What to Do When the Worst Happens!

The last few weeks have been full of news that confirms the advice we’ve been presenting to readers of this column. The Love Bug virus was one example, it demonstrated the current pitiful state we find ourselves in when we have global electronic commerce, but only national and local laws dealing with criminal abuse of the systems. In the past few days we have two additional developments that show there is more cause for alarm.     

SpaDeS: Detecting spammers at the source network

Despite the large variety and wide adoption of different techniques to detect and filter unsolicited messages (spams), the total amount of such messages over the Internet remains very large. Some reports point out that around 80% of all emails are spams. As a consequence, significant amounts of network resources are still wasted as filtering strategies are usually performed only at the email destination server. Moreover, a considerable part of these unsolicited messages is sent by users who are unaware of their spamming activity and may thus inadvertently be classified as spammers. In this case, these oblivious users act as spambots, i.e., members of a spamming botnet. This paper proposes a new method for detecting spammers at the source network, whether they are individual malicious users or oblivious members of a spamming botnet. Our method, called SpaDeS, is based on a supervised classification technique and relies only on network-level metrics, thus not requiring inspection of message content. We evaluate SpaDeS using real datasets collected from a Brazilian broadband ISP. Our results show that our method is quite effective, correctly classifying the vast majority (87%) of the spammers while misclassifying only around 2% of the legitimate users.     

When elephants dance, mice watch out! [legal issues]

Bristol Technology develops software tools-in particular cross-platform tools that software developers use to port applications software to Unix from other operating system platforms. Bristol had an agreement with Microsoft to get access to technical information about the Win98 application interfaces (APIs), the means for causing applications software to interact with the operating system. According to Bristol, its Wind/U tool was making it too easy for developers to write Unix programs that could also run under NT. Microsoft therefore used pretexts to deny Bristol access to the updated APIs for Windows NT 5, the operating system that will follow Win98 (probably under the name Windows 2000). Microsoft denies that it is doing any more than trying to gain a fair price for the crown jewels of its intellectual property. Yes; Microsoft is demanding four times as high a fee for access to the source code needed to use the NT APIs, but NT code is worth much more than that for Win98 or Win95. The article focuses on the ensuing legal battle between Microsoft and Bristol Technology     

Collusion-aware detection of review spammers in location based social networks

World Wide Web - To ensure the quality of online review, more and more location-based social networks (LBSNs), like Yelp, have established the filtering systems to detect groups of review spammers....     

面向文化产品水军的多视角特征发现与识别

为解决现有电商水军特征模型对文化产品水军识别不足以及单一分类器识别精度不高的问题,提出面向文化产品水军的多视角特征表达与识别模型.根据文化产品具有丰富的语义性、严格的时效性以及网络交互性等3个特点,从内容、行为、属性3个视角提出了评论主题相似度、平均有用度、行为关联性、兴趣关联性、平均评价积极度和综合质量评价等特征.将...     

An empirical study of behavioral characteristics of spammers: Findings and implications

In this paper we present a detailed study of the behavioral characteristics of spammers based on a two-month email trace collected at a large US university campus network. We analyze the behavioral characteristics of spammers that are critical to spam control, including the distributions of message senders, spam and non-spam messages by spam ratios; the statistics of spam messages from different spammers; the spam arrival patterns across the IP address space; and the active duration of spammers, among others. In addition, we also formally confirm an informal observation that spammers may hijack network prefixes in sending spam messages, by correlating the arrivals of spam messages with the BGP route updates of the corresponding networks. In this paper we present the detailed results of the measurement study; in addition, we also discuss the implications of the findings for the (content-independent) anti-spam efforts.     

Practical detection of spammers and content promoters in online video sharing systems

A number of online video sharing systems, out of which YouTube is the most popular, provide features that allow users to post a video as a response to a discussion topic. These features open opportunities for users to introduce polluted content, or simply pollution, into the system. For instance, spammers may post an unrelated video as response to a popular one, aiming at increasing the likelihood of the response being viewed by a larger number of users. Moreover, content promoters may try to gain visibility to a specific video by posting a large number of (potentially unrelated) responses to boost the rank of the responded video, making it appear in the top lists maintained by the system. Content pollution may jeopardize the trust of users on the system, thus compromising its success in promoting social interactions. In spite of that, the available literature is very limited in providing a deep understanding of this problem. In this paper, we address the issue of detecting video spammers and promoters. Towards that end, we first manually build a test collection of real YouTube users, classifying them as spammers, promoters, and legitimate users. Using our test collection, we provide a characterization of content, individual, and social attributes that help distinguish each user class. We then investigate the feasibility of using supervised classification algorithms to automatically detect spammers and promoters, and assess their effectiveness in our test collection. While our classification approach succeeds at separating spammers and promoters from legitimate users, the high cost of manually labeling vast amounts of examples compromises its full potential in realistic scenarios. For this reason, we further propose an active learning approach that automatically chooses a set of examples to label, which is likely to provide the highest amount of information, drastically reducing the amount of required training data while maintaining comparable classification effectiveness.     

Cheep! Cheep!

Open Forum

Cheep! Cheep!     

察打型无人机攻击航迹控制算法研究

固定翼无人机自身携带激光制导导弹进行对地攻击,需要自身携带的光电转台稳定跟踪目标并进行激光照射,指引导弹命中目标。为满足光电转台稳定跟踪目标的角速度限制及导弹可发射的限制条件,设计一种新型的航迹控制算法。利用基于李雅普诺夫向量场的导航算法,实现无人机从盘旋搜索到发现目标后转入导弹可攻击区并实施攻击的自动航迹控制,并保证无人机在调整姿态的同时光电转台稳定跟踪目标。利用某察打型无人机进行飞行验证,结果证明设计的算法能够较好完成无人机的攻击航迹控制,保证导弹发射。     

你好！夏天

《A Little Bit Longer》 艺人：Jonas Brothersl 发行时间：2009年4月 经过几年的辗转腾挪．原本青涩的Jonas Brothers愈发成熟起来．短短一年时间就升级为立足国际舞台的超级组合!     

基于攻击意图的复合攻击预测方法研究

入侵检测系统仅能检测到攻击,但不能预测攻击者下一步的攻击.分析了基于攻击行为预测方法的不足,提出了一种基于攻击意图的复合攻击预测方法.该方法使用抽象的攻击意图表示复合攻击,采用扩展的有向图表达攻击意图间的逻辑关系,建立了攻击匹配的攻击意图框架,在复合攻击预测算法中引入了攻击检测度和攻击匹配度两个概念.最后,通过实验验证了该方法的有效性.