Abstract

The increasing complexity of smartphone applications and services necessitate high battery consumption, but the growth of smartphones’ battery capacity is not keeping pace with these increasing power demands. To overcome this problem, researchers gave birth to the Mobile Cloud Computing (MCC) research area. In this paper, we advance on previous ideas, proposing and implementing a Near Field Communication (NFC)-based computation offloading framework. This research is motivated by the advantages of NFC’s short distance communication, its better security, and its low battery consumption characteristics. We design a new NFC communication protocol that overcomes the limitations of the default NFC protocol; removing the need for constant user interaction, the one-way communication restraint, and the limit on low data size transfer. Via the implemented framework, parts of mobile applications can be offloaded to other mobile devices or cloudlets equipped with an NFC reader. We present experimental results of the energy consumption and the time duration of computationally and data intensive representative applications: (i) RSA key generation and encryption, (ii) gaming/puzzles, (iii) face detection, (iv) media download from the Internet, and (v) data transferring between the mobile and the cloudlet. We show that when the helper device is more powerful than the device offloading the computations, the execution time of the tasks is reduced. Finally, we show that devices that offload application parts considerably reduce their energy consumption due to the low-power NFC interface and the benefits of offloading.

Abstract

During the current pandemic time of covid-19, we are urged to maintain a specific amount of social distance to prevent virus spread whenever we visit public places. Maintaining such distance becomes challenging sometimes even with implementation of new standard protocols. The contact can mainly happen when one steps out for essential services, and standing in queues for long hours. This paper aims at decreasing the spread of virus, by reducing the waiting time in queuing scenarios at supermarkets. We propose a Covid-19 social distancing system that complies with social distancing norms at various places. We put forth an Android application for customers and a web application for shopkeepers that operates with a token based system. It works with a system notifying the customer in the form of a message about the availability and turn to visit the supermarket. The paper provides the limitations of existing queue based systems, explanation and working of the proposed system.

Abstract

Contact tracing is an essential tool for public health officials and local communities to fight the spread of novel diseases, such as for the COVID-19 pandemic. The Singaporean government just released a mobile phone app, TraceTogether, that is designed to assist health officials in tracking down exposures after an infected individual is identified. However, there are important privacy implications of the existence of such tracking apps. Here, we analyze some of those implications and discuss ways of ameliorating the privacy concerns without decreasing usefulness to public health. We hope in writing this document to ensure that privacy is a central feature of conversations surrounding mobile contact tracing apps and to encourage community efforts to develop alternative effective solutions with stronger privacy protection for the users. Importantly, though we discuss potential modifications, this document is not meant as a formal research paper, but instead is a response to some of the privacy characteristics of direct contact tracing apps like TraceTogether and an early-stage Request for Comments to the community.

Abstract

Multimodal biometric authentication method can conquer the defects of the unimodal biometric authentication technology. In this paper, we design and develop an efficient Android-based multimodal biometric authentication system with face and voice. Considering the hardware performance restriction of the smart terminal, including the random access memory (RAM), central processing unit (CPU) and graphics processor unit (GPU), etc., which cannot efficiently accomplish the tasks of storing and quickly processing the large amount of data, a face detection method is introduced to efficiently discard the redundant background of the image and reduce the unnecessary information. Furthermore, an improved local binary pattern (LBP) coding method is presented to improve the robustness of the extracted face feature. We also improve the conventional endpoint detection technology, i.e. the voice activity detection (VAD) method, which can efficiently increase the detection accuracy of the voice mute and transition information and boost the voice matching effectiveness. To boost the authentication accuracy and effectiveness, we present an adaptive fusion strategy which organically integrates the merits of the face and voice biometrics simultaneously. The cross-validation experiments with public databases demonstrate encouraging authentication performances compared with some state-of-the-art methods. Extensive testing experiments on Android-based smart terminal show that the developed multimodal biometric authentication system achieves perfect authentication effect and can efficiently content the practical requirements.

Abstract

The main aim of this paper, to introduce the online based app for applying and renewals of bus pass in the government bus. Those who wish to take a bus pass in the government bus and also renewal of their bus pass within the specific period of time which is easy by using this app.

