IEEE 2014 / 13 - Android Projects
IEEE 2014 : Privacy-Preserving Optimal Meeting Location Determination on Mobile Devices
IEEE 2014 :Efficient Authentication for Mobile and Pervasive Computing
IEEE 2013: Cloud Computing For Mobile Users: Can Offloading Computation Save Energy?
IEEE 2014: Wireless Sensor Networks Using Android Virtual Devices and Near Field Communication Peer-To- Peer Emulation
Abstract— Several new Android Smartphone’s support Near Field Communication (NFC). The Android SDK provides an NFC API that can be used to develop NFC applications that conduct peer-to-peer (P 2 P) data exchange. The Android emulator does not support P 2 P communication between instances of the Android Virtual Device (A VD). In addition to this constraint, P2P experimentation on actual Smartphone’s is difficult due to limited NFC support. To fill the gap created by this minimal support, we propose the Java Mail NFC API (J NFC). J NFC uses the Java Mail API to emulate the functionality of the Android NFC P2P API. To evaluate the performance of J NFC, we created the Droid WSN Wireless Sensor Network (WSN) model and implemented it as an Android application. We design and conduct an experiment for our Droid WSN model to measure the execution time of our Android application WSN on AVDs. We compare our simulation results against those from a similar experiment that measured the execution time of a WSN composed of Sun SPOT wireless devices. While the execution time of our Droid W S N model is slower, we assert that our design is more simple and flexible than that of our comparison study. We conclude that this benefit and the factors of J N F C cost (it is open source), the quality and quantity of Android Smartphone sensors, and imminent Android Smartphone support for NFC P 2 P, combine to make J N F C and the Android A V D a platform for NFC and W S N research. Our study also emphasizes the need for Google to create Android NFC P 2 P and sensor emulation APIs
Abstract—Equipped with state-of-the-art smart phones 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 un trusted, 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 smart phones. By means of a targeted user-study, we attempt to get an insight in privacy-awareness of users in location based services and the usability of the propose solutions.
Abstract—With today’s technology, many applications rely on the existence of small devices that can exchange information and form communication networks. In a significant portion of such applications, the confidentiality and integrity of the communicated messages are of particular interest. In this work, we propose two novel techniques for authenticating short encrypted messages that are directed to meet the requirements of mobile and pervasive applications. By taking advantage of the fact that the message to be authenticated must also be encrypted, we propose provably secure authentication codes that are more efficient than any message authentication code in the literature. The key idea behind the proposed techniques is to utilize the security that the encryption algorithm can provide to design more efficient authentication mechanisms, as opposed to using standalone authentication primitives.
IEEE 2014 :Preserving Location Privacy in Geo-Social Applications
Abstract—Using geo-social applications, such as Four Square, millions of people interact with their surroundings through their friends and their recommendations. Without adequate privacy protection, however, these systems can be easily misused, e.g., to track users or target them for home invasion. In this paper, we introduce Loc X, a novel alternative that provides significantly-improved location privacy without adding uncertainty into query results or relying on strong assumptions about server security. Our key insight is to apply secure user-specific, distance-preserving coordinate transformations to all location data shared with the server. The friends of a user share this user’s secrets so they can apply the same transformation. This allows all location queries to be evaluated correctly by the server, but our privacy mechanisms guarantee that servers are unable to see or infer the actual location data from the transformed data or from the data access. We show that Loc X provides privacy even against a powerful adversary model, and we use prototype measurements to show that it provides privacy with very little performance overhead, making it suitable for today’s mobile devices.
IEEE 2014 :Protection and Monitoring of School Kid Using Android Virtual Devices and Near Field Communication
Abstract—With the increasing number of location-dependent applications,positioning and tracking a mobile device becomes more and more important to enable pervasive and context-aware service. While extensive research has been performed in physical localization and logical localization for satellite, GSM and w if I communication networks where fixed reference points are densely-deployed, positioning and tracking techniques in a sparse disruption tolerant network (DTN) have not been well addressed. In this paper, we propose a decentralized cooperative method called Pulse Counting for DTN localization and a probabilistic tracking method called P r ob Tracking to confront this challenge. Pulse Counting evaluates the user walking steps and movement orientations using accelerometer and electronic compass equipped in cell phones. It estimates user location by accumulating the walking segments, and improves the estimation accuracy by exploiting the encounters of mobile nodes. Several methods to refine the location estimation are discussed, which include the adjustment of trajectory based on reference point sand the mutual refinement of location estimation for encountering nodes based on maximum-likelihood. To track user movement, the proposed P rob Tracking method uses Markov chain to describe movement patterns and determines the most possible user walking trajectories without full record of user locations. We implemented the positioning and tracking system in Android phones and deployed a test bed in the campus of Nanjing University. Extensive experiments are conducted to evaluate the effectiveness and accuracy of the proposed methods, which show an average deviation of 9m in our system compared to GPS.
