Sameh Abdalla

Efficiency of network event logs as admissible digital evidence

The large number of event logs generated in a typical network is increasingly becoming an obstacle for forensic investigators to analyze and use to detect and verify malicious activities. Research in the area of network forensic is trying to address the challenge of using network logs to reconstruct attack scenarios by proposing event correlation models. In this paper we introduce a new network forensics model that makes network event-logs admissible in the court of law. Our model collects available logs from connected network devices, applies decision tree algorithm in order to filter anomaly intrusion, then re-route the logs to a central repository where event-logs management functions are applied.

Ubiquitous human perception for real-time gender estimation

In environments where robotic systems are deployed people often have different requirements for the robotic services and human-robot interaction methods. This paper presents a robotic system that exploits the advantages of ubiquitous perception in order to gather knowledge from multiple sensors and various modalities. This ubiquitous human perception will facilitate user profiling in order to support personalised services and individual human-robot interaction. This system combines ubiquitous smart sensing, methods of multi-modal human perception and existing human recognition algorithms from the field of biometrics to collectively work towards a real-time, robust and scalable solution for gender estimation.

Cyberspace Forensics Readiness and Security Awareness Model

The goal of reaching a high level of security in wire- less and wired communication networks is continuously proving difficult to achieve. The speed at which both keepers and violators of secure networks are evolving is relatively close. Nowadays, network infrastructures contain a large number of event logs captured by Firewalls and Domain Controllers (DCs). However, these logs are increasingly becoming an obstacle for network administrators in analyzing networks for malicious activities. Forensic investigators mission to detect malicious activities and reconstruct incident scenarios is extremely complex considering the number, as well as the quality of these event logs. This paper presents the building blocks for a model for automated network readiness and awareness. The idea for this model is to utilize the current network security outputs to construct forensically comprehensive evidence. The proposed model covers the three vital phases of the cybercrime management chain, which are: 1) Forensics Readiness, 2) Active Forensics, and 3) Forensics Awareness.

Electroencephalograms for Ubiquitous Robotic Systems

Abstract Ubiquitous robotics augments the capabilities of one or more robots by leveraging ubiquitous computational and/or sen- sorial resources. Augmentation complements and/or enhances the capabilities of one or more robots while such robots can simultaneously serve as intermediaries to ubiquitous services. Electroencephalograms (EEG) are Brain-Computer Interfaces that consist of a series of conductors placed on the scalp. These conductors measure voltage fluctuations in the brain, and using machine learning techniques can be classified and used to command ubiquitous robotic systems. The purpose of our work is to increase the collaboration between humans and surrounding robotic components while fulfilling a certain goal or requirement. We aim to do that by granting humans more precise manipulation, (i.e., brain- driven), over part or all of the involved robotic components. This paper presents our approach on the integration and benefits of an EEG interface within ubiquitous robotic systems.

Towards middleware security framework for next generation data centers connectivity

Data Center as a Service (DCaaS) facilitates to clients as an alternate outsourced physical data center, the expectations of business community to fully automate these data centers to run smoothly. Geographically Distributed Data Centers and their connectivity has major role in next generation data centers. In order to deploy the reliable connections between Distributed Data Centers, the SDN based security and logical firewalls are attractive and enviable. We present the middleware security framework for software defined data centers interconnectivity, the proposed security framework will be based on some learning processes, which will reduce the complexity and manage very large number of secure connections in real-world data centers. In this paper we will focus on two main objectives; (1) proposing simple and yet scalable techniques for security and analysis, (2) Implementing and evaluating these techniques on real-world data centers.

An agent-based negotiation approach for knowledge exchange in cloud service platforms

A number of cloud service platforms are targeting experts involved in vital decision-making activities that can lead, for example, governments to take precautions or healthcare professionals to perform specific operations. In order for these cloud platforms to operate there exist an underlying knowledge discovery engine that is employing a number of advanced data analytics techniques to derive insightful conclusions. The technical challenges facing designers and developers of such cloud architectures are increasing relatively with the sensitivity of the data in subject and the ranking of the addressees. In this paper, we investigate these challenges and examine the design approaches of these specific cloud service architectures. We propose an agent-based negotiation model for knowledge exchange among service architectures similar to those in subject.

Simulating SQL-Injection Cyber-attacks using GNS3

The 6th International Conference on Computer Modeling and Simulation (ICCMS 2015), Amsterdam Netherlands, 12-13 February 2015

BarterCell: An Agent-Based Bartering Service for Users of Pocket Computing Devices

The rising integration of pocket computing devices in our daily life duties has taken the attention of researchers from different scientific backgrounds. Todays amount of software applications bringing together advanced mobile services and literature of Artificial Intelligence AI is quite remarkable and worth investigating. In our research, software agents of BarterCell can operate in wireless networks on behalf of nomadic users, cooperate to resolve complex tasks and negotiate to reach mutually beneficial bartering agreements. In this paper, we introduce BarterCell that is an agent-based service application for users of pocket computing devices. We introduce new negotiation algorithms dedicated to bartering services in specific. We examine our approach in a scenario wherein it is essential for a multi-agent system to establish a chain of mutually attracted agents seeking to fulfill different bartering desires. And, we demonstrate and analyze the obtained results.

Electroencephalogram training phase reduction for ubiquitous robotic brain symbiosis

Electroencephalograms are brain-computer interfaces that consist of a series of conductors placed on the scalp, using machine-learning techniques, the P300 signal can be classified and used to command ubiquitous robotic systems. For both able-bodied and disabled subjects, the collection of training data can be an exhaustive exercise. It is the goal of this work-in-progress to substitute an extended training phase with a more generalized approach involving electroencephalogram data from multiple subjects, in an attempt to eliminate classification redundancy.

Sensor Infrastructures for Ambient Assisted Living

The presence of people on virtual social networks, their interactions, interests and their feedback can be perceived as inputs for assistive healthcare systems to predict a certain risk or condition. In this chapter we address the modern role of Ambient Assisted Living (AAL) in daily life activities. We emphasise the significance of integrating intelligent sensor infrastructures to current AAL architectures. We describe the main features and core architecture of a sensor middleware and introduce the service gateways provided to expand the range of data inputs within AAL architectures. Finally we present a motivating scenario of a healthcare service application, (i.e., iMED), which we are employing as an example to link AAL architectures and Sensor Middlewares.