model for information sharing in distributed collaborative environments. However, problems may arise during the procedures of PRA. Conflicting permissions may assign to one role, and as a result, the role with the permissions can derive unexpected access capabilities. This paper aims to analyze the problems during the procedures of permission-role assignments in distributed collaborative environments and to develop authorization allocation algorithms to address the problems within permission-role assignments. The algorithms are extended to the case of PRA with the mobility of permission-role relationship. Finally, comparisons with other related work are discussed to demonstrate the effective work of the paper

CSCWD technologies, applications and challenges [Editorial]

As CSCWD (Computer Supported Cooperative Work in Design) has involved the cooperation of multidisciplinary design teams, traditionally the communication among different design teams has been facilitated by the Intranet or Extranet, which makes the applications of CSCWD more expensive and hardly accessible to most organizations, especially small and medium enterprises. The Internet which can be accessed anywhere and at anytime has changed the whole world as well as CSCWD communities. The phenomenon of Internet has significantly reshaped the research of CSCWD. The universal and nearly free accessibility has made it much easier for people to coordinate and do collaborative design jobs without any physical location boundaries. The new technologies and applications from CSCWD have significantly contributed to the multidisciplinary design teams. Over the past thirteen years, CSCWD communities have been actively involved in the dynamic researches and practical developments from both academia and industry. In order to address the new challenges that CSCWD communities are facing, we carefully selected 15 manuscripts from 198 papers (from 360 original submissions) presented at the 12th International Conference on Computer Supported Cooperative Work in Design (CSCWD 2008), Xi�an, China on April 16-18, 2008, to forge this J.UCS special issue. It is intended for researchers and practitioners interested in CSCWD Technologies, Applications and Challenges. All selected papers have been revised and extended into current versions by three rigorous review rounds

Extended RBAC with role attributes

Though RBAC has been researched for many years as a current dominant access control technology, there are few researches to be done to address the further extension of the role which is the fundamental entity of RBAC. This paper tries to extend the role to a further level, the role attributes. Through the attributes, the function and operation on the role can be enhanced and extended. Through the attributes, ANSI RBAC is significantly extended. In the inheritance of hierarchical role, the privacy of its parental role can be kept by using HA (Hidden Attribute)

Mining heterogeneous information graph for health status classification

In the medical domain, there exists a large volume of data from multiple sources such as electronic health records, general health examination results, and surveys. The data contain useful information reflecting people’s health and provides great opportunities for studies to improve the quality of healthcare. However, how to mine these data effectively and efficiently still remains a critical challenge. In this paper, we propose an innovative classification model for knowledge discovery from patients’ personal health repositories. By based on analytics of massive data in the National Health and Nutrition Examination Survey, the study builds a classification model to classify patients’health status and reveal the specific disease potentially suffered by the patient. This paper makes significant contributions to the advancement of knowledge in data mining with an innovative classification model specifically crafted for domain-based data. Moreover, this research contributes to the healthcare community by providing a deep understanding of people’s health with accessibility to the patterns in various observations

Cloud computing adoption in regional councils

Cloud computing is becoming increasingly important in information technology as an enabler for improved productivity, efficiency and cost reduction; and is expected to offer benefits for public sector organisations. Cloud computing has the potential to improve the reliability and scalability of information technology systems, which allows organisations such as regional municipal governments to focus more on their core business and strategy. Research about the use of cloud computing in the public sector in general is limited. There is a lack of exploratory studies that provide an in-depth and holistic investigation of the factors perceived to influence the adoption of cloud computing. There are no empirical studies about the factors that are perceived to influence the adoption of cloud computing in reference to Australia. This research aimed at exploring perceptions of the potential for value creation from cloud computing in regional councils, to identify factors that are likely to influence adoption of cloud computing including factors that need to be considered when planning to adopt cloud, anticipated benefits of cloud adoption, and challenges and issues that faced cloud adoption. This research aimed to improve understandings related to the factors that influence cloud computing adoption decision making in regional municipal governments. The research employed a mixed method approach (qualitative and quantitative). In-depth interviews of Australian councils’ IT managers were conducted with the aim of providing insights into the factors that are perceived likely to influence adoption of cloud computing including factors that need to be considered when planning to adopt cloud, anticipated benefits of cloud adoption, and challenges and issues that faced cloud adoption. Survey data from 480 IT staff across 47 local government councils were collected to confirm the findings of the exploratory stage. The factors that were examined included: compatibility, complexity, cost, security concern, top management support, organisation size, government regulation, and information intensity. The findings of this research are expected to assist in making investment decisions on cloud computing adoption

