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RSS feed of ComSoc Technology NewsMonitoring and detecting abnormal behavior in mobile cloud infrastructure
CTN Issue: August 2012
Mobile Cloud Computing (MCC) is an emerging technology that leverages the benefits of cloud computing to enhance mobile computing capability. This paper discusses an example MCC service, in which mobile operating systems (OS) are virtualized in cloud infrastructure as mobile instances. These virtual mobile instances can run the same mobile applications as those supported by their counterparts on physical mobile devices. Unfortunately, security is one of the major barriers to the adoption of MCC in the real world. In this paper, how to identify and defeat security threats in MCC is described, and a behavior-based abnormal detection methodology of monitoring both virtual hosts and network data is proposed. Network Operations and Management Symposium 2012Towards Ubiquitous Mobility Solutions for Body Sensor Networks on HealthCare
CTN Issue: July 2012
The use of electronic health (eHealth) technologies in healthcare improves the quality of health services furnished to patients. Body sensor networks (BSNs) are a type of wireless sensor networks aimed to be deployed on persons in order to collect physiological parameters for healthcare monitoring purposes. BSNs need to operate every time and everywhere to transmit these important parameters to healthcare providers or automatic systems to detect any anomaly in the patient health status. It is mandatory to provide mobility support for the BSN so it can always be connected to some gateway to the Internet and therefore to back-end health providers. This article overviews available handover mechanisms used for wireless sensors mobility and proposes a new ubiquitous mobility approach for BSNs in healthcare. IEEE Communications MagazineCharacterization of ISP Traffic: Trends, User Habits, and Access Technology Impact
CTN Issue: June 2012
In the recent years, the research community has increased its focus on network monitoring which is seen as a key tool to understand the Internet and the Internet users. Several studies have presented a deep characterization of a particular application, or a particular network, considering the point of view of either the ISP, or the Internet user. In this paper, we take a different perspective. We focus on three European countries where we have been collecting traffic for more than a year and a half through 5 vantage points with different access technologies. This humongous amount of information allows us not only to provide precise, multiple, and quantitative measurements of "What the user do with the Internet" in each country but also to identify common/uncommon patterns and habits across different countries and nations. Considering different time scales, we start presenting the trend of application popularity; then we focus our attention to a one-month long period, and further drill into a typical daily characterization of users activity. Results depict an evolving scenario due to the consolidation of new services as Video Streaming and File Hosting and to the adoption of new P2P technologies. Despite the heterogeneity of the users, some common tendencies emerge that can be leveraged by the ISPs to improve their service. IEEE Transactions on Network and Service ManagementAutonomic Parameter Tuning of Anomaly-Based IDSs: an SSH Case Study
CTN Issue: June 2012
Anomaly-based intrusion detection systems classify network traffic instances by comparing them with a model of the normal network behavior. To be effective, such systems are expected to precisely detect intrusions (high true positive rate) while limiting the number of false alarms (low false positive rate). However, there exists a natural trade-off between detecting all anomalies (at the expense of raising alarms too often), and missing anomalies (but not issuing any false alarms). The parameters of a detection system play a central role in this trade-off, since they determine how responsive the system is to an intrusion attempt. Despite the importance of properly tuning the system parameters, the literature has put little emphasis on the topic, and the task of adjusting such parameters is usually left to the expertise of the system manager or expert IT personnel. In this paper, we present an autonomic approach for tuning the parameters of anomaly-based intrusion detection systems in case of SSH traffic. We propose a procedure that aims to automatically tune the system parameters and, by doing so, to optimize the system performance. We validate our approach by testing it on a flow-based probabilistic detection system for the detection of SSH attacks. IEEE Transactions on Network and Service ManagementLeveraging Local Image Redundancy for Efficient Virtual Machine Provisioning
CTN Issue: May 2012
Image-based provisioning provides a fast and reliable mechanism for handling the demands of Cloud Computing. Typically, a Cloud data center contains a catalog of images in the image library, multiple hypervisors with inexpensive direct attached storage (where the instances are created), and a placement mechanism that allocates and reserves resources. Image-based provisioning is a deployment and activation mechanism that clones a “golden” read-only virtual machine (VM) image residing in the image library to create a new virtual machine instance on a hypervisor. The main steps of the provisioning process are: 1) selection of hypervisor based on a placement policy; 2) copying VM image from a storage server to the direct attached storage of the hypervisor, and 3) image activation to create an instance. The image copy from the storage server to the direct attached storage of the hypervisor is time consuming and network intensive, directly contributing to user perceived provisioning latency. Network Operations and Management Symposium 2012
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