Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item Attacks on web services and mitigation schemes(2010) Patel, V.; Mohandas, R.; Pais, A.R.Web Services have become dependable platform for e-commerce and many B2B models. Extensive adaptation of Web Services has resulted in a bunch of standards such as WS-Security, WS-Trast etc. to support business and security requirements for the same. Majority of the web services are offered over Http with Simple Object Access Protocol (SOAP) as an underlying exchange infrastructure. This paper describes attacks targeted at Web Services such as XML injection, XSS injection, HTTP header manipulation, sending stale message and other protocol specific attacks. We have used XML Re-Writing mechanism to perform "timestamp modification attack" and WS-Trast, WS-SecureConversation protocols attack. Schemas stated in WSDL file may not be accurate enough to validate messages effectively; Schemas should reflect structure of all possible genuine requests. Hence, we have proposed a new self-adaptive schema hardening algorithm to obtain fine-tuned schema that can be used to validate SOAP messages more effectively. We have also proposed mitigation techniques to counter attacks using MIME/DIME attachments.Item Safeguarding web services using self-adaptive schema hardening algorithm(2011) Patel, V.; Mohandas, R.; Pais, A.R.Web Services in production often evolve over time due to changes in business and security requirements. Often various Web Service standards such as WS-Security, WS-Trust, WS-Routing etc. are introduced or revoked. Such changes alter the structure of an input message accepted by web services. Message validation mechanism becomes in-effective if schemas in use are not updated in line with aforementioned changes. Also, Web Services become prone to different attack vectors if the schemas are loosely defined. Here, we present algorithms that help fine tune schemas by the process of iterative deduction. Also, our work helps to identify patterns of attack vectors that demarcate themselves from genuine messages. Our adaptive schema refining algorithm classifies logged requests into set of schema classes based on a measure of similarity. This classification of messages in to schema classes enables us to tighten the schemas to prevent bad requests or expand the schemas to accommodate newer requests. © 2011 Springer-Verlag.Item Utilizing Machine Learning for Lung Disease Diagnosis(Institute of Electrical and Electronics Engineers Inc., 2024) Markose, G.C.; Sitaraman, S.R.; Kumar, S.V.; Patel, V.; Mohammed, R.J.; Vaghela, C.For lung issues to be really treated and made due, early location and analysis are fundamental. In healthcare, machine learning (ML) strategies have arisen as an expected innovation with quick development, particularly in the field of clinical diagnostics. To analyze lung diseases, this research investigates the utilization of machine learning calculations. It centers around picture examination, patient information understanding, and the reconciliation of numerous information hotspots for an intensive investigation. This research's principal objective is to explore the chance of utilizing machine learning calculations to foresee and analyze a scope of lung conditions, including lung malignant growth, bronchitis, asthma, sensitivities, and persistent obstructive pneumonic disease (COPD). Proactive mediation depends on expecting the probability of lung issues before they manifest. Utilizing an assortment of machine learning techniques for classification and expectation, the examination assembled a heterogeneous dataset fully intent on laying the preparation for protection healthcare measures. © 2024 IEEE.