Abstract—School kids monitoring is of great importance for parents who send their kids to school via school transport vehicle. There are many applications that exist for monitoring the vehicle as the kids go to school and come back from school. The existing system gives the tracking report of vehicle and its exact location. Even some applications give vehicle position update information to the parents. This system helps the parents only with the information of the vehicle but they don’t tell whether their kid is in the bus or not.Assume that some kid has participated in cultural program. They are not able to take the vehicle allotted to them or suppose the kid has missed the vehicle to reach his/her house. In that case parents are not able to monitor the kid after school time. This was the problem of existing approaches.In proposed system we are planning to send email / SMS confirmation to the parent when the kid steps into the vehicle using Android Mobile phones through Near Field Communication (NFC) features.
IEEE 2014 :Context-driven,Prescription-Based Personal Activity Classification: Methodology, Architecture, and End-to-End Implementation
Abstract—Enabling large-scale monitoring and classification of a range of motion activities is of primary importance due to the need by healthcare and fitness professionals to monitor exercises for quality and compliance.Past work has not fully addressed the unique challenges that arise from scaling.This paper presents a novel end-to-end system solution to some of these challenges. The system is built on the prescription-based context driven activity classification methodology. First, we show that by refining the definition of context, and introducing the concept of scenarios, a prescription model can provide personalized activity monitoring. Second, through a flexible architecture constructed from interface models, we demonstrate the concept of a context-driven classifier. Context classification is achieved through a classification committee approach, and activity classification follows by means of context specific activity models. Then, the architecture is implemented in an end-to-end system featuring an Android application running on a mobile device, and a number of classifiers as core classification components. Finally, we use a series of experimental field evaluations to confirm the expected benefits of the proposed system in terms of classification accuracy, rate, and sensor operating life.
IEEE 2014 :Context-based Access Control Systems for Mobile Devices
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.
IEEE 2014 :Cooperative Positioning and Tracking in Disruption Tolerant Networks
IEEE 2014 :Efficient Authentication for Mobile and Pervasive Computing
Abstract—With today’s technology, many applications rely on the existence of small devices that can exchange information and form communication networks. In a significant portion of such applications, the confidentiality and integrity of the communicated messages are of particular interest. In this work, we propose two novel techniques for authenticating short encrypted messages that are directed to meet the requirements of mobile and pervasive applications. By taking advantage of the fact that the message to be authenticated must also be encrypted, we propose provably secure authentication codes that are more efficient than any message authentication code in the literature. The key idea behind the proposed techniques is to utilize the security that the encryption algorithm can provide to design more efficient authentication mechanisms, as opposed to using standalone authentication primitives.
IEEE 2014 :Hiding in the Mobile Crowd: Location Privacy through Collaboration
Abstract—Location-aware smart phones support various location-based services (LBSs): users query the LBS server and learn on the fly about their surroundings. However, such queries give away private information, enabling the LBS to track users. We address this problem by proposing a user-collaborative privacy-preserving approach for LBSs. Our solution does not require changing the LBS server architecture and does not assume third party servers; yet, it significantly improves users’ location privacy. The gain stems from the collaboration of mobile devices: they keep their context information in a buffer and pass it to others seeking such information. Thus, a user remains hidden from the server, unless all the collaborative peers in the vicinity lack the sought information. We evaluate our scheme against the Bayesian localization attacks that allow for strong adversaries who can incorporate prior knowledge in their attacks. We develop a novel epidemic model to capture the, possibly time-dependent, dynamics of information propagation among users. Used in the Bayesian inference framework, this model helps analyze the effects of various parameters, such as users’ querying rates and the lifetime of context information, on users’ location privacy. The results show that our scheme hides a high fraction of location-based queries, thus significantly enhancing users’ location privacy. Our simulations with real mobility traces corroborate our model-based findings. Finally, our implementation on mobile platforms indicates that it is lightweight and the cost of collaboration is negligible.
