A generic solution for unwanted traffic control through trust management

The Internet has dramatically changed our daily life. But it is also bogged down by unwanted traffic, which is malicious, harmful or unexpected for its receivers. In order to control the unwanted traffic over the Internet, especially the mobile Internet, in this paper, we propose a generic unwanted traffic control (UTC) solution through trust management. It can control unwanted traffic from its source to destinations in a personalized manner according to trust evaluation at a Global Trust Operator, traffic and behavior analysis at hosts and traffic observation in the Internet. Thus, it can conduct UTC by integrating distributed and centralized functions and supporting both defensive and offensive approaches. Simulation based evaluation shows that the solution is effective with regard to accuracy and efficiency for botnet intrusion and DDoS intrusion via reflectors. It is also robust against a number of malicious system attacks, such as hide evidence attack, bad mouthing attack, on-off attack, malicious attack by an Internet Service Provider and combinations of the above, playing in conjunction with traffic intrusions. Meanwhile, the solution can provide a personalized UTC based on unwanted traffic detection behaviors.     

基于行为识别和SVM的短信过滤方法研究

针对手机垃圾短息难以治理的现象,提出一种基于行为识别和SVM的短信过滤方法。综合行为识别和SVM的特点,从运营商短信业务支撑中心方面实施对垃圾短信的过滤,并对SVM方法进行了相关实验。实验表明,SVM方法在短信拦截过滤方面有着较好的效果。     

User bias in online trust systems: aligning the system designers’ intentions with the users’ expectations

The advent of social networks opened a myriad opportunities for merging the social character of trust with the technical possibilities offered by the Internet and its availability as a mobile service. While most of the computational trust models aim to detect trustworthy entities, much less attention is paid to how these models are perceived by the users who are the core of the system. This paper delves into the workings of online trust systems under user bias and analyses the user behaviour through biases defined by Prospect theory. By performing empirical study on an existing system, we are able to demonstrate that there is a huge discrepancy between the aim of implementation of the online trust models and the users’ perception of those models. Understanding of this relation by the system designers can reduce complexity and improve the user experience and the system performance. The results imply that the tendency of the users to exhibit cognitive biases is not only the cause, but also the effect from the trust system design. These results and the analysis are then used to propose to the system designers a methodology for user bias identification and mitigation in the form of a Choice architecture for trust systems.     

A multi-level approach to highly efficient recognition of Chinese spam short messages

The problem of spam short message (SMS) recognition involves many aspects of natural language processing. A good solution to solving the problem can not only improve the quality of people experiencing the mobile life, but also has a positive role on promoting the analysis of short text occurring in current mobile applications, such as Webchat and microblog. As spam SMSes have characteristics of sparsity, transformation and real-timedness, we propose three methods at different levels, i.e., recognition based on symbolic features, recognition based on text similarity, and recognition based on pattern matching. By combining these methods, we obtain a multi-level approach to spam SMS recognition. In order to enrich the pattern base to reduce manual labor and time, we propose a quasi-pattern learning method, which utilizes quasi-pattern matching results in the pattern matching process. The method can learn many interesting and new patterns from the SMS corpus. Finally, a comprehensive analysis indicates that our spam SMS recognition approach achieves a precision rate as high as 95.18%, and a recall rate of 95.51%.     

基于多用户垃圾短信数据的伪基站活动轨迹可视分析方法

由于传统短信服务（SMS）存在严重的安全漏洞,不法分子可通过伪基站发送大量垃圾短信和诈骗信息,严重干扰人们的日常生活,危及人们的财产安全,影响社会稳定。然而,现有的关于伪基站的分析方法不能很好地感知某个大区域内的伪基站分布态势,难以探索伪基站的活动规律,把握伪基站的运动轨迹。针对这一问题,提出基于多用户垃圾短信数据进行可视分析的方法。通过用户上报垃圾短信的时间、相对位置、内容等信息,来追溯伪基站的近似活动轨迹;并通过设计多种可视化视图,实现一个多视图组合的交互式可视分析系统。最后,采用ChinaVis2017挑战赛I的数据集进行实验和案例分析,验证了该方法的可行性和有效性。     

