A hybrid association rule mining approach for characterizing network traffic behaviour

Understanding network traffic behaviour is crucial for managing and securing computer networks. One important technique is to mine frequent patterns or association rules from analysed traffic data. On the one hand, association rule mining usually generates a huge number of patterns and rules, many of them meaningless or user‐unwanted; on the other hand, association rule mining can miss some necessary knowledge if it does not consider the hierarchy relationships in the network traffic data. Aiming to address such issues, this paper proposes a hybrid association rule mining method for characterizing network traffic behaviour. Rather than frequent patterns, the proposed method generates non‐similar closed frequent patterns from network traffic data, which can significantly reduce the number of patterns. This method also proposes to derive new attributes from the original data to discover novel knowledge according to hierarchy relationships in network traffic data and user interests. Experiments performed on real network traffic data show that the proposed method is promising and can be used in real applications. Copyright © 2013 John Wiley & Sons, Ltd.     

Efficient mobility prediction scheme for pervasive networks

This paper aims towards probabilistic reasoning and Bayesian‐based recommendations to predict the next movement of a person. The proposed model in this work observes the behavior and movement patterns of humans for a day both at home and at their office to predict their future activities. To achieve this, an efficient model has been designed that provides the probable context‐based location of a person and predicts his next movement based on his behavior on some particular day at a particular time. The proposed model allows ubiquitous services to adapt to uncertain situations in today's world using different mechanisms such as monitoring the human behavior patterns and evaluating the user preferences and profiles. A case study of the office activity chart has been provided, and based on the experimentation performed on the related events, the probability in evaluating some “N”chained events of a person in a consecutive order using the proposed model has been found to be 0.002, which infers that there are fewer chances that the person will perform the same particular sequence of events.     

Hierarchical location service for wireless sensor networks with mobile sinks

In wireless sensor networks (WSNs), a mobile sink can help eliminate the hotspot effect in the vicinity of the sink, which can balance the traffic load in the network and thus improve the network performance. Location‐based routing is an effective routing paradigm for supporting sink mobility in WSNs with mobile sinks (mWSNs). To support efficient location‐based routing, scalable location service must be provided to advertise the location information of mobile sinks in an mWSN. In this paper, we propose a new hierarchical location service for supporting location‐based routing in mWSNs. The proposed location service divides an mWSN into a grid structure and exploits the characteristics of static sensors and mobile sinks in selecting location servers. It can build, maintain, and update the grid‐spaced network structure via a simple hashing function. To reduce the location update cost, a hierarchy structure is built by choosing a subset of location servers in the network to store the location information of mobile sinks. The simulation results show that the proposed location service can significantly reduce the communication overhead caused by sink mobility while maintaining high routing performance, and scales well in terms of network size and sink number. Copyright © 2009 John Wiley & Sons, Ltd.     

基于运动趋势的移动对象位置预测

提出一种基于运动趋势的移动对象位置预测算法,不仅借鉴马尔可夫模型思想对移动对象的历史活动轨迹进行建模,而且将对象的运动趋势作为位置预测的重要因素。以全体历史停留区域作为未来位置的候选,根据位置的特征,将结果分为预测位置和推荐位置。真实数据实验表明,算法在保证较高时间效率的同时,预测精度较同类算法提高近10%。     

Performance of dead reckoning‐based location service for mobile ad hoc networks

A predictive model‐based mobility tracking method, called dead reckoning, is developed for mobile ad hoc networks. It disseminates both location and movement models of mobile nodes in the network so that every node is able to predict or track the movement of every other node with a very low overhead. The basic technique is optimized to use ‘distance effect’, where distant nodes maintain less accurate tracking information to save overheads. The dead reckoning‐based location service mechanism is evaluated against three known location dissemination service protocols: simple, distance routing effect algorithm for mobility (DREAM) and geographic region summary service (GRSS). The evaluation is done with geographic routing as an application. It is observed that dead reckoning significantly outperforms the other protocols in terms of packet delivery fraction. It also maintains low‐control overhead. Its packet delivery performance is only marginally impacted by increasing speed or noise in the mobility model, that affects its predictive ability. Copyright © 2004 John Wiley & Sons, Ltd.     

固定单站对运动目标的无源定位

单站无源定位技术具有隐蔽性强、设备量小及系统相对独立等优点,有着较强的实用价值.以往人们对运动单站无源定位技术研究较多,而对固定单站无源定位技术研究相对较少.针对此种情况,文章对固定单站对运动目标的无源定位技术的基本原理进行了分析,并提出了多普勒变化率、到达角变化率等定位参数的测量方法.     

