Process of Security Assurance Technique for Application Functional Logic in E-Commerce Systems

Security practices such as Audits that often focus on penetration testing are performed to find flaws in some types of vulnerability & use tools, which have been tailored to resolve certain risks based on code errors, code conceptual assumptions bugs, etc. Most existing security practices in e-Commerce are dealt with as an auditing activity. They may have policies of security, which are enforced by auditors who enable a particular set of items to be reviewed, but also fail to find vulnerabilities, which have been established in compliance with application logic. In this paper, we will investigate the problem of business logic vulnerability in the component-based rapid development of e-commerce applications while reusing design specification of component. We propose secure application functional processing Logic Security technique for component-based e-commerce application, based on security requirement of e-business process and security assurance logical component behaviour specification approach to formulize and design a solution for business logic vulnerability phenomena.

Lom： Discovering Logic Flaws Within MongoDB-based Web Applications

Logic flaws within web applications will allow malicious operations to be triggered towards back-end database. Existing approaches to identifying logic flaws of database accesses are strongly tied to structured query language （SQL） statement construction and cannot be applied to the new generation of web applications that use not only structured query language （NoSQL） databases as the storage tier. In this paper, we present Lom, a black-box approach for discovering many categories of logic flaws within MongoDB- based web applications. Our approach introduces a MongoDB operation model to support new features of MongoDB and models the application logic as a mealy finite state machine. During the testing phase, test inputs which emulate state violation attacks are constructed for identifying logic flaws at each application state. We apply Lom to several MongoDB-based web applications and demonstrate its effectiveness.