基于短信和自动语音查费系统设计与实现

随着移动通信资费方式的层出不穷,移动用户对于自身的话费信息也越来越关注。分析了各通信运营商现有查费系统的局限性,利用现有的两种比较成熟的技术SMS(短消息服务)和IVR(自动语音应答),设计了一种占用资源相对较少,同时又比较灵活、方便的话费查询系统,并且给出该系统的具体实现过程。     

构造移动P2P环境下的分布式信任模型

基于固定网络的信任模型缺乏对网络高度动态性的考虑,不能直接应用于移动P2P网络。本文利用节点的报文转发能力,提出了一种移动P2P环境下的分布式信任模型MobTrust。该模型通过分布式存储机制,将节点转发的评价数据备份于K桶中,扩充了评价数据的存储范围。同时,鉴于移动设备有限的计算能力,设计双反馈机制提高评价数据的可靠性,然后以轻量级的方式计算信任度。仿真结果表明,MobTrust能有效降低系统开销,并拥有较高的评价数据利用率和交易成功率。     

SMS安全通信系统的研究与实现

随着短信的发展和使用,越来越多的用户使用无线移动网络进行重要数据的传输。但是,在GSM网络中,短信是以明文形式进行传送,这就使得信息在传输过程中极易受到不法分子的各种攻击,因此,必须寻求一种可靠的传输策略。该文针对该问题提出了一个安全解决方案,提出了一种基于认证与加解密的通信架构,确保信息传递的安全性。该方案已在智能手机上得到实现与验证。     

基于复杂网络的垃圾短信过滤算法

对垃圾短信发送用户的识别和过滤具有十分重要的研究价值和社会意义. 随着新形式和内容的垃圾短信出现, 传统的关键字匹配和发送速度频率过滤方法无法有效地处理这一问题. 在对短信发送/接收网络形式化表达的基础上, 以真实短信发送和接收以及通话关系数据为例, 统计和分析了短信发送网络的网络特性. 进一步分析和挖掘了垃圾短信用户在网络上发送接收的异常模式和行为, 并以此提出了一个基于语音关联程度和短信回复比率的过滤算法(NASFA算法). 通过实验和分析表明, 本文的算法能够高效地识别垃圾短信发送用户, 同时能够有效地控制将正常用户误识别为垃圾短信用户的比率.     

Certification-based trust models in mobile ad hoc networks: A survey and taxonomy

A mobile ad hoc network is a wireless communication network which does not rely on a pre-existing infrastructure or any centralized management. Securing the exchanges in such network is compulsory to guarantee a widespread development of services for this kind of networks. The deployment of any security policy requires the definition of a trust model that defines who trusts who and how. There is a host of research efforts in trust models framework to securing mobile ad hoc networks. The majority of well-known approaches is based on public-key certificates, and gave birth to miscellaneous trust models ranging from centralized models to web-of-trust and distributed certificate authorities. In this paper, we survey and classify the existing trust models that are based on public-key certificates proposed for mobile ad hoc networks, and then we discuss and compare them with respect to some relevant criteria. Also, we have developed analysis and comparison among trust models using stochastic Petri nets in order to measure the performance of each one with what relates to the certification service availability.     

Examining WeChat users’ motivations,trust, attitudes,and positive word-of-mouth: Evidence from China

WeChat is a mobile instant text and voice messaging communication service and has become an important social media platform in China. The objectives of this article are to examine the effects of psychological motivations (entertainment, sociality, and information) and trust on WeChat users’ attitudes and to assess the influence of users’ attitudes and their trust on positive word-of-mouth. This study represents one of the few that empirically investigates WeChat users’ motives, attitudes, trust, and their associated behavior. The research model was tested using data randomly collected from the database of Sojump. The numbers of valid observations were 264. Structure equation modeling was employed to verify and validate the research model. The outcomes confirm the path effects showing that entertainment, sociality, information, and trust positively influence WeChat users’ attitudes and users’ trust and their attitudes significantly affect positive WOM. The research results provide insight into how WeChat can motivate users and build their trust to improve their attitudes which in turn will increase WeChat users’ willingness in making positive comments on products and services.     

