CSSR: a 2For1 Compressive Sensing Software Receiver with Combined Correlation For GPS-CA and Galileo-OS Signals

This is a 2for1 receiver because it acquires both GPS and Galileo signals at less than 50% of the complexity and processing time required by a Matched Filter acquisition receiver. CSSR is a new implementation of a dual-GNSS-signal Software Receiver using, for the first time, the compressive sensing technique to process the two GNSS signals at the same time (in this implementation, GPS C/A code and Galileo OS code signals are used). This paper describes this CSSR implementation, focusing on: (a) how we remove the subcarrier frequency effect from the Galileo signal, and combine it with the GPS signal as a BPSK like signal; (b) the pre-processing stage of the resultant BPSK signal to generate the non-Doppler shift vectors that compensates for the matching measurements in the compressive sensing process; and finally (c) the compressive sensing process to acquire both signals simultaneously by combining their dictionaries, or correlators. CSSR has been simulated using various actual signal conditions/scenarios. The results are compared to those obtained from running the same tests on 3-other matched filter receivers. CSSR achieves similar probability of detection to the others, and has a higher frequency resolution of 10Hz for the same 4ms dwell time. With Application processors on-board Smartphones getting more powerful and cheaper, and with 60% of the 3.1 billion dual GNSS offering on-board current Smartphones are based on side-by-side implementations, we believe that CSSR is a good candidate to saving cost and valuable battery energy when implemented on-board Smartphones

SCCOF: smart cooperative computation offloading framework for mobile cloud computing services

Virtual reality games and image processing Apps are examples of mobile cloud computing services (MCCS) common on Smartphones (SPs) nowadays, requiring intensive processing and/or wireless networking. The consequences are slow execution and huge battery consumption. Offloading the intensive computations of such Apps to a cloud based server can overcome such consequences. However, such offloading will introduce time delay and communication overheads. This paper proposes to do the offloading to nearby computing resources in a cooperative computation sharing network via short-range wireless connectivity. The proposed SCCOF reduces offloading response time and energy consumption overheads. SCCOF is supported by an intelligent cloud located controller that will form the cooperative resource sharing network on the go when needed, based on available devices in the vicinity, and will use the cloud if necessary. Upon the initiation of the MCCS service via the App, our controller will devise the offloaded VMs as well as the offloading network. A study test scenario was performed to evaluate the performance of SCCOF, resulting in saving of up to 16.2x in execution time and 57.25% energy

SILS: a Smart Indoors Localization Scheme based on on-the-go cooperative Smartphones networks using onboard Bluetooth, WiFi and GNSS

Seamless outdoors-indoors localization based on Smartphones sensors is essential to realize the full potential of Location Based Services. This paper proposes a Smart Indoors Localization Scheme (SILS) whereby participating Smartphones (SPs) in the same outdoors and indoors vicinity, form a Bluetooth network to locate the indoors SPs. To achieve this, SILS will perform 3 functions: (1) synchronize & locate all reachable WiFi Access Points (WAPs) with live GNSS time available on the outdoors SPs; 2) exchange a database of all SPs location and time-offsets; 3) calculate approximate location of indoor-SPs based on hybridization of GNSS, Bluetooth and WiFi measurements. These measurements includes a) Bluetooth to Bluetooth relative pseudo ranges of all participating SPs based on hop-synchronization and Master-Slave role switching to minimize the pseudo-ranges error, b) GNSS measured location of outdoors-SPs with good geometric reference points, and c) WAPs-SPs Trilateration estimates for deep indoors localization. Results, obtained from OPNET simulation and live trials of SILS built for various SPs network size and indoors/outdoors combinations scenarios, show that we can locate under 1 meter in near-indoors while accuracy of around 2-meters can be achieved when locating SPs at deep indoors situations. Better accuracy can be achieved when large numbers of SPs (up to 7) are available in the network/vicinity at any one time and when at least 4 of them have a good sky view outdoors

