Project Code: RBA100
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 Smart Class, which allows the programmers to solve this problem using web services. By introducing service-oriented architecture (SOA), Smart Class is able to provide classroom scheduling services with back-stage design space exploration and greedy algorithms. Furthermore, the Smart Class architecture can be dynamically coupled to different scheduling algorithms to fit in specific demands. A typical case study demonstrates that Smart Class 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 Smart Class has lower scheduling overheads with higher efficiency

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Project Code: RBA101
Abstract: In cloud service over crowd-sensing data, the data owner (DO) publishes the sensing data through the cloud server, so that the user can obtain the information of interest on demand. But the cloud service providers (CSP) are often untrustworthy. The privacy and security concerns emerge over the authenticity of the query answer and the leakage of the DO identity. To solve these issues, many researchers study the query answer authentication scheme for cloud service system. The traditional technique is providing DO’s signature for the published data. But the signature would always reveal DO’s identity. To deal with this disadvantage, this paper proposes a cooperative query answer authentication scheme, based on the ring signature, the Merkle hash tree (MHT) and the non-reputable service protocol. Through the cooperation among the entities in cloud service system, the proposed scheme could not only verify the query answer but also protect the DO’s identity. First, it picks up the internal nodes of MHT to sign, as well as the root node. Thus, the verification computation complexity could be significantly reduced from O(log2N) to O(log2N0.5 ) in the best case. Then it improves an existing ring signature to sign the selected nodes. Furthermore, the proposed scheme employs the non-repudiation protocol during the transmission of query answer and verification object (VO) to protect trading behavior between the CSP and users. The security and performance analysis prove the security and feasibility of the proposed scheme. Extensive experimental results demonstrate its superiority of verification efficiency and communication overhead.

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Project Code: RBA102
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.

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Project Code: RBA103
Abstract: The convergence of mobile communications and cloud computing facilitates the cross-layer network design and content-assisted communication. Mobile video broadcasting can benefit from this trend by utilizing joint source-channel coding and strong information correlation in clouds. In this paper, a knowledge-enhanced mobile video broadcasting (KMV-Cast) is proposed. The KMV-Cast is built on a linear video transmission instead of traditional digital video system, and exploits the hierarchical Bayesian model to integrate the correlated information into the video reconstruction at the receiver. The correlated information is distilled to obtain its intrinsic features, and the Bayesian estimation algorithm is used to maximize the video quality. The KMV-Cast system consists of both likelihood broadcasting and prior knowledge broadcasting. The simulation results show that the proposed KMV-Cast scheme outperforms the typical linear video transmission scheme called Softcast, and achieves 8dB more of the peak signal-to-noise ratio (PSNR) gain at low-SNR channels (i.e., -10dB), and 5dB more of PSNR gain at high-SNR channels (i.e., 25dB). Compared to traditional digital video system, the proposed scheme has 7dB more of PSNR gain than JPEG2000+802.11a scheme at 10dB channel SNR.

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Project Code: RBA104
Abstract: Location Based Services (LBS) have seen alarming privacy breaches in recent years. While there has been much recent progress by the research community on developing privacy-enhancing mechanisms for LBS, their evaluation has been often focused on the privacy guarantees, while the question of whether these mechanisms can be adopted by practical LBS applications has received limited attention. This paper studies the applicability of Privacy-Preserving Location Proximity (PPLP) protocols in the setting of mobile apps. We categorize popular location social apps and analyze the tradeoffs of privacy and functionality with respect to PPLP enhancements. To investigate the practical performance trade-offs, we present an in-depth case study of an Android application that implements InnerCircle, a state-of-the-art protocol for privacypreserving location proximity. This study indicates that the performance of the privacy-preserving application for coarse-grained precision is comparable to real applications with the same feature set.

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Project Code: RBA105
Abstract: Android, the most popular mobile OS, has around 78 % of the mobile market share. Due to its popularity, it attracts many malware attacks. In fact, people have discovered around one million new malware samples per quarter, and it was reported that over 98 % of these new malware samples are in fact “derivatives” (or variants) from existing malware families. In this paper, we first show that runtime behaviors of malware’s core functionalities are in fact similar within a malware family. Hence, we propose a framework to combine “runtime behavior” with “static structures” to detect malware variants. We present the design and implementation of MONET, which has a client and a backend server module. The client module is a lightweight, in device app for behavior monitoring and signature generation, and we realize this using two novel interception techniques. The backend server is responsible for large scale malware detection. We collect 3723 malware samples and top 500 benign apps to carry out extensive experiments of detecting malware variants and defending against malware transformation. Our experiments show that MONET can achieve around 99 % accuracy in detecting malware variants. Furthermore, it can defend against 10 different obfuscation and transformation techniques, while only incurs around 7 % performance overhead and about 3 % battery overhead. More importantly, MONET will automatically alert users with intrusion details so to prevent further malicious behaviors.

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Project Code: RBA106
Abstract: Authenticated key exchange (AKE) is one of the most important applications in applied cryptography, where a user interacts with a server to set up a session key where pre-registered information (aka. authentication factor), such as a password or biometrics, of the user is stored. While single-factor AKE is widely used in practice, higher security concerns call for multi-factor AKE (MFAKE) schemes, e.g. combining both passwords and biometrics simultaneously. However, in some casually designed schemes, security is even weakened in the sense that leakage of one authentication factor will defeat the whole MFAKE protocol. Furthermore, an inevitable by-product arise that the usability of the protocol often drop greatly. To summarize, the existing multi-factor protocols did not provide enough security and efficiency simultaneously. In this paper, we make one step ahead by proposing a very efficient MFAKE protocol. We define the security model and give the according security analysis. We also implement our protocol on a smartphone and a cloud server. The theoretic comparisons and the experimental results show that our scheme achieves both security and usability

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