Abstract

This project deals with the camera application that can process the image to various processes. The impact of this project is made by the existing system where Google Lens process the image into text, translate, navigate and search about the text. The image is processed based on two major modules TEXT and IMAGE. TEXT module contains OCR, translation, maps, related Images. IMAGE module contains face emotions and image recognition. Where face emotion detects a face and reveals one’s reactions such as happiness or sadness, etc. Whereas the image recognition module processes the entire object within an image and identifies each object in text form. This project is being developed using Android Studio with the Cognitive Services from Microsoft and Google API services.

Abstract

Mobile and web application security, particularly the areas of data privacy, has raised much concerns from the public in recent years. Most applications, or apps for short, are installed without disclosing full information to users and clearly stating what the application has access to, which often raises concern when users become aware of unnecessary information being collected. Unfortunately, most users have little to no technical expertise in regards to what permissions should be turned on and can only rely on their intuition and past experiences to make relatively uninformed decisions. To solve this problem, we developed DroidNet, which is a crowd-sourced Android recommendation tool and framework. DroidNet alleviates privacy concerns and presents users with high confidence permission control recommendations based on the decision from expert users who are using the same apps. This paper explains the general framework, principles, and model behind DroidNet while also providing an experimental setup design which shows the effectiveness and necessity for such a tool.

Abstract

In this digital era, different organizations have started taking attendance using biometric fingerprint authentication. This will keep the track of employee’s attendance but the question arises if the employee is fully present at his/her workplace after giving attendance. In this modern era of digitalization, it is seen that after giving attendance a huge number of employees escape away from their workplace and do their personal job in the office time. This paper focuses on a smart attendance system where an android device will be used as a smart ID card. A mobile application is developed in Java to ensure the attendance of an individual employee using bio-metric fingerprint authentication. In addition, the entire working place will be a Wi-Fi zone. So, the connection or disconnection of the android device (Smart ID card) to the router will determine whether an employee is present in the working place or not. A counter will be there into the system to count the total amount of time an employee spends in the working place.

Abstract

During past decades, the classroom scheduling problem has posed significant challenges to educational programmers and teaching secretaries. In order to alleviate the burden of the programmers, this paper presents SmartClass, which allows the programmers to solve this problem using web services. By introducing service-oriented architecture (SOA), SmartClass is able to provide classroom scheduling services with back-stage design space exploration and greedy algorithms. Furthermore, the SmartClass architecture can be dynamically coupled to different scheduling algorithms (e.g. Greedy, DSE, etc.) to fit in specific demands. A typical case study demonstrates that SmartClass provides a new efficient paradigm to the traditional classroom scheduling problem, which could achieve high flexibility by software services reuse and ease the burden of educational programmers. Evaluation results on efficiency, overheads and scheduling performance demonstrate the SmartClass has lower scheduling overheads with higher efficiency.

Abstract

The convergence of Internet of Things, cloud computing, and wireless body-area networks (WBANs) has greatly promoted the industrialization of electronic-/mobile-healthcare (e-/m-healthcare). However, the further flourishing of e-/m-healthcare still faces many challenges including information security and privacy preservation. To address these problems, a healthcare system (HES) framework is designed that collects medical data from WBANs, transmits them through an extensive wireless sensor network infrastructure, and finally, publishes them into wireless personal-area networks via a gateway. Furthermore, HES involves the groups of send-receive model scheme to realize key distribution and secure data transmission, the homomorphic encryption based on matrix scheme to ensure privacy, and an expert system able to analyze the scrambled medical data and feedback the results automatically. Theoretical and experimental evaluations are conducted to demonstrate the security, privacy, and improved performance of HES compared with current systems or schemes. Finally, the prototype implementation of HES is explored to verify its feasibility.

Abstract

In every higher education setting in Malaysia, there are concerns about student attendance, as the current process of manual attendance taking is not only time consuming but is also inaccurate. Inconsistent attendance in class may significantly affect students’ overall academic performance. Thus, having a consistent attendance system is important. This paper proposes a mobile attendance system equipped with face recognition and a GPS locator. The face recognition adopts the Local Binary Pattern Histogram (LBPH) algorithm and retrieves the student’s location using GPS services. This project has a high potential to replace the current attendance system, as it is designed for speed and accuracy and is more convenient than the current approach.