IEEE 2014 :How Long to Wait? Predicting Bus Arrival Time With Mobile Phone Based Participatory Sensing
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 pro to type 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-weekperiod. 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.
IEEE 2013 : iMAS - an Intelligent Mobile Advertising System
IEEE 2013 Transactions on Intelligent and Software System
Abstract—Rapid expansion of wireless technologies has provided a platform to support intelligent systems in the domain of mobile marketing. Utilizing Location Based Services and Global Navigational Satellite Systems provides the capability for transport of real-time, scheduled, and location-based Advertising to individuals and businesses. This paper introduces location-based marketing and iMAS, a related novel intelligent mobile advertising system. Following an overview of location technologies, the iMAS prototype is presented. Evaluation is discussed as well as the testing strategy, results and open research questions.
IEEE 2013: Secure Transmission Medical Data for Pervasive Healthcare System using Android
Abstract— Emerging technologies are transforming the workflows in pervasive healthcare enterprises. Pervasive Healthcare is a one of the developing technology within the pervasive computing paradigm. The presence of pervasive computing, consisting of wireless network gives innovative medium for data transmission of medical applications. We currently use a various wireless technology in healthcare domain. In the existing technology of e-Health has less security of Electronic Medical Records (EMR) and cannot access the medical records in wireless medium. An EMR is a digital version of the traditional paper-based medical record for an each patient’s record. The EMR represents a medical record within a faculty can access the data, such as a doctor or a patient or administration. The accessing of information from the remote database should be high security; it should be a secured access of data by authorized persons. We propose a Pervasive Mobile Healthcare solve these problems and provide user to access the multimedia medical record from anywhere and anytime with security using Elliptical Curve Cryptography(ECC) algorithm, which includes authentication and access control. The authentication is allows the types of users who is authorized to use the application. Security is provided through the process of Encryption and decryption of data. This secured system will provide security in delivering the EMR of patients. Implementation here is done by using Android software and for database MySql is used in Server system. A Wi-Fi enabled mobile is used to receive or transmit the secured medical data as well as image retrieval. The novelty of my application deals with mobility where the users can able to access the secure information. The mobile application develop for real world environment.
IEEE 2013: Cloud Computing For Mobile Users: Can Offloading Computation Save Energy?
Abstract—The cloud heralds a new era of computing where application services are provided through the Internet. Cloud computing can enhance the computing capability of mobile systems, but is it the ultimate solution for extending such systems' battery lifetimes? Cloud computing1 is a new paradigm in which computing resources such as processing, memory, and storage are not physically present at the user’s location. Instead, a service provider owns and manages these resources, and users access them via the Internet. For example, Amazon Web Services lets users store personal data via its Simple Storage Service (S3) and perform computations on stored data using the Elastic Compute Cloud (EC2). This type of computing provides many advantages for businesses—including low initial capital investment, shorter start-up time for new services, lower maintenance and operation costs, higher utilization through virtualization, and easier disaster recovery—that make cloud computing an attractive option. Reports suggest that there are several benefits in shifting computing from the desktop to the cloud.1,2 What about cloud computing for mobile users? The primary constraints for mobile computing are limited energy and wireless bandwidth. Cloud computing can provide energy savings as a service to mobile users, though it also poses some unique challenges.
IEEE 2013: CAM: Cloud-Assisted Privacy Preserving Mobile Health Monitoring
Abstract—Cloud-assisted mobile health (mHealth) monitoring, which applies the prevailing mobile communications and cloud computing technologies to provide feedback decision support, has been considered as a revolutionary approach to improving the quality of healthcare service while lowering the healthcare cost. Unfortunately, it also poses a serious risk on both clients’ privacy and intellectual property of monitoring service providers, which could deter the wide adoption of mHealth technology. This paper is to address this important problem and design a cloud assisted privacy preserving mobile health monitoring system to protect the privacy of the involved parties and their data. Moreover, the outsourcing decryption technique and a newly proposed key private proxy re-encryption are adapted to shift the computational complexity of the involved parties to the cloud without compromising clients’ privacy and service providers’ intellectual property. Finally, our security and performance analysis demonstrates the effectiveness of our proposed design.