基于UCON的空间访问控制模型的研究

虽然UCON模型包含了传统访问控制、信任管理、DRM三个问题领域,是下一代访问控制技术的发展方向,但是它不能解决空间数据库系统和基于移动用户位置的信息服务系统中空间动态授权。本文将空间授权规则引入到UCON模型中,提出了一个支持空间特性的面向使用的访问控制模型GEO—UCON,并给出了在空间环境下的授权规则,扩展了传统的UCON模型的空间安全描述能力。     

Web挖掘中基于RD_Apriori算法发现用户频繁访问模式

从Web日志数据中发现用户的频繁访问模式，可分为两步进行。首先把经过预处理后的目志数据转换为最大前向引用的集合，然后使用Apriori算法挖掘出频繁访问模式。本文针对挖掘的第二步提出了一种基于缩减数据库(Reduced Database)的RD—Apriori算法，此算法能够准确、高效地挖掘各种长度不同的频繁访问模式。     

低轨卫星系统中结合时间和移动的位置更新策略

低轨(LEO)卫星快速运动,移动终端(MT)相对于卫星的位置信息也在不断变化,如何有效地管理MT的位置信息,减小位置更新频率和寻呼开销是研究位置管理的主要目的。为此,提出一种低轨卫星系统中的动态位置管理策略,基于时间和移动相结合进行位置更新,在不增加寻呼开销的条件下,减小了位置更新频率,从而有效降低了位置管理的总开销。     

Delay‐aware privacy‐preserving location‐based services under spatiotemporal constraints

The ubiquitous use of location‐based services (LBS) through smart devices produces massive amounts of location data. An attacker, with an access to such data, can reveal sensitive information about users. In this paper, we study location inference attacks based on the probability distribution of historical location data, travel time information between locations using knowledge of a map, and short and long‐term observation of privacy‐preserving queries. We show that existing privacy‐preserving approaches are vulnerable to such attacks. In this context, we propose a novel location privacy‐preserving approach, called KLAP, based on the three fundamental obfuscation requirements: minimum k ‐locations, l ‐diversity, and privacy a rea p reservation. KLAP adopts a personalized privacy preference for sporadic, frequent, and continuous LBS use cases. Specifically, it generates a secure concealing region (CR) to obfuscate the user's location and directs that CR to the service provider. The main contribution of this work is twofold. First, a CR pruning technique is devised to establish a balance between privacy and delay in LBS usage. Second, a new attack model called a long‐term obfuscated location tracking attack, and its countermeasure is proposed and evaluated both theoretically and empirically. We assess KLAP with two real‐world datasets. Experimental results show that it can achieve better privacy, reduced delay, and lower communication costs than existing state‐of‐the‐art methods.     

A distributed database architecture for global roaming in next-generation mobile networks

The next-generation mobile network will support terminal mobility, personal mobility, and service provider portability, making global roaming seamless. A location-independent personal telecommunication number (PTN) scheme is conducive to implementing such a global mobile system. However, the nongeographic PTNs coupled with the anticipated large number of mobile users in future mobile networks may introduce very large centralized databases. This necessitates research into the design and performance of high-throughput database technologies used in mobile systems to ensure that future systems will be able to carry efficiently the anticipated loads. This paper proposes a scalable, robust, efficient location database architecture based on the location-independent PTNs. The proposed multitree database architecture consists of a number of database subsystems, each of which is a three-level tree structure and is connected to the others only through its root. By exploiting the localized nature of calling and mobility patterns, the proposed architecture effectively reduces the database loads as well as the signaling traffic incurred by the location registration and call delivery procedures. In addition, two memory-resident database indices, memory-resident direct file and T-tree, are proposed for the location databases to further improve their throughput. Analysis model and numerical results are presented to evaluate the efficiency of the proposed database architecture. Results have revealed that the proposed database architecture for location management can effectively support the anticipated high user density in the future mobile networks.     

A class of mobile motion prediction algorithms for wireless mobile computing and communications

This paper describes a class of novel mobile motion prediction algorithms for supporting global mobile data accessing. Traditionally, mobility and routing management includes functions to passively keep track of the location of the users/terminals and to maintain connections to the terminals belonging to the system. To maintain uninterrupted high-quality service for distributed applications, it is important that a mobile system be more intelligent and can anticipate the change of the location of its user. We propose an aggressive mobility and routing management scheme, called predictive mobility management. A class of mobile motion prediction algorithms predicts the future location of a mobile user according to the user's movement history, i.e., previous movement patterns. By combining this scheme with mobility agent functions, the service and user routing data are actually pre-connected and pre-assigned at the locations to which the user is moving. Thus, the user can immediately receive service or data with virtually the same efficiency as at the previous location, i.e., without encountering a large data structure handover delay before service or data is available.     

Hybrid Scheme with Adaptive Replication and Mobility Anchoring Point (MAP) in Wireless Networks

Replication strategy is mostly useful for replicating the mobile user’s profile at selected locations from which some callers have higher calling rate. Location management scheme also include replication strategy to reduce the location lookup cost of called mobile user. It plays important role in personal communication services in order to reduce call setup cost, call setup time, and increases the QoS (quality of service). In prior replication schemes, called user’s location profile is placed at some fixed and limited number of visitor location registers (VLRs) based on call history of the caller. In prior hybrid schemes location update and replication strategies are combined together. These prior hybrid schemes apply pointer forwarding strategy and replication. But these schemes have limitations like holding “loose” form of location profile and higher location update cost. We have proposed a new hybrid scheme which includes adaptive replication of updated user’s location profile and mobility anchoring point (MAP) for location update. The main objective of the proposed scheme is to reduce call setup cost and call setup time. In order to achieve the objective, adaptive replication is applied at certain visitor location registers (VLRs) according to movement of caller. The replica is kept updated at MAP and replicated to neighbor VLRs as per movement of the caller. We have presented fluid-flow based analytical modeling which shows that proposed scheme outperforms the prior hybrid scheme.     

