天巡收购移动APP开发公司Distinction

全球旅游搜索企业天巡(Skyscanner)收购了移动APP开发公司Distinction,此举将为天巡增添30名移动应用设计和开发人才,助力其全球旅游APP战略。Distinction团队拥有丰富的多平台APP开发经验。

本文讲的是天巡收购移动APP开发公司Distinction,近日,全球领先旅游搜索企业天巡(Skyscanner)宣布成功收购位于布达佩斯的移动APP开发公司Distinction,通过收购来不断发展其全球旅游APP战略。

  此次收购将为天巡(Skyscanner)增添30名优秀的移动应用设计和开发人才,见证了天巡内部移动团队的快速发展。Distinction团队拥有丰富的多平台APP开发经验(如IOS、安卓和Windows),并荣获多项奖项。

  据悉,布达佩斯办公室将成为天巡主要的移动应用开发中心,现有Distinction团队将继续在布达佩斯办公室工作。同时,天巡新增创意团队也将加入,并促进天巡全球网点的移动端发展。

  天巡在过去的12个月里不断增加其APP的功能范围,在备受欢迎的多平台机票APP基础上,又增加了租车和酒店APP,这也让全球范围的旅行者都能随时随地,轻松制定出游计划。截至目前,天巡的APP累计下载量超过3,000万次,支持30多种语言。

  天巡和Distinction紧密合作设计并开发的酒店APP已于今年8月上线,并提供IOS和安卓版本。这款APP将帮助旅行者在全球数以万计的酒店中找到最优酒店,APP的设计以“读图”为核心,用户在使用过程中不需要离开搜索结果页面,就可以轻松浏览酒店的照片。

  天巡(Skyscanner)创始人兼CEO Gareth Williams表示:“移动将毫无争议地主导未来的在线旅游预订行业,越来越多的旅行者在路上制定计划,这种发展趋势只会越来越快。”

  Gareth Williams还表示“由Bálint Orosz 和Akos Kapui所领导的Distinction是我见到过的最好的移动开发团队。在这次酒店APP的设计合作中,我们也见证了他们对用户体验的关注。Distinction是一家拥有杰出企业文化的优秀公司,加入天巡(Skyscanner)后,他们将进一步聚焦为旅行者提供所需要的移动旅游支持。”

  Distinction联合创始人兼CEO Bálint Orosz表示:“四年前我们创立Distinction,我们的目标是鼓励人们实现其最大价值和潜能。过去的20个月里,我们团队迅速扩大,从7人增加到30人,我们致力于确保为每一个人提供能充分发挥所长的环境。天巡(Skyscanner)和我们结识已经超过3年,我们充分体会到大家的相同理念。”

  同时Bálint Orosz还表示:“这次收购为我们整个团队提供了极好的机会,此前我们和全球品牌的合作为我们积累了许多经验,作为天巡(Skyscanner)一员,我们将更进一步创造移动旅游的未来。从2011年起,我们就和天巡(Skyscanner)产品团队保持合作,我们很兴奋加入到如此优秀的组织,携手同行。

作者:李伟

来源:IT168

原文标题:天巡收购移动APP开发公司Distinction

DDoS Attacks: Evolution, Detection, Prevention, Reaction, and Tolerance discusses the evolution of distributed denial-of-service (DDoS) attacks, how to detect a DDoS attack when one is mounted, how to prevent such attacks from taking place, and how to react when a DDoS attack is in progress, with the goal of tolerating the attack. It introduces types and characteristics of DDoS attacks, reasons why such attacks are often successful, what aspects of the network infrastructure are usual targets, and methods used to launch attacks. The book elaborates upon the emerging botnet technology, current trends in the evolution and use of botnet technology, its role in facilitating the launching of DDoS attacks, and challenges in countering the role of botnets in the proliferation of DDoS attacks. It introduces statistical and machine learning methods applied in the detection and prevention of DDoS attacks in order to provide a clear understanding of the state of the art. It presents DDoS reaction and tolerance mechanisms with a view to studying their effectiveness in protecting network resources without compromising the quality of services. To practically understand how attackers plan and mount DDoS attacks, the authors discuss the development of a testbed that can be used to perform experiments such as attack launching, monitoring of network traffic, and detection of attacks, as well as for testing strategies for prevention, reaction, and mitigation. Finally, the authors address current issues and challenges that need to be overcome to provide even better defense against DDoS attacks. Table of Contents Chapter 1 - Introduction Chapter 2 - DDoS, Machine Learning, Measures Chapter 3 - Botnets: Trends and Challenges Chapter 4 - DDoS Detection Chapter 5 - DDoS Prevention Chapter 6 - DDoS Reaction and Tolerance Chapter 7 - Tools and Systems Chapter 8 - Conclusion and Research Challenges
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