Android platform-based individual privacy information protection system

With the popularity of mobile phones with Android platform, Android platform-based individual privacy information protection has been paid more attention to. In consideration of individual privacy information problem after mobile phones are lost, this paper tried to use SMS for remote control of mobile phones and providing comprehensive individual information protection method for users and completed a mobile terminal system with self-protection characteristics. This system is free from the support of the server and it can provide individual information protection for users by the most basic SMS function, which is an innovation of the system. Moreover, the protection mechanism of the redundancy process, trusted number mechanism and SIM card detection mechanism are the innovations of this system. Through functional tests and performance tests, the system could satisfy user functional and non-functional requirements, with stable operation and high task execution efficiency.     

基于K 近邻法及移动agent技术的垃圾邮件检测系统研究*

为了解决日益严重的垃圾邮件问题,设计了一个新型的基于K近邻法及移动agent技术的垃圾邮件检测系统。简单介绍了K近邻法及移动agent技术,详细阐述了基于K近邻法及移动agent技术的垃圾邮件检测系统的体系结构、工作流程和关键技术。实验结果表明,与同类系统相比,该系统执行速度提高了,对网络稳定性的要求比较低,能够有效阻止垃圾邮件的传播。     

P2P网络中一种可信访问控制模型

信任模型强调成员以及数据的可信性,通过对网络中的不端行为进行通告和限制,为用户能够更加合理地使用网络提供保证。提出了一个基于相似度加权推荐的全局信任模型（GSTrust）。在模型中,信任值的请求者使用推荐者和自己之间的节点评分行为相似度加权推荐意见,以节点评价行为的相似度加权其推荐度计算全局信任值,并提出了基于群组的激励机制作为信任模型的有效补充,仿真实验证明了模型的有效性。     

一种对等网络信任模型的改进

对等网络提供了一种开放的、自由进行文件交换的环境，但随着网络的飞速发展，恶意文件泛滥，搭便车现象严重，使得系统的稳定性和可用性受到了威胁。信任机制的建立将有助于解决这些问题。该文在分析了一种信任模型SELCUK的特点和不足基础上，提出了一种改进的信任模型SELCUK-I，通过对等网络协同工具应用表明，SELCUK-I信任模型具有更好的安全性和可用性。     

Spam Short Messages Detection via Mining Social Networks

Short message service(SMS) is now becoming an indispensable way of social communication,and the problem of mobile spam is getting increasingly serious.We propose a novel approach for spam messages detection.Instead of conventional methods that focus on keywords or flow rate filtering,our system is based on mining under a more robust structure:the social network constructed with SMS.Several features,including static features,dynamic features and graph features,are proposed for describing activities of nodes in the network in various ways.Experimental results operated on real dataset prove the validity of our approach.     

Disseminating trust information in wearable communities

This paper describes a framework for managing and distributing trust information in a community of mobile and wearable computer users. Trust information in the form of reputations are used to aid users during their social interactions with the rest of the community.     

移动P2P网络中的多粒度信任模型

移动P2P网络的应用越来越广泛,随之而来的是大量欺诈等恶意行为,使系统的有效性和可用性难以保证。现有模型大多针对固定网络,忽略了终端类型对节点信任值的影响,而且不能很好地解决节点在不同领域、不同方面的可信度计算问题。针对上述问题,利用聚类思想和时间因子的概念,提出一种多粒度信任模型MGT（Multiple Granularity Trust Model）,并给出基于该模型的资源选择协议的工作流程。分析结果表明,模型能够有效地抵御恶意节点的破坏,增强P2P网络的安全性。     

内容中心移动边缘网络用户移动感知缓存机制

为了提高内容中心移动边缘网络的缓存性能,提出了一种基于用户移动性感知和节点中心性度量的内容中心移动边缘网络缓存机制（user mobility-aware and node centrality based caching,简称UMANCC）.UMANCC机制利用边缘节点计算节点中心性、缓存空闲率以及小区内用户逗留时间.移动边缘网络控制器综合各边缘节点的信息,计算各边缘节点的重要性并进行排序,最后根据排序结果选择内容缓存节点.仿真实验结果表明：与传统缓存机制LCE及Prob相比,UMANCC有效减少用户获取内容的平均跳数高达15.9%,提高边缘节点缓存命中率至少13.7%,减少进入核心网流量高达32.1%,有效地提高了内容中心移动边缘网络的内容分发性能.