Drug prescription support in dental clinics through drug corpus mining

The rapid increase in the volume and variety of data poses a challenge to safe drug prescription for the dentist. The increasing number of patients that take multiple drugs further exerts pressure on the dentist to make the right decision at point-of-care. Hence, a robust decision support system will enable dentists to make decisions on drug prescription quickly and accurately. Based on the assumption that similar drug pairs have a higher similarity ratio, this paper suggests an innovative approach to obtain the similarity ratio between the drug that the dentist is going to prescribe and the drug that the patient is currently taking. We conducted experiments to obtain the similarity ratios of both positive and negative drug pairs, by using feature vectors generated from term similarities and word embeddings of biomedical text corpus. This model can be easily adapted and implemented for use in a dental clinic to assist the dentist in deciding if a drug is suitable for prescription, taking into consideration the medical profile of the patients. Experimental evaluation of our model’s association of the similarity ratio between two drugs yielded a superior F score of 89%. Hence, such an approach, when integrated within the clinical work flow, will reduce prescription errors and thereby increase the health outcomes of patients

Drug prescription support in dental clinics through drug corpus mining

The rapid increase in the volume and variety of data poses a challenge to safe drug prescription for the dentist. The increasing number of patients that take multiple drugs further exerts pressure on the dentist to make the right decision at point-of-care. Hence, a robust decision support system will enable dentists to make decisions on drug prescription quickly and accurately. Based on the assumption that similar drug pairs have a higher similarity ratio, this paper suggests an innovative approach to obtain the similarity ratio between the drug that the dentist is going to prescribe and the drug that the patient is currently taking. We conducted experiments to obtain the similarity ratios of both positive and negative drug pairs, by using feature vectors generated from term similarities and word embeddings of biomedical text corpus. This model can be easily adapted and implemented for use in a dental clinic to assist the dentist in deciding if a drug is suitable for prescription, taking into consideration the medical profile of the patients. Experimental evaluation of our model’s association of the similarity ratio between two drugs yielded a superior F score of 89%. Hence, such an approach, when integrated within the clinical work flow, will reduce prescription errors and thereby increase the health outcomes of patients

Transcriptional activation of CBFβ by CDK11p110 is necessary to promote osteosarcoma cell proliferation.

BACKGROUND:Aberrant expression of cyclin-dependent protein kinases (CDK) is a hallmark of cancer. CDK11 plays a crucial role in cancer cell growth and proliferation. However, the molecular mechanisms of CDK11 and CDK11 transcriptionally regulated genes are largely unknown. METHODS:In this study, we performed a global transcriptional analysis using gene array technology to investigate the transcriptional role of CDK11 in osteosarcoma. The promoter luciferase assay, chromatin immunoprecipitation assay, and Gel Shift assay were used to identify direct transcriptional targets of CDK11. Clinical relevance and function of core-binding factor subunit beta (CBFβ) were further accessed in osteosarcoma. RESULTS:We identified a transcriptional role of protein-DNA interaction for CDK11p110, but not CDK11p58, in the regulation of CBFβ expression in osteosarcoma cells. The CBFβ promoter luciferase assay, chromatin immunoprecipitation assay, and Gel Shift assay confirmed that CBFβ is a direct transcriptional target of CDK11. High expression of CBFβ is associated with poor outcome in osteosarcoma patients. Expression of CBFβ contributes to the proliferation and metastatic behavior of osteosarcoma cells. CONCLUSIONS:These data establish CBFβ as a mediator of CDK11p110 dependent oncogenesis and suggest that targeting the CDK11- CBFβ pathway may be a promising therapeutic strategy for osteosarcoma treatment