608 research outputs found

    Application of ARIMA(1,1,0) Model for Predicting Time Delay of Search Engine Crawlers

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    World Wide Web is growing at a tremendous rate in terms of the number of visitors and number of web pages. Search engine crawlers are highly automated programs that periodically visit the web and index web pages. The behavior of search engines could be used in analyzing server load, quality of search engines, dynamics of search engine crawlers, ethics of search engines etc. The more the number of visits of a crawler to a web site, the more it contributes to the workload. The time delay between two consecutive visits of a crawler determines the dynamicity of the crawlers. The ARIMA(1,1,0) Model in time series analysis works well with the forecasting of the time delay between the visits of search crawlers at web sites. We considered 5 search engine crawlers, all of which could be modeled using ARIMA(1,1,0).The results of this study is useful in analyzing the server load

    Using decoys to block SPIT in the IMS

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    Includes bibliographical references (leaves 106-111)In recent years, studies have shown that 80-85% of e-mails sent were spam. Another form of spam that has just surfaced is VoIP (Voice over Internet Telephony) spam. Currently, VoIP has seen an increasing numbers of users due to the cheap rates. With the introduction of the IMS (IP Multimedia Subsystem), the number of VoIP users are expected to increase dramatically. This calls for a cause of concern, as the tools and methods that have been used for blocking email spam may not be suitable for real-time voice calls. In addition, VoIP phones will have URI type addresses, so the same methods that were used to generate automated e-mail spam messages can be employed for unsolicited voice calls. Spammers will always be present to take advantage of and adapt to trends in communication technology. Therefore, it is important that IMS have structures in place to alleviate the problems of spam. Recent solutions proposed to block SPIT (Spam over Internet Telephony) have the following shortcomings: restricting the users to trusted senders, causing delays in voice call set-up, reducing the efficiency of the system by increasing burden on proxies which have to do some form of bayesian or statistical filtering, and requiring dramatic changes in the protocols being used. The proposed decoying system for the IMS fits well with the existing protocol structure, and customers are oblivious of its operation

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    Information Leakage Attacks and Countermeasures

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    The scientific community has been consistently working on the pervasive problem of information leakage, uncovering numerous attack vectors, and proposing various countermeasures. Despite these efforts, leakage incidents remain prevalent, as the complexity of systems and protocols increases, and sophisticated modeling methods become more accessible to adversaries. This work studies how information leakages manifest in and impact interconnected systems and their users. We first focus on online communications and investigate leakages in the Transport Layer Security protocol (TLS). Using modern machine learning models, we show that an eavesdropping adversary can efficiently exploit meta-information (e.g., packet size) not protected by the TLS’ encryption to launch fingerprinting attacks at an unprecedented scale even under non-optimal conditions. We then turn our attention to ultrasonic communications, and discuss their security shortcomings and how adversaries could exploit them to compromise anonymity network users (even though they aim to offer a greater level of privacy compared to TLS). Following up on these, we delve into physical layer leakages that concern a wide array of (networked) systems such as servers, embedded nodes, Tor relays, and hardware cryptocurrency wallets. We revisit location-based side-channel attacks and develop an exploitation neural network. Our model demonstrates the capabilities of a modern adversary but also presents an inexpensive tool to be used by auditors for detecting such leakages early on during the development cycle. Subsequently, we investigate techniques that further minimize the impact of leakages found in production components. Our proposed system design distributes both the custody of secrets and the cryptographic operation execution across several components, thus making the exploitation of leaks difficult

    Determinants of quality, latency, and amount of Stack Overflow answers about recent Android APIs.

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    Stack Overflow is a popular crowdsourced question and answer website for programming-related issues. It is an invaluable resource for software developers; on average, questions posted there get answered in minutes to an hour. Questions about well established topics, e.g., the coercion operator in C++, or the difference between canonical and class names in Java, get asked often in one form or another, and answered very quickly. On the other hand, questions on previously unseen or niche topics take a while to get a good answer. This is particularly the case with questions about current updates to or the introduction of new application programming interfaces (APIs). In a hyper-competitive online market, getting good answers to current programming questions sooner could increase the chances of an app getting released and used. So, can developers anyhow, e.g., hasten the speed to good answers to questions about new APIs? Here, we empirically study Stack Overflow questions pertaining to new Android APIs and their associated answers. We contrast the interest in these questions, their answer quality, and timeliness of their answers to questions about old APIs. We find that Stack Overflow answerers in general prioritize with respect to currentness: questions about new APIs do get more answers, but good quality answers take longer. We also find that incentives in terms of question bounties, if used appropriately, can significantly shorten the time and increase answer quality. Interestingly, no operationalization of bounty amount shows significance in our models. In practice, our findings confirm the value of bounties in enhancing expert participation. In addition, they show that the Stack Overflow style of crowdsourcing, for all its glory in providing answers about established programming knowledge, is less effective with new API questions