Abstract

Avatar is a system that leverages cloud resources to support fast, scalable, reliable, and energy efficient distributed computing over mobile devices. An avatar is a per-user software entity in the cloud that runs apps on behalf of the user’s mobile devices. The avatars are instantiated as virtual machines in the cloud that run the same operating system with the mobile devices. In this way, avatars provide resource isolation and execute unmodified app components, which simplifies technology adoption. Avatar apps execute over distributed and synchronized (mobile device, avatar) pairs to achieve a global goal. The three main challenges that must be overcome by the Avatar system are: creating a high-level programming model and a middleware that enable effective execution of distributed applications on a combination of mobile devices and avatars, re-designing the cloud architecture and protocols to support billions of mobile users and mobile apps with very different characteristics from the current cloud workloads, and explore new approaches that balance privacy guarantees with app efficiency/usability. We have built a basic Avatar prototype on Android devices and Android x86 virtual machines. An application that searches for a lost child by analyzing the photos taken by people at a crowded public event runs on top of this prototype.

Abstract

Mobile Android applications often have access to sensitive data and resources on the user device. Misuse of this data by malicious applications may result in privacy breaches and sensitive data leakage. An example would be a malicious application surreptitiously recording a confidential business conversation. The problem arises from the fact that Android users do not have control over the application capabilities once the applications have been granted the requested privileges upon installation. In many cases, however, whether an application may get a privilege depends on the specific user context and thus we need a context-based access control mechanism by which privileges can be dynamically granted or revoked to applications based on the specific context of the user. In this paper we propose such an access control mechanism. Our implementation of context differentiates between closely located sub-areas within the same location. We have modified the Android operating system so that context-based access control restrictions can be specified and enforced. We have performed several experiments to assess the efficiency of our access control mechanism and the accuracy of context detection.

Abstract

Equipped with state-of-the-art smartphones and mobile devices, today’s highly interconnected urban population is increasingly dependent on these gadgets to organize and plan their daily lives. These applications often rely on current (or preferred) locations of individual users or a group of users to provide the desired service, which jeopardizes their privacy; users do not necessarily want to reveal their current (or preferred) locations to the service provider or to other, possibly untrusted, users. In this paper, we propose privacy-preserving algorithms for determining an optimal meeting location for a group of users. We perform a thorough privacy evaluation by formally quantifying privacy-loss of the proposed approaches. In order to study the performance of our algorithms in a real deployment, we implement and test their execution efficiency on Nokia smartphones. By means of a targeted user-study, we attempt to get an insight into the privacy-awareness of users in location-based services and the usability of the proposed solutions.

Abstract

The bus arrival time is primary information to most city transport travelers. Excessively long waiting time at bus stops often discourages the travelers and makes them reluctant to take buses. In this paper, we present a bus arrival time prediction system based on bus passengers’ participatory sensing. With commodity mobile phones, the bus passengers’ surrounding environmental context is effectively collected and utilized to estimate the bus traveling routes and predict bus arrival time at various bus stops. The proposed system solely relies on the collaborative effort of the participating users and is independent from the bus operating companies, so it can be easily adopted to support universal bus service systems without requesting support from particular bus operating companies. Instead of referring to GPS-enabled location information, we resort to more generally available and energy efficient sensing resources, including cell tower signals, movement statuses, audio recordings, etc., which bring less burden to the participatory party and encourage their participation. We develop a prototype system with different types of Android-based mobile phones and comprehensively experiment with the NTU campus shuttle buses as well as Singapore public buses over a 7-week period. The evaluation results suggest that the proposed system achieves outstanding prediction accuracy compared with those bus operator initiated and GPS supported solutions. We further adopt our system and conduct quick trial experiments with London bus system for 4 days, which suggests the easy deployment of our system and promising system performance across cities. At the same time, the proposed solution is more generally available and energy friendly.

