Department Publications

The development of computer based systems expands the usage of computer based application in human life. It can be observed that illegal activities such as unauthorized data access, data theft, data modification and various other intrusion activities are rapidly growing during last decade. Hence, deployment and continuous improvement of Intrusion Detection Systems (IDS) are of paramount importance. Training, testing and evaluation of IDS with real network traffic is significant challenge, so most of IDS evaluation is based on intrusion datasets. Therefore, analysis of intrusion datasets are of paramount importance. In this paper, we evaluated Aegean Wi-Fi Intrusion Dataset (AWID) with different machine learning techniques. Feature reduction techniques such as Information Gain (IG) and Chi-Squared statistics (CH) were applied to evaluate dataset performance with feature reduction. Results of experiments show …

Higher compression efficiency in HEVC encoders comes with increased computational complexity, making real time encoding of high resolution videos a challenging task. This challenge can be addressed by software, yet hardware solutions are more appealing due to their superior performance and low power consumption. This paper presents an FPGA based hardware implementation of an all intra HEVC encoder, which can encode 8 bits per sample, 1920×1080 resolution, 30 frames per second raw video, that is viable in real time even at low operating frequencies. A major obstacle to real time encoding in available architectures is the dependency created by reference generation. Moreover, each coding unit (CU) has to be processed in multiple configurations to determine the most efficient split and prediction mode representation, based on the bit stream generated. We propose a new three stage architecture to …

The P300 wave is an Event Related Potential that is elicited in the brain when a subject is presented with a familiar stimulus. The Guilty Knowledge Test is used to determine if certain information is stored in the brain by detecting the P300 wave. In this paper, an improved Guilty Knowledge Test has been conducted on 14 subjects. Although a variety of feature extraction and classification algorithms for detecting the P300 have been used thus far, this paper introduces the use of deep learning techniques for the Guilty Knowledge Test. Two deep learning techniques; Deep Belief Networks and Stacked Autoencoders, have been compared. The input to these classifiers was the filtered EEG signal without any feature extraction. A mean accuracy of 86.9% was achieved for the Deep Belief Network and 86.01% for the Stacked Autoencoder on our dataset, outperforming the conventional Support Vector Machine.

Intrusion detection is only a starting step in securing IT infrastructure. Prediction of intrusions is the next step to provide an active defense against incoming attacks. Current intrusion prediction methods focus mainly on prediction of either intrusion type or intrusion category and do not use or provide contextual information such as source and target IP address. In addition most of them are dependant on domain knowledge and specific scenario knowledge. The proposed algorithm employs a bag-of-words model together with a hidden Markov model which not depend on specific domain knowledge. Since this algorithm depends on a training process it is adaptable to different conditions. A key advantage of the proposed algorithm is the inclusion of contextual data such as source IP address, destination IP range, alert type and alert category in its prediction, which is crucial for an eventual response. Experiments conducted using a public data set generated over 2500 alert predictions and achieved accuracy of 81% and 77% for single step and five step predictions respectively for prediction of the next alert cluster. It also achieved an accuracy of prediction of 95% and 92% for single step and five step predictions respectively for prediction of the next alert category. The proposed methods achieved a prediction accuracy improvement of 5% for alert category over existing variable length Markov chain intrusion prediction methods, while providing more information for a possible defense.

This paper presents on the stability analysis for RAVAN twin boom H-Tail Medium Scale UAV which has been developed by University of Moratuwa. It is required to understand the UAV behavior for the small perturbations in high altitudes while it is flying to be invisible. Indeed, without doing a proper stability analysis in different flying conditions, there is a high risk to fail the UAV for perturbations. Not only that but also it will help to optimize aerodynamic behavior for prolonging the flight endurance and effective deployment. The proper stability analysis will facilitate to increase the control flexibility.XFLR5 computational fluid dynamic software is used to do this stability analysis.

Vehicular ad-hoc networks (VANETs) play a vital role in enabling intelligent transport services (ITS). The state of art dedicated short range communication (DSRC), which is envisioned to facilitate the communication in VANETs, requires dedicated hardware. This hinders the penetration of ITS especially in developing countries. This paper studies the suitability of Wi-Fi Direct (WD), which is readily available on many smart phones, as an alternative communication technology for VANETs. Performance measures such as throughput, end-to-end delay, packet receiving/loss ratios for both WD and DSRC are presented through simulations, using network simulator NS3, and the traffic simulator Simulation of Urban Mobility (SUMO). Both single-hop and multi-hop communication is considered. The results show the potential of WD as an alternative communication technology for VANETs.

Visible Light Communication (VLC) is emerging as a next generation data transmission method for short-range communication applications. In this paper we implement and characterize two prototype stereo audio streaming methods utilizing VLC. A software architecture is developed to process and stream data. The software architecture is bridged with a hardware section, which facilitates free-space VLC channel, over a Universal Serial Bus (USB) to serial interface. A particularly attractive feature of our system is that it uses commonly available, low-cost components which enables its implementation in everyday applications.

