Mohammed Alzaabi

Using Cloud Computing to Implement a Security Overlay Network

This article proposes and analyzes a general cloud-based security overlay network that can be used as a transparent overlay network to provide services such as intrusion detection systems, antivirus and antispam software, and distributed denial-of-service prevention. The authors analyze each of these in-cloud security services in terms of resiliency, effectiveness, performance, flexibility, control, and cost.

Ensuring Anonymity for LBSs in Smartphone Environment

With the rapid growth of GPS-enable Smartphones, the interest on using Location Based Services (LBSs) has increased significantly. The evolution in the functionalities provided by those smartphones has enabled them to accurately pinpoint the location of a user. Because location information is what all LBSs depend on to process users request, it should be properly protected from attackers or malicious service providers (SP). Additionally, maintaining users privacy and confidentiality are imperative challenges to be overcome. A possible solution for these challenges is to provide user anonymity, which means to ensure that a user initiating a request to the SP should be indistinguishable from a group of people by any adversary who had access to the request. Most of the proposals that maintain users anonymity are based on location obfuscation. It mainly focuses on adjusting the resolution of the users location information. In this paper, we present a new protocol that is focused on using cryptographic techniques to provide anonymity for LBSs users in the smartphone environment. This protocol makes use of a trusted third party called the Anonymity Server (AS) that ensures anonymous communication between the user and the service provider. Keywords—Location Based Services, Anonymity, Location Information The massive evolution in wireless communications and the dramatic increase in the usage of smartphones have facilitated a greater ability to access mobile networks and their services. Be- cause smartphones are easy to carry and available while the users are moving around, accessing network services has become easier and ubiquitous. At the same time, Location Information (LI) introduced a new and highly personalized class of applications and services. The availability of such functionality along with the ability to uni- quely identify smartphones, enabled service providers to provide services based on their location removing the time and location constrains that are associated with providing services to custom- ers. Information services that make use of the location of users by either utilizing satellites or mo- bile network cells, with the intention of providing services that are customized to their precise geographical area are called Location Based Services (LBSs). LBSs are usually accessible by mobile devices such as Smartphones, Personal Digital Assistants (PDAs) and mobile phones. There are varieties of LBS applications that include emergency services, point of interest search, ※ This research was supported by Ministry of Land, Transport and Maritime Affairs of Korean gorernment (Grant 36- 2007-CAirport)

CISRI: A Crime Investigation System Using the Relative Importance of Information Spreaders in Networks Depicting Criminals Communications

In this paper, we propose a forensic analysis system called crime investigation system using the relative importance (CISRI) that helps forensic investigators determine the most influential members of a criminal group, who are related to known members of the group, for the purposes of investigation. In the CISRI framework, we describe the structural relationships between the members of a criminal group in terms of a graph. In such a graph, a node represents a member of a criminal group, an edge connecting two nodes represents the relationship between two members of the group, and the weight of an edge represents the degree of the relationship between those two members. Using this representation, we propose a method that determines the relative importance of nodes in a graph with respect to a given set of query nodes. Most current approaches that study relative importance determine the relative importance of a node under consideration by estimating the contribution of each query node individually to the importance of this node while overlooking the contribution of the query nodes collectively to the importance of the node under consideration. This may lead to results with low precision. CISRI overcomes this limitation by: 1) computing the contribution of the overall set of query nodes to the importance of a node under consideration and 2) adopting a tight constraint calculation that considers how much each query node contributes to the relative importance of a node under consideration. This leads to accurate identification of nodes in the graph that are important, in relation to the query nodes. In the framework of CISRI, a graph is constructed from mobile communication records (e.g., phone calls and messages), where a node represents a caller and the weight of an edge reflects the number of contacts between two callers. We evaluated the quality of CISRI by comparing it experimentally with three comparable methods. Our results showed marked improvement.

The Use of Ontologies in Forensic Analysis of Smartphone Content

Digital forensics investigators face a constant challenge in keeping track with evolving technologies such as smartphones. Analyzing the contents of these devices to infer useful information is becoming more time consuming as the volume and complexity of data are increasing. Typically, such analysis is undertaken by a human, which makes it dependent on the experience of the investigator. To overcome such impediments, an automated technique can be utilized in order to aid the investigator to quickly and eciently analyze the data. In this paper, we propose F-DOS; a set of ontologies that models the smartphone content for the purpose of forensic analysis. F-DOS can form a knowledge management component in a forensic analysis system. Its importance lies in its ability to encode the semantics of the smartphone content using concepts and their relationships that are modeled by F-DOS.

On the fly generation of mobile learning structured multimedia content from the web

This paper presents a mobile learning system that makes use of available multimedia web resources to manage the authoring and delivery of learning material for nomadic users. The system constructs in real time a personalized learning web for a mobile user who enquires about a particular topic to fit his/her curiosity while facing a real-life situation. The learning web is mapped from a hierarchical structure that is automatically generated based on information gathered from a specific location in the web. The learning content is packaged into preset layouts and presented to the user based on his/her profile and the capabilities of the mobile handset. The architecture of the system is web-based which is designed as a set of modules that i) gather multimedia information from different locations in the web, ii) package the content into lightweight learning objects (LO), iii) organize LOs into a learning web structure, and finally iv) deliver the whole to the user allowing him/her to navigate through the learning web according to his/her needs and constraints.

Ontology-based forensic analysis of mobile devices

A critical part of investigating any digital device in digital forensics is the analysis phase. The analysis phase has been known to be a time-intensive process. The time required to analyze the data is mainly influenced by the volume of storage capacity as well as the complexity of data under investigation. Given that these two factors are at constant growth rates, the need for advanced forensic methods and tools to address these issues becomes crucial. The main contribution of this research is to design and develop a new framework which will assist the investigator to automatically analyze the content of a mobile device with a minimum human interaction. The adopted approach utilizes Ontologies as a form of knowledge representation for the mobile device domain. These Ontologies define fundamental concepts in that domain and the relations between them. By organizing the evidence objects that are extracted from mobile devices in such a model, a network of interconnected evidence objects is formed which will enhance the process of analyzing data and locating relevant evidence to the investigation.