oBiometrics: A Software protection scheme using biometric-based obfuscation

This paper proposes to integrate biometric-based key generation into an obfuscated interpretation algorithm to protect authentication application software from illegitimate use or reverse-engineering. This is especially necessary for mCommerce because application programmes on mobile devices, such as Smartphones and Tablet-PCs are typically open for misuse by hackers. Therefore, the scheme proposed in this paper ensures that a correct interpretation / execution of the obfuscated program code of the authentication application requires a valid biometric generated key of the actual person to be authenticated, in real-time. Without this key, the real semantics of the program can not be understood by an attacker even if he/she gains access to this application code. Furthermore, the security provided by this scheme can be a vital aspect in protecting any application running on mobile devices that are increasingly used to perform business/financial or other security related applications, but are easily lost or stolen. The scheme starts by creating a personalised copy of any application based on the biometric key generated during an enrolment process with the authenticator as well as a nuance created at the time of communication between the client and the authenticator. The obfuscated code is then shipped to the client’s mobile devise and integrated with real-time biometric extracted data of the client to form the unlocking key during execution. The novelty of this scheme is achieved by the close binding of this application program to the biometric key of the client, thus making this application unusable for others. Trials and experimental results on biometric key generation, based on client's faces, and an implemented scheme prototype, based on the Android emulator, prove the concept and novelty of this proposed scheme

OGSR: A Low Complexity Galileo Software Receiver using Orthogonal Data and Pilot Channels

To improve localisation accuracy and multipath rejection, the Galileo-OS signal offers a new modulation with efficient power distribution technique between the two data and pilot navigation components. To achieve the full benefits of this modulation, a robust acquisition and tracking methods must be deployed. For example, using two parallel correlation channels to acquire these data and pilot will gain 3dB over using a single channel acquisition correlating with either one of them. However, dual channel SW receivers cost more processing overheads. In this paper, the authors propose to orthogonalise the received data and pilot signals so to enable their acquisition in a single correlation channel bandpass sampling receiver. Our simulation results, using Simulink, prove that OGSR performance is maintained (preserving the 3dB gain) with less processing time while the implementation complexity is reduced by 50%

UNILS: Unconstrained indoors localization scheme based on Cooperative Smartphones networking with onboard inertial, Bluetooth and GNSS devices

Location-based services (LBS) are becoming an important feature on today’s smartphones (SPs), tablets and wearable devices. Seamless outdoors-indoors navigation, and especially for accurate indoors localization, is the main demand of LBS users. Onboard WiFi, Bluetooth (BT) or inertial-sensors technologies have been proven to somewhat provide alternative solutions in GNSS-signal-denied areas (i.e. indoors) to define SPs location. However, limited coverage of WiFi access-points (WAPs), pre-installed BT-anchors, constrained of WAPs/BT-anchors physical positions within a building, and limitations of existing localisation techniques (in a standalone mode) on SPs are some of the main challenges to designing a spontaneous autonomous positioning solution with reliable accuracy at reasonable cost. This paper proposes an unconstrained indoors localization scheme (UNILS) based on cooperative SPs networking to tackle these challenges. The aim of this new scheme is to fuse multi-technologies measurements on SPs. The scheme uses relative-pseudoranging (based on time-of-arrival TOA technique) approach between the connected SPs that are GNSS enabled, especially when the majority of the SPs are outdoors, and combining this with uncertainty calculations from onboard dead-reckoning (DR) measurements using Kalman Filter, that can provide seamless and improve location accuracy significantly, especially when deep indoors. This means that, in deep indoors, UNILS can utilize only available devices/sensors on SPs, when communication with WAPs or BT-anchors is deemed unreliable or unavailable, to offer reasonable cost & good localization performance. Results obtained from actual trials & simulations (using OPNET) of this scheme (based on Android-SPs network implementations for various indoors scenarios) show that around 3-meters accuracy can be achieved when locating SPs at various deep indoors situations

eBiometrics: an enhanced multi-biometrics authentication technique for real-time remote applications on mobile devices

