Web Service Classification and Prediction Using Rule-Based Approach with Recommendations for Quality Improvements

Author(s):  
M. Swami Das ◽  
A. Govardhan ◽  
D. Vijaya Lakshmi
2008 ◽  
Author(s):  
Qianhui Althea Liang ◽  
Herman Lam ◽  
Lalita Narupiyakul ◽  
Patrick C.K. Hung

2018 ◽  
Vol 7 (4.7) ◽  
pp. 322 ◽  
Author(s):  
Abbas Alasri ◽  
Rossilawati Sulaiman

A web service is defined as the method of communication between the web applications and the clients. Web services are very flexible and scalable as they are independent of both the hardware and software infrastructure. The lack of security protection offered by web services creates a gap which attackers can make use of. Web services are offered on the HyperText Transfer Protocol (HTTP) with Simple Object Access Protocol (SOAP) as the underlying infrastructure. Web services rely heavily on the Extended Mark-up Language (XML). Hence, web services are most vulnerable to attacks which use XML as the attack parameter. Recently, a new type of XML-based Denial-of-Service (XDoS) attacks has surfaced, which targets the web services. The purpose of these attacks is to consume the system resources by sending SOAP requests that contain malicious XML content. Unfortunately, these malicious requests go undetected underneath the network or transportation layers of the Transfer Control Protocol/Internet Protocol (TCP/IP), as they appear to be legitimate packets.In this paper, a middleware tool is proposed to provide real time detection and prevention of XDoS and HTTP flooding attacks in web service. This tool focuses on the attacks on the two layers of the Open System Interconnection (OSI) model, which are to detect and prevent XDoS attacks on the application layer and prevent flooding attacks at the Network layer.The rule-based approach is used to classify requests either as normal or malicious,in order to detect the XDoS attacks. The experimental results from the middleware tool have demonstrated that the rule-based technique has efficiently detected and prevented theattacks of XDoS and HTTP flooding attacks such as the oversized payload, coercive parsing and XML external entities close to real-time such as 0.006s over the web services. The middleware tool provides close to 100% service availability to normal request, hence protecting the web service against the attacks of XDoS and distributed XDoS (DXDoS).\  


Author(s):  
Padmavathi .S ◽  
M. Chidambaram

Text classification has grown into more significant in managing and organizing the text data due to tremendous growth of online information. It does classification of documents in to fixed number of predefined categories. Rule based approach and Machine learning approach are the two ways of text classification. In rule based approach, classification of documents is done based on manually defined rules. In Machine learning based approach, classification rules or classifier are defined automatically using example documents. It has higher recall and quick process. This paper shows an investigation on text classification utilizing different machine learning techniques.


2019 ◽  
Vol 50 (2) ◽  
pp. 98-112 ◽  
Author(s):  
KALYAN KUMAR JENA ◽  
SASMITA MISHRA ◽  
SAROJANANDA MISHRA ◽  
SOURAV KUMAR BHOI ◽  
SOUMYA RANJAN NAYAK

2010 ◽  
Vol 12 (1) ◽  
pp. 9-16 ◽  
Author(s):  
Xueying ZHNAG ◽  
Guonian LV ◽  
Boqiu LI ◽  
Wenjun CHEN

Author(s):  
G Deena ◽  
K Raja ◽  
K Kannan

: In this competing world, education has become part of everyday life. The process of imparting the knowledge to the learner through education is the core idea in the Teaching-Learning Process (TLP). An assessment is one way to identify the learner’s weak spot of the area under discussion. An assessment question has higher preferences in judging the learner's skill. In manual preparation, the questions are not assured in excellence and fairness to assess the learner’s cognitive skill. Question generation is the most important part of the teaching-learning process. It is clearly understood that generating the test question is the toughest part. Methods: Proposed an Automatic Question Generation (AQG) system which automatically generates the assessment questions dynamically from the input file. Objective: The Proposed system is to generate the test questions that are mapped with blooms taxonomy to determine the learner’s cognitive level. The cloze type questions are generated using the tag part-of-speech and random function. Rule-based approaches and Natural Language Processing (NLP) techniques are implemented to generate the procedural question of the lowest blooms cognitive levels. Analysis: The outputs are dynamic in nature to create a different set of questions at each execution. Here, input paragraph is selected from computer science domain and their output efficiency are measured using the precision and recall.


Author(s):  
Supriya Raheja ◽  
Geetika Munjal ◽  
Jyoti Jangra ◽  
Rakesh Garg

Author(s):  
Isanka Rajapaksha ◽  
Chanika Ruchini Mudalige ◽  
Dilini Karunarathna ◽  
Nisansa de Silva ◽  
Gathika Rathnayaka ◽  
...  

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