Abstract

With the pervasiveness of smart phones and the advance of wireless body sensor networks (BSNs), mobile Healthcare (m-Healthcare), which extends the operation of Healthcare provider into a pervasive environment for better health monitoring, has attracted considerable interest recently. However, the flourish of m-Healthcare still faces many challenges including information security and privacy preservation. In this paper, we propose a secure and privacy-preserving opportunistic computing framework, called SPOC, for m-Healthcare emergency. With SPOC, smart phone resources including computing power and energy can be opportunistically gathered to process the computing-intensive personal health information (PHI) during m-Healthcare emergency with minimal privacy disclosure. In specific, to leverage the PHI privacy disclosure and the high reliability of PHI process and transmission in m-Healthcare emergency, we introduce an efficient user-centric privacy access control in SPOC framework, which is based on an attribute-based access control and a new privacy-preserving scalar product computation (PPSPC) technique, and allows a medical user to decide who can participate in the opportunistic computing to assist in processing his overwhelming PHI data. Detailed security analysis shows that the proposed SPOC framework can efficiently achieve user-centric privacy access control in m-Healthcare emergency. In addition, performance evaluations via extensive simulations demonstrate the SPOC’s effectiveness in term of providing high-reliable-PHI process and transmission while minimizing the privacy disclosure during m-Healthcare emergency.

Abstract

The wireless body area network (WBAN) has attracted considerable attention and becomes a promising approach to provide a 24-h on-the-go healthcare service for users. However, it still faces many challenges on the privacy of users’ sensitive personal information and the confidentiality of healthcare center’s disease models. For this reason, many privacy-preserving schemes have been proposed in recent years. However, the efficiency and accuracy of those privacy-preserving schemes become a big issue to be solved. In this paper, we propose an efficient and privacy-preserving priority classification scheme, named PPC, for classifying patients’ encrypted data at the WBAN-gateway in a remote eHealthcare system. Specifically, to reduce the system latency, we design a non-interactive privacy-preserving priority classification algorithm, which allows the WBAN-gateway to conduct the privacy-preserving priority classification for the received users’ medical packets by itself and to relay these packets according to their priorities (criticalities). A detailed security analysis shows that the PPC scheme can achieve the priority classification and packets relay without disclosing the privacy of the users’ personal information and the confidentiality of the healthcare center’s disease models. In addition, the extensive experiments with an android app and two java server programs demonstrate its efficiency in terms of computational costs and communication overheads.

Abstract

We design and explore the usability and security of two geographic authentication schemes: GeoPass and GeoPassNotes. GeoPass requires users to choose a place on a digital map to authenticate with (a location password). GeoPassNotes-an extension of GeoPass-requires users to annotate their location password with a sequence of words that they can associate with the location (an annotated location password). In GeoPassNotes, users are authenticated by correctly entering both a location and an annotation. We conducted user studies to test the usability and assess the security of location passwords and annotated location passwords. The results indicate that both the variants are highly memorable, and that annotated location passwords may be more advantageous than location passwords alone due to their increased security and the minimal usability impact introduced by the annotation.

Abstract

Smartphones and tablets have become ubiquitous in our daily lives. Smartphones, in particular, have become more than personal assistants. These devices have provided new avenues for consumers to play, work, and socialize whenever and wherever they want. Smartphones are small in size, so they are easy to handle and to stow and carry in users’ pockets or purses. However, mobile devices are also susceptible to various problems. One of the greatest concerns is the possibility of breach in security and privacy if the device is seized by an outside party. It is possible that threats can come from friends as well as strangers. Due to the size of smart devices, they can be easily lost and may expose details of users’ private lives. In addition, this might enable pervasive observation or imitation of one’s movements and activities, such as sending messages to contacts, accessing private communication, shopping with a credit card, and relaying information about where one has been. This paper highlights the potential risks that occur when smartphones are stolen or seized, discusses the concept of continuous authentication, and analyzes current approaches and mechanisms of behavioral biometrics with respect to methodology, associated datasets and evaluation approaches.

Abstract

With the pervasiveness of smart phones, location-based services (LBS) have received considerable attention and become more popular and vital recently. However, the use of LBS also poses a potential threat to user’s location privacy. In this paper, aiming at spatial range query, a popular LBS providing information about points of interest (POIs) within a given distance, we present an efficient and privacy-preserving location-based query solution, called EPLQ. Specifically, to achieve privacy-preserving spatial range query, we propose the first predicate-only encryption scheme for inner product range (IPRE), which can be used to detect whether a position is within a given circular area in a privacy-preserving way. To reduce query latency, we further design a privacy-preserving tree index structure in EPLQ. Detailed security analysis confirms the security properties of EPLQ. In addition, extensive experiments are conducted, and the results demonstrate that EPLQ is very efficient in privacy-preserving spatial range query over outsourced encrypted data. In particular, for a mobile LBS user using an Android phone, around 0.9 s is needed to generate a query, and it also only requires a commodity workstation, which plays the role of the cloud in our experiments, a few seconds to search POIs.