In the face of conflict governments often face the dilemma of protecting national security as well as fundamental rights. Often, it requires infringing on fundamental rights such as the due process of arrest and detention. Additionally governments are compelled to invade privacy and curtail freedom of speech, expression and information. This is further complicated by the tendency of the enemy to masquerade as innocent civilians. This paper investigates how this has been handled in the past by foreign nations with special attention to nations that practice consitutionalism and judicial review. Based on these past actions it is possible to formulate the concept of reasonable consequentialism. Reasonable consquentialism can be used as a legal maxim to determine when a government has acted excessively in an attempt to safeguard national security by compromising fundamental rights. Furthermore, these limits can act as checks and balances between the legislature/executive and judiciary to prevent misuse by an authoritarian government.

Intrusion detection is only a starting step in securing IT infrastructure. Prediction of intrusions is the next step to provide an active defense against incoming attacks. Most of the existing intrusion prediction methods mainly focus on prediction of either intrusion type or intrusion category. Also, most of them are built based on domain knowledge and specific scenario knowledge. This thesis proposes an alert prediction framework which provides more detailed information than just the intrusion type or category to initiate possible defensive measures. The proposed algorithm is based on hidden Markov model and it does not depend on specific domain knowledge. Instead, it depends on a training process. Hence the proposed algorithm is adaptable to different conditions. Also, it is based on prediction of the next alert cluster, which contains source IP address, destination IP range, alert type and alert category. Hence …

In this work we propose and analyze a possible hardware architecture for experimentation on fine-grained reconfigurable supercomputing based on modern Field Programmable Gate Array (FPGA) technology. It is proposed a scalable cubic array of elementary computational units which are interconnected according to a tridimensional toroidal mesh network. Each computational unit is essentially formed by an FPGA plus an onboard external RAM memory. While the adjacent units in the bulk are directly interconnected through the regular FPGA IOs; the external units at opposite faces of the cubic array are interconnected by mean of high speed serial links in order to grant homogeneous data transfer bandwidth among all topologically adjacent units. Among several relevant issues we discuss the feasibility, scalability and portability.

This paper introduces a model to study both single tier and multitier wireless communication systems consisting of a multitude of wireless access points (AP), and operating according to the classical opportunistic beamforming framework. The AP locations in the proposed network model are determined by using planar Poisson point processes. The extreme value distribution of signal-to-interference-plus-noise-ratio (SINR) on a beam is of fundamental importance for obtaining performance bounds for such an opportunistic communication system. Two tight distribution approximation results are provided for the distribution of maximum SINR on a beam, which is hard to obtain due to correlation structure of the underlying inter-AP interference field, using key tools from stochastic geometry. These approximations hold for general path loss models that satisfy some mild conditions. Simulations and numerical evaluations …

Increasing demands for faster, more responsive and manageable networks have brought about a different approach to networking - Software Defined Networking (SDN). SDN introduces flow-based networking with a centralized controller. Matching incoming traffic flows with rules sent by the controller is an integral part of traffic forwarding in SDN. How efficiently this is carried out has a huge impact on network performance. In this paper, we present a high-performance, low-cost architecture for flow matching in an SDN switch. Our architecture consists of a dedicated unit for flow matching and a custom processor. Novel design of the flow match unit reduces matching latency significantly, when compared with the generic architecture, while also reducing usage of costly resources like TCAMs. When testing on FPGA platforms, implementing the system required only a minimum amount (around 10% on Virtex-7) of …

Since recently, UAVs (Unmanned Aerial Vehicles) have increasingly been recognized as a reliable, and effective means of aerial surveillance. Deployment of UAVs in disaster management for aerial surveillance and real-time video feed, when land access is cut off, is one of the most prominent applications. The ability of small, lightweight UAVs in aerial access and gathering data, in areas that are insecure or impossible for humans to reach has significantly improved remote accessibility. In this research, a new low cost small scale UAV with fully-fledged autopilot system on board the aircraft with the capabilities of following a predefined path and returning home autonomously has been designed, built, and tested successfully. This small-scale UAV is capable of navigating through given GPS coordinates at given altitude, while providing real-time flying status back to the ground control station.

Multiple antenna techniques, that allow energy beamforming, have been looked upon as a possible candidate for increasing the efficiency of the transfer process between the energy transmitter (ET) and the energy receiver (ER) in wireless energy transfer. This paper introduces a novel scheme that facilitates energy beamforming by utilizing Received Signal Strength Indicator (RSSI) values to estimate the channel. Firstly, in the training stage, the ET will transmit sequentially using each beamforming vector in a codebook, which is pre-defined using a Cramer-Rao lower bound analysis. The RSSI value corresponding to each beamforming vector is fed back to the ET, and these values are used to estimate the channel through a maximum likelihood analysis. The results that are obtained are remarkably simple, requires minimal processing, and can be easily implemented. Also, the results are general and hold for all …

Everyone is moving towards smart era rapidly with new technologies. This paper focuses on monitoring a building from a remote place to ensure the activities happening in particular locations. Here we have proposed a sensor-based wireless distributed system with people counting and activity detection for a building. A novel approach is used to people count using one motion sensor. A System model is built and experimented in the department of Electronic and Telecommunication Engineering (ENTC), University of Moratuwa. This enables monitoring activities in the lecture hall, lecturer room and lab with high precision.

