The complexity of Lucent Technologies' advanced 5ESS® switching system makes the cost of finding, fixing, and retesting a software fault very high. The current 5ESS system contains several million lines of source code, which provide many complicated real‐time switching function features. As customer demands for ever‐increasing product quality compound the high cost of testing and reworking source code, it is crucial for the 5ESS Switching Development organization to find ways to prevent faults from being introduced into the software in the first place. The 5ESS Switch Coding Fault Prevention Team was assembled to find methods to prevent the most frequent faults from being injected into a product during coding. The Coding Fault Prevention Guidelines, developed by the team for use in various Lucent switching development organizations, lists the most frequent errors made during coding. It also provides coders with information that will help reduce the risk of introducing faults into the software. This paper describes the most common preventable faults and the technical guidelines developed to overcome them. It also explains the metrics used to evaluate the results achieved.
Phishing has become the most popular practice among the criminals of the Web. Phishing attacks are becoming more frequent and sophisticated. The impact of phishing is drastic and significant since it can involve the risk of identity theft and financial losses. This paper explains the most popular methods used for phishing and the PhishCatch algorithm developed to detect phishing. The PhishCatch algorithm is a heuristic based algorithm which will detect phishing emails and alert the users about the phishing emails. The phishing filters and rules in the algorithm are formulated after extensive research of phishing methodologies and tactics. After testing, we determined that PhishCatch algorithm has a catch rate of 80% and an accuracy of 99%. The approach used in developing this algorithm, the implementation details and testing results are discussed in this paper.
Phishing, a criminal act ofcollecting personal, bank and credit card information by sending outforged e-mails with fake websites, has become the most popular practice among the criminals of the Web. Phishing attacks are becoming more and more sophisticated and are constantly on the rise. The impact ofphishing is quite drastic since it involves the threat of identity theft and financial losses. A lot of groups and organizations are trying to study this act and also inform and update the public on what are the latest tactics being used in the phishing sector. According to industry estimates, phishing attacks are on the rise every year and the existing anti phishing solutions fall short in detecting phishing. Moreover, phishers come up with innovative methods ofphishing everyday making it even more difficult to detect and prevent phishing. This paper explains in detail the various methods used in phishing. We perform a root-cause analysis of the methods used in phishing, the motivation for phishing and in the process come up with a jishbone diagram outlining the causes and methodologies used in phishing. This analysis is aimed at helping developers to design and develop better anti phishing solutions.
The new technology of Web services is beginning to impact the global business approaches and trends in which the services are being offered and consumed. The advancement of Web services and its wide spread use require that its quality of service (QoS) components to be highly dependable and robust. It is clear that one of the major inevitable challenges facing the business organizations today is to provide adequate QoS aspects for Web services. This paper gathers together the various techniques that can be used for measuring and optimizing the major QoS requirements for Web services proposed by the World Wide Consortium (W3C), while presenting a methodology to build QoS-aware Web services. A software model was designed and implemented to test a Web service and perform the experiments to quantitatively measure the QoS requirements involved in a Web service. Various modeling tests and experiments were designed and conducted to illustrate the proposed QoS measurement metrics. The techniques discussed in this paper can be incorporated into the planning, design, implementation, deployment, operational and maintenance phases during a Web service development lifecycle.
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