Saleh M. Basalamah

A Distributed Access Control Architecture for Cloud Computing

The large-scale, dynamic, and heterogeneous nature of cloud computing poses numerous security challenges. But the clouds main challenge is to provide a robust authorization mechanism that incorporates multitenancy and virtualization aspects of resources. The authors present a distributed architecture that incorporates principles from security management and software engineering and propose key requirements and a design model for the architecture.

A distributed cloud architecture for mobile multimedia services

Mobile cloud computing is emerging as a new paradigm for supporting a broad range of multimedia services. MCC alleviates the burden of storage and computation on mobile devices. In this article, we describe design requirements and an architecture for MCC. The novelty in this architecture is an integrated cloudlet and base station subsystem that can meet application-level quality of service requirements and allow mobile resource provisioning close to the user. We present a layered architecture for MCC that elucidates the required functions and protocols. We also propose a connection handoff mechanism among cloudlets and discuss related resource management challenges for MCC.

Multimedia interactive therapy environment for children having physical disabilities

In this paper, we present an interactive multimedia environment that can be used to effectively complement the role of a therapist in the process of rehabilitation for disabled children. We use Microsoft Kinect 3D depth sensing camera with the online Second Life virtual world to record rehabilitation exercises performed by a physiotherapist or a disabled child. The exercise session can be played synchronously in Second Life. The physical activities of the users are synchronized with their virtual counterparts in the Second Life. The exercises can be recorded as well and made available for downloading to facilitate offline playback. A disabled child can follow the exercise at home in the absence of the therapist, since the system can provide visual guidance for performing the exercise in the right manner. Using the proposed system, parents at home can also assist the disabled child in performing therapy sessions in the absence of a therapist. Following the suggestions of therapists, the developed prototype can track several gestures of children who have mobility problems. Using a single Kinect device, we can capture high resolution joint movement of the body, without the need for any complicated hardware set up. The initial joint-based angular measurements show promising potential of our prototype to be deployed in real physiotherapy sessions.

A Framework for Composition and Enforcement of Privacy-Aware and Context-Driven Authorization Mechanism for Multimedia Big Data

The proliferation of multimedia big data for dissemination and sharing of massive amounts of information raises important security and privacy concerns. One such concern is the composition and enforcement of privacy policies in order to securely manage access of multimedia big data. Several researchers have pointed out that for proper enforcement of privacy policies, the privacy requirements should be captured in access control systems. In this paper, we propose a hybrid approach where privacy requirements are captured in an access control system and present a framework for composition and enforcement of privacy policies. The focus is to allow a user, not a system or security administrator to compose conflict free policies for their online multimedia data. An additional requirement is that such a policy be context-aware. We also present a methodology for verifying the privacy policy in order to ensure correctness and logical consistency. The verification process is also used to ensure that sensitive security requirements are not violated when privacy rules are enforced. A prototype, named Intelligent Privacy Manager (iPM), has been implemented for sharing of multimedia big data in a secure and private manner.

Tornado: a distributed spatio-textual stream processing system

The widespread use of location-aware devices together with the increased popularity of micro-blogging applications (e.g., Twitter) led to the creation of large streams of spatio-textual data. In order to serve real-time applications, the processing of these large-scale spatio-textual streams needs to be distributed. However, existing distributed stream processing systems (e.g., Spark and Storm) are not optimized for spatial/textual content. In this demonstration, we introduce Tornado, a distributed in-memory spatio-textual stream processing server that extends Storm. To efficiently process spatio-textual streams, Tornado introduces a spatio-textual indexing layer to the architecture of Storm. The indexing layer is adaptive, i.e., dynamically re-distributes the processing across the system according to changes in the data distribution and/or query workload. In addition to keywords, higher-level textual concepts are identified and are semantically matched against spatio-textual queries. Tornado provides data deduplication and fusion to eliminate redundant textual data. We demonstrate a prototype of Tornado running against real Twitter streams, where the users can register continuous or snapshot spatio-textual queries using a map-assisted query-interface.