Abstract

PassBYOP is a new graphical password scheme for public terminals that replaces the static digital images typically used in graphical password systems with personalized physical tokens, herein in the form of digital pictures displayed on a physical user-owned device such as a mobile phone. Users present these images to a system camera and then enter their password as a sequence of selections on live video of the token. Highly distinctive optical features are extracted from these selections and used as the password. We present three feasibility studies of PassBYOP examining its reliability, usability, and security against observation. The reliability study shows that image-feature based passwords are viable and suggests appropriate system thresholds – password items should contain a minimum of seven features, 40% of which must geometrically match originals stored on an authentication server in order to be judged equivalent. The usability study measures task completion times and error rates, revealing these to be 7.5 s and 9%, broadly comparable with prior graphical password systems that use static digital images. Finally, the security study highlights PassBYOP’s resistance to observation attack – three attackers are unable to compromise a password using shoulder surfing, camera-based observation, or malware. These results indicate that PassBYOP shows promise for security while maintaining the usability of current graphical password schemes.

Abstract

A common functionality of many location-based social networking applications is a location sharing service that allows a group of friends to share their locations. With a potentially untrusted server, such a location sharing service may threaten the privacy of users. Existing solutions for Privacy-Preserving Location Sharing Services (PPLSS) require a trusted third party that has access to the exact location of all users in the system or rely on expensive algorithms or protocols in terms of computational or communication overhead. Other solutions can only provide approximate query answers. To overcome these limitations, we propose a new encryption notion, called Order-Retrievable Encryption (ORE), for PPLSS for social networking applications. The distinguishing characteristics of our PPLSS are that it (1) allows a group of friends to share their exact locations without the need of any third party or leaking any location information to any server or users outside the group, (2) achieves low computational and communication cost by allowing users to receive the exact location of their friends without requiring any direct communication between users or multiple rounds of communication between a user and a server, (3) provides efficient query processing by designing an index structure for our ORE scheme, (4) supports dynamic location updates, and (5) provides personalized privacy protection within a group of friends by specifying a maximum distance where a user is willing to be located by his/her friends. Experimental results show that the computational and communication cost of our PPLSS is much better than the state-of-the-art solution.

Abstract

Location-based services are quickly becoming immensely popular. In addition to services based on users’ current location, many potential services rely on users’ location history, or their spatial-temporal provenance. Malicious users may lie about their spatial-temporal provenance without a carefully designed security system for users to prove their past locations. In this paper, we present the Spatial-Temporal provenance Assurance with Mutual Proofs (STAMP) scheme. STAMP is designed for ad-hoc mobile users generating location proofs for each other in a distributed setting. However, it can easily accommodate trusted mobile users and wireless access points. STAMP ensures the integrity and non-transferability of the location proofs and protects users’ privacy. A semi-trusted Certification Authority is used to distribute cryptographic keys as well as guard users against collusion by a light-weight entropy-based trust evaluation approach. Our prototype implementation on the Android platform shows that STAMP is low-cost in terms of computational and storage resources. Extensive simulation experiments show that our entropy-based trust model is able to achieve high ( > 0.9) collusion detection accuracy.

Abstract

Many web applications provide secondary authentication methods, i.e., secret questions (or password recovery questions), to reset the account password when a user’s login fails. However, the answers to many such secret questions can be easily guessed by an acquaintance or exposed to a stranger that has access to public online tools (e.g., online social networks); moreover, a user may forget her/his answers long after creating the secret questions. Today’s prevalence of smartphones has granted us new opportunities to observe and understand how the personal data collected by smartphone sensors and apps can help create personalized secret questions without violating the users’ privacy concerns. In this paper, we present a Secret-Question based Authentication system, called “Secret-QA”, that creates a set of secret questions on basic of people’s smartphone usage. We develop a prototype on Android smartphones, and evaluate the security of the secret questions by asking the acquaintance/stranger who participates in our user study to guess the answers with and without the help of online tools; meanwhile, we observe the questions’ reliability by asking participants to answer their own questions. Our experimental results reveal that the secret questions related to motion sensors, calendar, app installment, and part of legacy app usage history (e.g., phone calls) have the best memorability for users as well as the highest robustness to attacks.