Evaluation and protection of multi-level location privacy based on an information theoretic approach

A privacy metric based on mutual information was proposed to measure the privacy leakage occurred when location data owner trust data users at different levels and need to publish the distorted location data to each user according to her trust level,based on which an location privacy protection mechanism (LPPM)was generated to protect user’s location privacy.In addition,based on mutual information,a metric was proposed to measure the privacy leakage caused by attackers obtaining different levels of distorted location data and then performing inference attack on the original location data more accurately.Another privacy metric was also proposed to quantify the information leakage occurred in the scenario based on mutual information.In particular,the proposed privacy mechanism was designed by modifying Blahut-Arimoto algorithm in rate-distortion theory.Experimental results show the superiority of the proposed LPPM over an existing LPPM in terms of location privacyutility tradeoff in both scenarios,which is more conspicuous when there are highly popular locations.     

Trajectory privacy protection method based on location obfuscation

In the process of continuous queries,a method of trajectory privacy protection based on location obfuscation was proposed to solve the problem that K-anonymity was difficult to guarantee user privacy in third party architectrue.Firstly,the (G-1) query obfuscation locations through the location prediction was obtained and the dummy location selection mechanism,and then sent them together with the user’s real query location to different anonymizers to form cloaking regions and sent them to the LBS server for queries,and the query results were returned to the user by different anonymizers.In this method,the user’s real query location was confused by the location obfuscation,and the attacker couldn’t deduce the user’s trajectory from a single anonymizer or the LBS server.The method can enhance the privacy of the user’s trajectory and can effectively solve the performance bottleneck in the single anonymizer structure.Security analysis shows the security of the proposed approach,and experiments show this method can reduce the number of interactions between the user and the LBS server and the overhead of the single anonymizer.     

Efficient paging and multicast schemes for Mobile Virtual Private Networks

The issue of providing a mobile virtual private network (MVPN) service by a cellular network is addressed in this study. The main focus of this study is on two aspects of MVPN handling: a multicast transmission, and location management of the MVPN members. Virtual private networks (VPNs) already exist in wired networks. The growing number of mobile users increases the demand for mobile services. It is expected that future wireless networks will have to provide wireless internet services, and in particular, to support MVPNs. In order to maintain an MVPN service offering, the system must support an efficient information delivery to the MVPN members. In order to achieve this goal, the physical locations of the MVPN members must be known to the system. In this study, we present methods to efficiently route and transmit information to the MVPN members, without affecting the quality of the personal service provided to each and every MVPN member. It is shown that the wireless MVPN bandwidth requirement is significantly less than the equivalent bandwidth required by a wired VPN. The offered bandwidth utilization is significantly better than the efficiency of IP‐based multicast transmission in the Internet, and the proposed IP‐based multicast transmission in cellular networks. Copyright © 2005 John Wiley & Sons, Ltd.     

基于敏感位置多样性的LBS位置隐私保护方法研究

针对LBS查询服务中构造的匿名框或选取的锚点仍位于敏感区域而导致的位置隐私泄漏问题,提出了基于敏感位置多样性的锚点选取算法。该算法根据用户访问数量和访问高峰时段,对不同敏感位置进行定义和筛选,选择具有相似特征的其他敏感位置构成多样性区域,并以该区域形心作为查询锚点,提高用户在敏感位置出现的多样性。以该锚点为查询标志,提出一种均衡增量近邻兴趣点查询算法HINN,在无需用户提供真实位置坐标的条件下实现K近邻兴趣点查询,同时改进了SpaceTwist方法中存在的查询兴趣点围绕锚点分布的缺陷,提高了查询准确度。实验表明,本方法实现了用户在敏感区域停留时的位置隐私保护目标,同时具有良好的兴趣点查询质量和较低的通信开销。     

Adaptive region-based location management for PCS systems

The personal communications services (PCSs) systems can provide ubiquitous and customized services. The key issue, which affects the performance of the whole system, is the location management. We propose a region-based location strategy by taking advantage of the user's movement behavior to improve the performance of the conventional systems. Each mobile user is associated with a set of regions, which are derived from the user's movement patterns. The registration processes in the same region can be eliminated such that the cost of location management can be significantly reduced. Several design issues are studied by considering the workload balance and the call-to-mobility ratio for a user. The proposed strategy can be dynamically adjusted based on different system parameters and user behavior. A performance analysis on the signaling cost and the database access cost is given to justify the benefits of this approach