This paper identifies the challenges involved in designing the 100 Gigabit per second (Gbps) Ethernet Physical Coding Sublayer (PCS) Semiconductor Intellectual property (IP) compliant with IEEE 802.3 standard. Challenges are discussed under the two topics, implementation challenges and verification challenges. Furthermore, our solutions to identified challenges are presented in the paper.

This paper presents the implementation and analysis of a low complex architecture for a fast locking Phase Locked Loop. In this paper, we analyse a high speed mixed signal PLL architecture and its components such as phase frequency detector, charge pump, voltage controlled oscillator etc. are further reviewed. The simulation results show that proposed PLL design achieves locking within 1 μβ and it operates at 5 GHz featuring a significant P k -P k jitter value less than 10 ps and root-mean-square jitter less than 5 ps. Mathematical modeling and simulations of the proposed PLL architecture are also presented.

The P300 Speller is a Brain Computer Interface that enables communication using the EEG signal. The P300 wave is an Event Related Potential that occurs as a response to a familiar stimulus. This system can be used to aid persons who are unable to communicate via conventional methods. In this paper, the P300 Speller has been modified to allow communication in three languages: English, Sinhala and Tamil. Classification of the P300 waveform was done using an ensemble of Support Vector Machines. A mean letter classification accuracy of 83.76% and a mean P300 classification accuracy of 90.68% was achieved on our dataset.

Electrophysiology has recently evolved into an interactive, high-throughput endeavor. Recording from dozens to hundreds of electrodes is today routine; novel means of manipulating the system in real time, through electrical stimulation, optogenetics or sensory manipulation are allowing us to decipher neural circuit function at an unparalleled rate. To contribute to the wide dissemination of such techniques, we present an open hardware project, High-Channel Count Electrophysiology (HiCCE), aiming to produce low-cost, high-channel count (≥128 channels) electrophysiology instrumentation capable of fast data acquisition rates, real-time processing and feedback capabilities. Our design is centered on an open standard, FPGA Mezzanine Card (FMC), which permits a varied choice of FPGA carrier architectures suited to different laboratory experimental needs. The HiCCE-128, a low-cost highperformance 128 …

Memory Based Event Triggering (MBET) is a pragmatic approach to reduce the effective sampling rate of a control system. In MBET, periodically sampled state variables and control inputs are encoded such that data transmission takes place only when they change by a value that exceeds a predetermined threshold. This results in a significant reduction of network traffic in Networked Control Systems (NCS). Should MBET encoding result in an asymptotic cyclic behavior (limit cycle like behavior), it would result in a lower bound in the required bandwidth. In this paper, the necessary conditions for the formation of such a cycle are investigated. It is demonstrated analytically as well as through empirical simulations that the main requirement for the occurrence of asymptotic dynamic cycles is a diffeomorphism between a scalar control input and a unique equilibrium point to which the system will converge to for a constant …

Frequently, a physical plant of a control system has an optimum operating point such as the spark (or injection) time of an internal combustion engine that results in maximum torque. Extremum Seeking Control (ESC) is a method of adaptive control capable of locating and maintaining a plant at such an optimum operating point in real time. It is capable of doing so with minimal a priori knowledge of the plant and can also track slowly varying changes. Input perturbed ESC schemes that use periodic dither signals have the disadvantage of requiring a high bandwidth for sampling and correlating the plant output with the dither signal. If the feedback path was to be implemented over a packet switched communication network, the high bandwidth requirement could result in increased congestion and consequently packet delays and dropouts. As a solution encoding using sporadic (aperiodic) sampling techniques can be used in the feedback path of the ESC scheme to reduce the required bandwidth. However, in order to ensure convergence of the ESC scheme with encoding, the effect of the signal reconstruction error due to encoding on the critical correlation stage has to be investigated. The contribution of this paper is an investigation of the convergence requirements and bandwidth performance of two encoding schemes; Memory-Based Event Triggering (MBET) and Event Triggered Adaptive Differential Modulation (ETADM). The results show that MBET can fail for objective functions with plateaus. ETADM fails when the number of ETADM steps used for reconstructing the plant output per perturbation cycle is too low to allow correlation. In terms of …

This paper analyses the receiver of 40GBASE PCS Sub layer specified by IEEE 802.3ba CSMA/CD standards. Based on the analysis, possible optimization parameters for the receiver FIFO are identified. Proper functionality of the proposed design is verified with simulation results. The optimization of receiver FIFO design may lead to reduce the gate count, area and power consumption in ASIC design.

We present the development and testing of a cellular network built on open source technologies. This network supports voice calls and text messages within the network or between networks. The main objective of this work is to develop a stand-alone mobile network consisting of one base station and a switch, the access to which can be controlled as required. The mobile network is also connected to public networks. The designed network is based on Global System for Mobile Communications (GSM). Our work includes the configuration of the embedded hardware components, selection and integration of the proper software combination, testing of compatible versions of the software, hardware-software integration within the embedded system, and interconnecting the systems via the Internet. The key contribution and novelty of the project is the development of a stand-alone mobile network base station/ switch …