The use of mobile communication devices with advance sensors is growing rapidly. These sensors are enabling functions such as Image capture, Location applications, and Biometric authentication such as Fingerprint verification and Face & Handwritten signature recognition. Such ubiquitous devices are essential tools in today's global economic activities enabling anywhere-anytime financial and business transactions. Cryptographic functions and biometric-based authentication can enhance the security and confidentiality of mobile transactions. Using Biometric template security techniques in real-time biometric-based authentication are key factors for successful identity verification solutions, but are venerable to determined attacks by both fraudulent software and hardware. The EU-funded SecurePhone project has designed and implemented a multimodal biometric user authentication system on a prototype mobile communication device. However, various implementations of this project have resulted in long verification times or reduced accuracy and/or security. This paper proposes to use built-in-self-test techniques to ensure no tampering has taken place on the verification process prior to performing the actual biometric authentication. These techniques utilises the user personal identification number as a seed to generate a unique signature. This signature is then used to test the integrity of the verification process. Also, this study proposes the use of a combination of biometric modalities to provide application specific authentication in a secure environment, thus achieving optimum security level with effective processing time. I.e. to ensure that the necessary authentication steps and algorithms running on the mobile device application processor can not be undermined or modified by an imposter to get unauthorized access to the secure system

DEO: A Smart Dynamic Edge Offloading Scheme using Processing Resources of Nearby Wireless Devices to Form an Edge Computing Engine

Edge computing reduces connectivity costs and network traffic congestion over cloud computing, by offering local resources (processing and storage) at one hop closer to the end-users. I.e. it reduces the Round-Trip Time (RTT) for offloading part of the processing workload from end-nodes/devices to servers at the edge. However, edge servers are normally pre-setup as part of the overall computing resource infrastructure, which is tough to predict for mobile/IoT deployments. This paper introduces a smart Dynamic Edge Offloading scheme, (we named it DEO), that forms the “edge computing resource” on-the-go, as needed from nearby available devices in a cooperative sharing environment. This is especially necessary for hosting mobile/IoT applications traffic at crowded/urban situations, and, for example, when executing a processing intensive Mobile Cloud Computing Service (MCCS) on a Smartphone (SP). DEO implementation is achieved by using a short-range wireless connectivity between available cooperative end-devices, that will form the edge computing resource. DEO includes an intelligent cloud-based engine, that will facilitate the engagement of the edge network devices. For example, if the end-device is a SP running an MCCS, DEO will partition the processing of the MCCS into sub-tasks, that will be run in parallel on the newly formed “edge resource network” of other nearby devices. Our experiments prove that DEO reduces the RTT and cost overhead by 62.8% and 75.5%, when compared to offloading to a local edge server or a cloud-based server

Privacy preserving, real-time and location secured biometrics for mCommerce authentication

Secure wireless connectivity between mobile devices and financial/commercial establishments is mature, and so is the security of remote authentication for mCommerce. However, the current techniques are open for hacking, false misrepresentation, replay and other attacks. This is because of the lack of real-time and current-precise-location in the authentication process. This paper proposes a new technique that includes freshly-generated real-time personal biometric data of the client and present-position of the mobile device used by the client to perform the mCommerce so to form a real-time biometric representation to authenticate any remote transaction. A fresh GPS fix generates the "time and location" to stamp the biometric data freshly captured to produce a single, real-time biometric representation on the mobile device. A trusted Certification Authority (CA) acts as an independent authenticator of such client's claimed real time location and his/her provided fresh biometric data. Thus eliminates the necessity of user enrolment with many mCommerce services and application providers. This CA can also "independently from the client" and "at that instant of time" collect the client's mobile device "time and location" from the cellular network operator so to compare with the received information, together with the client's stored biometric information. Finally, to preserve the client's location privacy and to eliminate the possibility of cross-application client tracking, this paper proposes shielding the real location of the mobile device used prior to submission to the CA or authenticators