Abstract

Medical organizations find it challenging to adopt cloud-based Electronic Health Records (EHR) services due to the risk of data breaches and the resulting compromise of patient data. Existing authorization models follow a patient-centric approach for EHR management, where the responsibility of authorizing data access is handled at the patients end. This creates a significant overhead for the patient who must authorize every access of their health record. This is not practical given that multiple personnel are typically involved in providing care and that the patient may not always be in a state to provide this authorization. Hence there is a need to develop a proper authorization delegation mechanism for safe, secure and easy to use cloud-based EHR Service management. We present a novel, centralized, attribute-based authorization mechanism that uses Attribute Based Encryption (ABE) and allows for delegated secure access of patient records. This mechanism transfers the service management overhead from the patient to the medical organization and allows easy delegation of cloud-based EHRs access authority to medical providers.

Abstract

Recent ubiquitous earthquakes have been leading to mass destruction of electrical power and cellular infrastructures, and deprive the innocent lives across the world. Due to the wide-area earthquake disaster, unavailable power and communication infrastructure, limited man-power and resource, traditional rescue operations and equipment are inefficient and time-consuming, leading to the golden hours missed. With the increasing proliferation of powerful wireless devices, like smartphones, they can be assumed to be abundantly available among the disaster victims and can act as valuable resource to coordinate disaster rescue operations. In this paper, we propose a smartphone-based self rescue system, also referred to as RescueMe, to assist the operations of disaster rescue and relief. The basic idea of RescueMe is that a set of smartphones carried by survivors trapped or buried under the collapsed infrastructure forms into a one-hop network and sends out distress signal in an energy-efficient manner to nearby rescue crews to assist rescue operations. We evaluate the proposed approach through extensive simulation experiment and compare its performance with the existing scheme TeamPhone. The simulation results show that the proposed approach can significantly reduce the schedule vacancy of broadcasting distress signal and improve the discovery probability with very little sacrifice of network lifetime, and indicate a potentially viable approach to expedite disaster rescue and relief operations.

Abstract

With banks reaching its users via mobile banking, it is becoming one of the essential feature that is demanded by almost every smartphone user. Mobile banking via a mobile browser is similar to internet banking. Browsing-based threats for smartphones are just the same as those for personal computers, elevating the need to focus on mobile security. Among the several authentication schemes, geolocation authentication is gaining importance as it is found most suitable for mobile devices. In this paper, GeoMoB, a dedicated secure mobile browser for mobile banking that makes use of multifactor authentication is designed and developed. GeoMoB features a geolocation based authentication scheme which ensures security of mobile transactions based on the user location. In addition to the existing two factor authentication scheme using user ID, password and OTP, the mobile number and geolocation is used to authenticate the user. The geolocation intimates the banks location from where the transaction is going to be performed thus helping banks to ensure secure transactions. The geolocation of the user is acquired through the network provider and hence the need for using GSM is eliminated. The multifactor authentication used in GeoMoB ensures security while performing mobile transaction and prevents users from various attacks.

Abstract

Nowadays, JPEG steganographic schemes, e.g., J-UNIWARD, which take into account the effects of embedding in the spatial domain tend to exhibit higher security and introduce less artifacts that can be captured by the prevalent steganalyzers. Following the paradigm, this letter proposes a new design of the distortion measure for JPEG steganography by incorporating the statistics of both the spatial and discrete cosine transform (DCT) domains. The spatial statistics of the decompressed JPEG images are first well characterized with distortion measures of some efficient steganographic schemes in the spatial domain, e.g., HILL, and the resulting embedding entropies of spatial blocks in alignment with DCT blocks are then transformed into the DCT domain to obtain the distortion measures for JPEG steganography. Experimental results show that the proposed method outperforms considerably other state-of-the-art JPEG steganographic schemes, i.e., J-UNIWARD and UERD, for the most effective feature set GFR at present, and rivals them for other feature sets, e.g., DCTR and CC-JRM.