IEEE 2013:SPOC: A Secure and Privacy-preserving
Opportunistic Computing Framework for Mobile-Healthcare Emergency
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 opportunisticallygathered 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
IEEE 2013: AMES-Cloud: A Framework of Adaptive Mobile Video Streaming and Efficient Social Video Sharing in the Clouds
Abstract—While demands on video traffic over mobile networks have been souring, the wireless link capacity cannot keep up with the traffic demand. The gap between the traffic demand and the link capacity, along with time-varying link conditions, results in poor service quality of video streaming over mobile networks such as long buffering time and intermittent disruptions. Leveraging the cloud computing technology, we propose a new mobile video streaming framework, dubbed AMES-Cloud, which has two main parts: adaptive mobile video streaming (AMoV) and efficient social video sharing (ESoV). AMoV and ESoV construct a private agent to provide video streaming services efficiently for each mobile user. For a given user, AMoV lets her private agent adaptively adjust her streaming flow with a scalable video coding technique based on the feedback of link quality. Likewise, ESoVmonitors the social network interactions among mobile users, and their private agents try to prefetch video content in advance. We implement a prototype of the AMES-Cloud framework to demonstrate its performance. It is shown that the private agents in the clouds can effectively provide the adaptive streaming, and perform video sharing (i.e., prefetching) based on the social network analysis.
IEEE 2013: Network Assisted Mobile Computing with Optimal Uplink Query Processing
Abstract—Many mobile applications retrieve content from remote servers via user generated queries. Processing these queries is often needed before the desired content can be identified. Processing the request on the mobile devices can quickly sap the limited battery resources. Conversely, processing user-queries at remote servers can have slow response times due communication latency incurred during transmission of the potentially large query. We evaluate a network-assisted mobile computing scenario where midnetwork nodes with “leasing” capabilities are deployed by a service provider. Leasing computation power can reduce battery usage on the mobile devices and improve response times. However, borrowing processing power from mid-network nodes comes at a leasing cost which must be accounted for when making the decision of where processing should occur. We study the tradeoff between battery usage, processing and transmission latency, and mid-network leasing. We use the dynamic programming framework to solve for the optimal processing policies that suggest the amount of processing to be done at each mid-network node in order to minimize the processing and communication latency and processing costs. Through numerical studies, we examine the properties of the optimal processing policy and the core tradeoffs in such systems.
IEEE 2013: Reputation Based Security Model for Android Applications
Abstract—The market for smart phones has been booming in the past few years. There are now over 400,000 applications on the Android market. Over 10 billion Android applications have been downloaded from the Android market. Due to the Android popularity, there are now a large number of malicious vendors targeting the platform. Many honest end users are being successfully hacked on a regular basis. In this work, a cloud based reputation security model has been proposed as a solution which greatly mitigates the malicious attacks targeting the Android market. Our security solution takes advantage of the fact that each application in the android platform is assigned a unique user id (UID). Our solution stores the reputation of Android applications in an anti-malware providers’ cloud (AM Cloud). The experimental results witness that the proposed model could well identify the reputation index of a given application and hence its potential of being risky or not.
IEEE 2013: SPOC: A Secure and Privacy-preserving Opportunistic Computing Framework for Mobile-Healthcare Emergency
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.
IEEE 2012: Music Recommendation Using Content and Context Information Mining
IEEE 2012 Transactions on Intelligent System
Abstract— Mobile devices such as smart phones are becoming popular, and real time access to multimedia data in different environments is getting easier. With properly equipped communication services, users can easily obtain the widely distributed videos, music, and documents they want. Because of its usability and capacity requirements, music is more popular than other types of multimedia data. Documents and videos are difficult to view on mobile phones’ small screens, and videos’ large data size results in high overhead for retrieval. But advanced compression techniques for music reduce the required storage space significantly and make the circulation of music data easier. This means that users can capture their favorite music directly from the Web without going to music stores. Accordingly, helping users find music they like in a large archive has become an attractive but challenging issue over the past few years. Traditional music recommenders have been based primarily on collaborative filtering (CF). But their effectiveness has been limited by insufficient information, including sparse rating data and a lack of contextual information. Sparse rating data occurs frequently in real applications and can result in a distorted recommendation list. In addition, a user’s preferences can vary in different contexts, such as location, time, movement state, and temperature. For example, someone jogging might prefer hip-hop to classical music. A survey showed that activity (a type of context information) significantly affects a listener’s mood.1 This finding delivers an important message that context information is an important element for a music recommender to consider in selecting music to suit the listener’s mood.
