Cloud application marketplaces of modern cloud infrastructures offer a new software deployment model, integrated with the cloud environment in its configuration and policies. However, similar to traditional software distribution which has been suffering from software piracy and reverse engineering, cloud marketplaces face the same challenges that can deter the success of the evolving ecosystem of cloud software. We present a novel system named CAFE for cloud infrastructures where sensitive software logic can be executed with high secrecy protected from any piracy or reverse engineering attempts in a virtual machine even when its operating system kernel is compromised. The key mechanism is the end-to-end framework for the execution of applications, which consists of the secure encryption and distribution of confidential application binary files, and the runtime techniques to load, decrypt, and protect the program logic by isolating them from tenant virtual machines based on hypervisor-level techniques. We evaluate applications in several software categories which are commonly offered in cloud marketplaces showing that strong confidential execution can be provided with only marginal changes (around 100-220 lines of code) and minimal performance overhead. The results demonstrate the effectiveness and practicality of CAFE in cloud marketplaces.

Authentication as a Service (AaaS) provides on-demand delivery of multi-factor authentication (MFA). However, current AaaS has left out of consideration the trustworthiness of user inputs at client evices and the risk of privacy exposure at the AaaS providers. To solve these concerns, we present TAaaS, Trustworthy Authentication as a Service, which offers a trusted path-based MFA service to the service provider in the cloud. TAaaS leverages the hypervisor-based trusted path to ensure the trustworthiness of user inputs, and addresses privacy concerns in the cloud by storing only the irreversible user account information. We implement two end-to-end prototypes and evaluate our work to show its feasibility and security.

In wireless broadcast environments, a system performance can be improved with random linear network coding (RLNC). In RLNC, a source transmits a set of coding coefficients and a coded packet together. The coded packet is a combination of the coding coefficients and uncoded packets. Using the key feature of RLNC, we herein propose a new RLNC scheme to minimize outage probability with a feedback channel. In addition, the outage probability of the proposed scheme is analyzed in a Rayleigh fading channel. Through the numerical analysis and Monte Carlo simulations, we demonstrate that the outage probability of the proposed scheme is lower than that of a conventional RLNC scheme.

Intel Software Guard Extensions (SGX) can address the information disclosure in cloud computing. However, the existing virtual machine managers do not provide the efficient management operations of the SGX-enabled virtual machines (VMs) like live migration. In this paper, we identify challenges and propose a novel approach and its implementation model to migrate the SGX-enabled VMs. As future work, we will design the protocol and new instructions for live migration of the SGX-enabled VMs, and implement them on top of OpenSGX, an open source SGX emulator.

Mobile cloud computing requires the efficient approach to access the outsourced data in public clouds due to resource scarceness of mobile devices. To this end, the outsourced data should be protected efficiently from being accessed in plaintext by unauthorized users and public clouds. User revocation should be appropriately managed to guarantee backward secrecy, collusion resistance, and key freshness. In this paper, we present AKMD (Advanced Attribute-based Key Management for Mobile Devices in Hybrid Clouds), an improved key management in hybrid clouds using cipher text-policy attribute-based encryption to allow only authorized users to access the outsourced data stored in public clouds while guaranteeing the efficiency by delegating the key management tasks to private clouds. We introduce new two procedures to handle user revocations, rekey of data encryption keys and policy renewal to support the backward secrecy and key freshness. Our implementation and analysis show that AKMD improves efficiency in security computations and key storage space for mobile devices and guarantees the improved security.

Cloud application marketplaces of modern cloud infrastructures offer a new software deployment model, integrated with the cloud environment in its configuration and policies. However, similar to traditional software distribution which has been suffering from software piracy and reverse engineering, cloud marketplaces face the same challenges that can deter the success of the evolving ecosystem of cloud software. We present a novel system named CAFE for cloud infrastructures where sensitive software logic can be executed with high secrecy protected from any piracy or reverse engineering attempts in a virtual machine even when its operating system kernel is compromised. The key mechanism is the end-to-end framework for the execution of applications, which consists of the secure encryption and distribution of confidential application binary files, and the runtime techniques to load, decrypt, and protect the program logic by isolating them from tenant virtual machines based on hypervisor-level techniques. We evaluate applications in several software categories which are commonly offered in cloud marketplaces showing that strong confidential execution can be provided with only marginal changes (around 100-220 lines of code) and minimal performance overhead.

In cellular networks, proximity users may directly communicate with each other without going through the base station. That is called Device-to-Device (D2D) communication. It has the advantages of improving the spectral efficiency and the power saving of a user equipment (UE). In D2D communication of cellular networks, multiple UEs work together to improve the overall throughput. We call this strategy user-cooperation. User-cooperation is useful method for multiple UEs using the same contents with the high data rate because they are capable of sharing information each other. However, these contents demand the high transmit power for a UE in uplink channel. Therefore, we study user-cooperation schemes based on clustering to minimize the average power consumption of UEs while guaranteeing the high data rate. In this paper, we develop an optimization problem that finds the optimal radius of the cluster to minimize the average power consumption of UEs. Numerical and simulation results show that user-cooperation of the proposed scheme can reduce a large amount of the average power consumption of a UE.

In this paper, we propose a cellular communication system in which base station (BS) uses smart antenna technology. In the system, BS can form multiple beams toward multiple mobile stations (MS) at the same time to serve those MS simultaneously. To support mobility, handover is the most important function. However, in this system, received pilot signal strength of neighbor BS changes according to the direction of the beam. Therefore, we cannot determine handover to the neighbor BS based on only the received pilot signal strength of the neighbor BS. To solve this problem, we propose an optimal handover scheme in which MS handovers directly from the serving beam of the serving BS to target beam of the target BS. However, this handover scheme requires much scanning time. It leads to much longer handover delay which may cause handover failure. Thus, we propose a new suboptimal handover scheme in which handover decision is made based on estimated received signal strength of target beams. Through analysis and simulation results, we show that the proposed suboptimal handover scheme could improve the outage probability performance of the system and require smaller scanning time.

In this paper, we consider a time-varying ad hoc network where nodes communicate cooperatively based on adaptive clustering. When nodes having data become active, each active node wants to construct own cluster with neighboring non-active nodes for cooperative communication. If there exist multi-cluster in the network, each cluster gives (or takes) a different magnitude of interference to (or from) other clusters according to the position and the size of clusters in each time. Hence, each header needs to control the size of own cluster to improve total throughput of the network. To solve this problem, with considering time-varying interference between clusters, the adaptive clustering algorithm and frame structure are proposed to improve the performance.

In a WSN (Wireless Sensor Network), cooperative communications can provide improved energy efficiency which is one of the most important metric given that sensors usually have constrained energy. In this paper, we consider a WSN where sensors operate selfish without centralized entity like as base station. The most of sensors do not tend to help spontaneously data transmission for others in a distributed WSN. We proposed the fair cooperative communication scheme which encourages sensors to participate in cooperative communication by giving some reward. In other words, sensors can participate in the same cluster and help each other to cooperatively transmit data if the following two conditions are satisfied: 1) sensors have a plan to transmit data to nearby area, and 2) sensors are able to decode message coming from a cluster representative. Hence, proposed scheme is more realistic and fair compared with existing scheme which makes sensors to participate in cooperative communication without reward. Moreover, simulation results show that the proposed scheme is more energy efficient than the existing schemes.