    Cloudarmor: Supporting Reputation-Based Trust Management for Cloud Services

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    Cloud services have become predominant in the current technological era. For the rich set of features provided by cloud services, consumers want to access the services while protecting their privacy. In this kind of environment, protection of cloud services will become a significant problem. So, research has started for a system, which lets the users access cloud services without losing the privacy of their data. Trust management and identity model makes sense in this case. The identity model maintains the authentication and authorization of the components involved in the system and trust-based model provides us with a dynamic way of identifying issues and attacks with the system and take appropriate actions. Further, a trust management-based system provides us with a new set of challenges such as reputation-based attacks, availability of components, and misleading trust feedbacks. Collusion attacks and Sybil attacks form a significant part of these challenges. This paper aims to solve the above problems in a trust management-based model by introducing a credibility model on top of a new trust management model, which addresses these use-cases, and also provides reliability and availability

    Scheduling methods for distributed Twitter crawling

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    Tese de Mestrado Integrado. Engenharia Informåtica e Computação. Faculdade de Engenharia. Universidade do Porto. 201

    Reverse Engineering and Testing of Rich Internet Applications

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    The World Wide Web experiences a continuous and constant evolution, where new initiatives, standards, approaches and technologies are continuously proposed for developing more effective and higher quality Web applications. To satisfy the growing request of the market for Web applications, new technologies, frameworks, tools and environments that allow to develop Web and mobile applications with the least effort and in very short time have been introduced in the last years. These new technologies have made possible the dawn of a new generation of Web applications, named Rich Internet Applications (RIAs), that offer greater usability and interactivity than traditional ones. This evolution has been accompanied by some drawbacks that are mostly due to the lack of applying well-known software engineering practices and approaches. As a consequence, new research questions and challenges have emerged in the field of web and mobile applications maintenance and testing. The research activity described in this thesis has addressed some of these topics with the specific aim of proposing new and effective solutions to the problems of modelling, reverse engineering, comprehending, re-documenting and testing existing RIAs. Due to the growing relevance of mobile applications in the renewed Web scenarios, the problem of testing mobile applications developed for the Android operating system has been addressed too, in an attempt of exploring and proposing new techniques of testing automation for these type of applications

    Test Generation and Dependency Analysis for Web Applications

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    In web application testing existing model based web test generators derive test paths from a navigation model of the web application, completed with either manually or randomly generated inputs. Test paths extraction and input generation are handled separately, ignoring the fact that generating inputs for test paths is difficult or even impossible if such paths are infeasible. In this thesis, we propose three directions to mitigate the path infeasibility problem. The first direction uses a search based approach defining novel set of genetic operators that support the joint generation of test inputs and feasible test paths. Results show that such search based approach can achieve higher level of model coverage than existing approaches. Secondly, we propose a novel web test generation algorithm that pre-selects the most promising candidate test cases based on their diversity from previously generated tests. Results of our empirical evaluation show that promoting diversity is beneficial not only to a thorough exploration of the web application behaviours, but also to the feasibility of automatically generated test cases. Moreover, the diversity based approach achieves higher coverage of the navigation model significantly faster than crawling based and search based approaches. The third approach we propose uses a web crawler as a test generator. As such, the generated tests are concrete, hence their navigations among the web application states are feasible by construction. However, the crawling trace cannot be easily turned into a minimal test suite that achieves the same coverage due to test dependencies. Indeed, test dependencies are undesirable in the context of regression testing, preventing the adoption of testing optimization techniques that assume tests to be independent. In this thesis, we propose the first approach to detect test dependencies in a given web test suite by leveraging the information available both in the web test code and on the client side of the web application. Results of our empirical validation show that our approach can effectively and efficiently detect test dependencies and it enables dependency aware formulations of test parallelization and test minimization
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