IEEE 2012: OPass - A User Authentication Protocol Resistant to Password Stealing and Password Reuse Attacks
IEEE 2012 TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
Abstract—Text password is the most popular form of user authentication on websites due to its convenience and simplicity. However, users’ passwords are prone to be stolen and compromised under different threats and vulnerabilities. Firstly, users often select weak passwords and reuse the same passwords across different websites. Routinely reusing passwords causes a domino effect; when an adversary compromises one password, she will exploit it to gain access to more websites. Second, typing passwords into untrusted computers suffers password thief threat. An adversary can launch several password stealing attacks to snatch passwords, such as phishing, key loggers and malware. In this paper, we design a user authentication protocol named oPass which leverages a user’s cell phone and short message service to thwart password stealing and password reuse attacks. oPass only requires each participating website possesses a unique phone number, and involves a telecommunication service provider in registration and recovery phases. Through oPass, users only need to remember a long-term password for login on all websites. After evaluating the oPass prototype, we believe oPass is efficient and affordable compared with the conventional web authentication mechanisms.
IEEE 2012: Offloading Android Applications to the Cloud without Customizing Android
IEEE 2012 PerCom Workshop on Pervasive Wireless Networking,
Abstract— Spreading more than twice as fast as PCs, smart phones are quickly becoming the primary mean for Internet access. However, smart phones today are still constrained by limited computation resources such as CPU, memory and battery. In this paper, we present a framework that automatically offloads heavy back-end tasks of a regular standalone Android application to an Android virtual machine in the cloud. This framework can be deployed in the application layer without modifying the underlying Android platform. It also features three metrics that consider total response time, energy consumption and remaining battery life in deciding whether a task should be offloaded.
IEEE 2013: Network Assisted Mobile Computing with Optimal Uplink Query Processing
IEEE 2013 Transactions on Mobile Computing,
Abstract— Many mobile applications retrieve content from remote servers via user generated queries. Processing these queries is often needed before the desired content can be identified. Processing the request on the mobile devices can quickly sap the limited battery resources. Conversely, processing user-queries at remote servers can have slow response times due communication latency incurred during transmission of the potentially large query. We evaluate a network-assisted mobile computing scenario where midnetwork nodes with “leasing” capabilities are deployed by a service provider. Leasing computation power can reduce battery usage on the mobile devices and improve response times. However, borrowing processing power from mid-network nodes comes at a leasing cost which must be accounted for when making the decision of where processing should occur. We study the tradeoff between battery usage, processing and transmission latency, and mid-network leasing. We use the dynamic programming framework to solve for the optimal processing policies that suggest the amount of processing to be done at each mid-network node in order to minimize the processing and communication latency and processing costs. Through numerical studies, we examine the properties of the optimal processing policy and the core tradeoffs in such systems.
IEEE 2012: A Flexible Approach to Multi session Trust Negotiations
IEEE 2012 TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
Abstract—Trust Negotiation has shown to be a successful, policy-driven approach for automated trust establishment, rough the release of digital credentials. Current real applications require new flexible approaches to trust negotiations, especially in light of the widespread use of mobile devices. In this paper, we present a multisession dependable approach to trust negotiations. The proposed framework supports voluntary and unpredicted interruptions, enabling the negotiating parties to complete the negotiation despite temporary unavailability of resources. Our protocols address issues related to validity, temporary loss of data, and extended unavailability of one of the two negotiators. A peer is able to suspend an ongoing negotiation and resume it with another (authenticated) peer. Negotiation portions and intermediate states can be safely and privately passed among peers, to guarantee the stability needed to continue suspended negotiations. We present a detailed analysis showing that our protocols have several key properties, including validity, correctness, and minimality. Also, we show how our negotiation protocol can withstand the most significant attacks. As by our complexity analysis, the introduction of the suspension and recovery procedures and mobile negotiations does not significantly increase the complexity of ordinary negotiations. Our protocols require a constant number of messages whose size linearly depend on the portion of trust negotiation that has been carried before the suspensions.
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