Abstract

Advanced security methods are necessary to introduce effective online voting in the whole world. Elections conducted on paper consume a lot of resources and contribute to the destruction of forests, which leads to climate deterioration. Recent online voting experiences in countries, such as the United States, India, and Brazil, demonstrated that further research is needed to improve security guarantees for future elections, to ensure the confidentiality of votes and enable the verification of their integrity and validity. In this paper, we propose a ranked choice online voting system, which addresses these challenges. It eliminates all hardwired restrictions on the possible assignments of points to different candidates according to the voters’ personal preferences. In order to protect the confidentiality of the votes, each cast ballot is encrypted using the exponential ElGamal cryptosystem before submission. Furthermore, during voting the system ensures that proofs are generated and stored for each element in the cast ballot. These proofs can then be used to verify the correctness and the eligibility of each ballot before counting without decrypting and accessing the content of the ballot. This validates the votes in the counting process and at the same time maintains confidentiality. The security and performance analyses included in this paper demonstrate that our method has achieved significant improvements in comparison with the previous systems. The outcomes of our experiments also show that our proposed protocols are feasible for practical implementations.

Abstract

The number of mobile phones and tablets has notably been raising in last few years, which allows to extend its potential applications. In the field of education, the possibilities offered by augmented reality are yet to be explored. The experience which is proposed in this paper pretends to implement QR codes in subject teaching belonging to an industrial engineering degree. In particular, changes are shown in two subjects (electronic instrumentation and thermal engineering), with the aim to improve the learning process with the use of QR codes in the practices of both subjects. An opinion test was used to evaluate the undergraduate’s acceptance rate and satisfaction with this new technology proposed. The results of this survey were satisfactory and support the proposal to use mobile technology as part of the learning process.

Abstract

Automatic chatbots (also known as chat-agents) have attracted much attention from both researching and industrial fields. Generally, the semantic relevance between users’ queries and the corresponding responses is considered as the essential element for conversation modeling in both generation and ranking based chat systems. By contrast, it is a nontrivial task to adopt the users’ information, such as preference, social role, etc., into conversational models reasonably, while users’ profiles play a significant role in the procedure of conversations by providing the implicit contexts. This paper aims to address the personalized response ranking task by incorporating user profiles into the conversation model. In our approach, users’ personalized representations are latently learned from the contents posted by them via a two-branch neural network. After that, a deep neural network architecture is further presented to learn the fusion representation of posts, responses, and personal information. In this way, the proposed model could understand conversations from the users’ perspective; hence, the more appropriate responses are selected for a specified person. The experimental results on two datasets from social network services demonstrate that our approach is hopeful to represent users’ personal information implicitly based on user generated contents, and it is promising to perform as an important component in chatbots to select the personalized responses for each user.

Abstract

This paper presents a face recognition algorithm based on Local Binary Pattern (LBP) to be implemented in a Smartphone with Android operating system where the input image is obtained using the camera of such Smartphone. The LBP algorithm is used for Face characterization, due to its low complexity and its robustness light of this method is chosen to be applied in a Smartphone, this is because the light sensor of smartphone could darken or lighten the captured image and affect a efficient recognition. To perform system testing on a Smartphone was used a standard database (AR Face database) to simulate the capture of images, the average of images was used for obtaining a template by person and using Euclidean distance for classification, showing that the LBP obtains good results using a simple classification algorithm with a Smartphone with limited processing power like a smartphone, further tests were performed with 1 to 9 training images, obtaining up to 90% of recognition.

Abstract

This paper presents a technique to improve anti-theft for android based mobile phones by using different services like MMS instead of SMS. As the use of smartphones, tablets, phablets based on android operating system is increasing, many scenarios related with anti-theft have already been proposed and many software based on anti-theft have also been developed, but most of these software are not freely available and it’s difficult to identify the thief by using these software’s e.g. GPS Tracking. We put forward a new scheme, which enhances the present scenario, based on new technologies like Multimedia Messages. The scenario proposed in this work is totally dependent on the hardware of your smartphone like camera (front & back) and support for multimedia messages. Once this software is installed, it will work in the background, stores the current SIM number in a variable and keeps checking continuously for SIM change, whenever SIM gets changed from mobile, it will take snapshots and record a video in the background i.e., without taking user permission and then it will send an MMS, and number of snap shots, to an alternate mobile number and an email id, which was provided during installation. The enviable advantage of this software is that it is very easy to configure and it keeps running in the background without interrupting the user. To some extent it helps the owner to identify the thief.

Abstract

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