Business Logic Abuse Detection in Cloud Computing .ppt
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1、Business Logic Abuse Detection in Cloud Computing Systems Grzegorz Koaczek,1st International IBM Cloud Academy ConferenceResearch Triangle Park, NC April 19-20,2012,Agenda,Introduction Business logic abuses Spatial statistics Detection of business logic abuses Conclusions,Introduction,Ten most inter
2、esting to industry consumers and security professionals security service categories according to Cloud Security Alliance (2011): 1: Identity and Access Management 2: Data Loss Prevention 3: Web Security 4: Email Security 5: Security Assessments 6: Intrusion Management 7: Security Information and Eve
3、nt Management (SIEM) 8: Encryption 9: Business Continuity and Disaster Recovery 10: Network Security,Introduction,Some of these categories are well known and typical for a very broad range of computer systemsThe importance of the others is relatively new and strictly related to cloud and service ori
4、ented systems e.g.: web security identity and access management security information and event management,Introduction,One of such security related research area, which is crucial for further evolution of Cloud Computing is business logic abuse detection. Business logic abuse is the abuse of the leg
5、itimate business logic of a website or other function that allows interaction. Business logic abuse is usually aimed to exploit in some way the system that supports certain business logic e.g. by an illicit use of a legitimate website function.,Business logic abuses,Examples of business logic abuse:
6、 password guessing Password guessing is a mechanism for a intruder to gain access to an account without having the passwordusing the credit card verification function of a website to confirm validity and expiration dates of stolen credit cardsmass registering accounts or stealing accounts on a websi
7、te to send spam to the websites users, and scraping “personal identifiable information”,Business logic abuses,Detection of business logic abuse is difficult because the offenders are using the same functionality as the legitimate users and therefore, their actions are likely intermixed with real act
8、ions. For example in password guessing Intruder is using the login function of the website to perpetrate his fraud The website doesnt want to turn off the login function, but still needs to stop the intruder from stealing accounts,Business logic abuses,While the intruder is using a legitimate flow o
9、n a website or other application, so disabling that flow would influence also the interactions of legitimate users. This is why the new and versatile methods are required to support the Cloud Computing with appropriate services that could secure them from this type of risk,Business logic abuses,One
10、of possible solution of the business logic abuses is anomaly detection approach. The proposition how to solve the problem of business logic abuses by detection of anomalies in statistical spatial analysis reports is the main point of the current presentation.,Spatial statistics,Spatial analysis is t
11、he process of discovering interesting and previously unknown, but potentially useful patterns from spatial datasets. Extracting interesting and useful patterns from spatial datasets is more challenging than extracting the corresponding patterns from traditional data. This difficulty arises from the
12、complexity of spatial relationships and spatial auto-correlation,Spatial statistics,The research focuses on a statistical model to represent observations of interactions among services constituting some composite services delivered by cloud computing environment. The spatial relationships which are
13、often used as a synonymous with geographical distance between objects, in this case have been redefined as the logical distance between services in an execution graph. The execution graph is created as the description of the sequence in which atomic services must be executed to provide required func
14、tionality.,Spatial statistics,Composite services description is generated from the high level description of business processes. This means that the distance between services is measured as a distance between nodes in a graph rep-resenting composite service execution plan This model has been used fo
15、r estimation and description of spatial correlations among network nodes.,Spatial statistics,Spatial outliers are observations which appear to be inconsistent with their neighborhoods. A spatial outlier can be defined as a spatially referenced object whose non-spatial attribute values differ signifi
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