Modeling therapy rehabilitation sessions using non-invasive serious games

The use of non-invasive methods for detecting motion of the human body in three dimensions has become very popular in recent years due to commercial availability of economically priced 3D sensors. In this paper, we present a web-based interactive serious game interface that uses noninvasive methods to recognize the movements of the body. Our framework provides a mechanism that can engage disabled children in playing serious games while tracking, in the background, their movements in the 3D axes. Motion data of the subjects is collected through multiple sensors in a noninvasive manner. This information can be displayed on screen in a live manner or recorded for offline replaying and data analysis. The system incorporates an intelligent authoring tool that allows the therapist to design a therapy and assign it to a patient. The subject as well as other members of the Community of Interest such as therapists, parents and caregivers can view the results at any time and thus could follow up with patients progress.

Demonstration of Taghreed: A system for querying, analyzing, and visualizing geotagged microblogs

This paper demonstrates Taghreed; a full-fledged system for efficient and scalable querying, analyzing, and visualizing geotagged microblogs, such as tweets. Taghreed supports a wide variety of queries on all microblogs attributes. In addition, it is able to manage a large number (billions) of microblogs for relatively long periods, e.g., months. Taghreed consists of four main components: (1) indexer, (2) query engine, (3) recovery manager, and (4) visualizer. Taghreed indexer efficiently digests incoming microblogs with high arrival rates in light main-memory indexes. When the memory becomes full, the memory contents are flushed to disk indexes which are managing billions of microblogs efficiently. On memory failure, the recovery manager restores the memory contents from backup copies. Taghreed query engine consists of two modules: a query optimizer and a query processor. The query optimizer generates an optimized query plan to be executed by the query processor to provide low query responses. Taghreed visualizer features to its users a wide variety of spatiotemporal queries and presents the answers on a map-based user interface that allows an interactive exploration. Taghreed is the first system that addresses all these challenges collectively for geotagged microblogs data. The system is demonstrated based on real system implementation through different scenarios that show system functionality and internals.

Capsule image segmentation in pharmaceutical applications using edge-based techniques

Real-time quality inspection of gelatin capsules in pharmaceutical applications is an important issue from the point of view of industry productivity and competitiveness. Computer vision-based automatic quality inspection and controller system is one of the solutions to this problem. In computer-vision based system a digital image obtained by a digital camera would usually have 24-bit color image. The analysis of an image with that many levels might require complicated image processing techniques. But in real-time application, where a part has to be inspected within a few milliseconds, either we have to reduce the image to a more manageable number of grey levels, usually two levels (binary image), and at the same time retain all necessary features of the original image or develop a complicated technique. A binary image can be obtained by thresholding the original image into two levels that is used as an input to the high throughput quality inspection system. In this paper, we develop a system using edge-based image segmentation techniques for quality inspection that satisfy the industrial requirements in pharmaceutical applications.

Visualization of a Scale Free Network in a Smartphone-Based Multimedia Big Data Environment

Smartphones equipped with varieties of sensors enable them in participatory and opportunistic crowd-sourced sensing. The built-in as well as external sensors paired with modern smartphones provide an ideal multimedia big data source, where a very large crowd can share audio, video, text, SMS, location, etc. In this paper, we will illustrate our proposed big data framework that has been storing multimedia data from a very large crowd since September 2014. Our framework uses Scale Free Network (SFN) to represent the dynamics of large crowd and produces visualization metrics by running spatio-temporal queries over the proposed multimedia big data framework.

Adding Inverse Kinematics for Providing Live Feedback in a Serious Game-Based Rehabilitation System

In this paper, we present a serious game-based framework for providing live feedback to a patient performing a rehabilitation therapy for the purpose of assisting a patient in correct therapeutic steps and obtaining high quality therapy data for further analysis. The game environment uses forward kinematics to receive the live sensory data from two 3D motion tracking sensors and uses inverse kinematics to analyze the sensory data stream in real-time. A subject performs a rehabilitation therapy prescribed by the physician and using both forward and inverse kinematics the system validates the angular and rotational positions of the joints with respect to the correct therapeutic posture and provides live feedback to the subject. As a proof of concept, we have developed an open source web-based framework that can be easily adopted for inhome therapy, without the assistance of a therapist. Finally, we share our initial test result, which is encouraging.