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Abstract In this paper, we propose a framework for lightning-fast privacy-preserving outsourced computation framework in the cloud, which we refer to as LightCom. Using LightCom, a user can securely achieve the outsource data storage and fast, secure data processing in a single cloud server different from the existing multi-server outsourced computation model. Specifically, we first present a general secure computation framework for LightCom under the cloud server equipped with multiple Trusted Processing Units (TPUs), which face the side-channel attack. Under the LightCom, we design two specified fast processing toolkits, which allow the user to achieve the commonly-used secure integer computation and secure floating-point computation against the side-channel information leakage of TPUs, respectively. Furthermore, our LightCom can also guarantee access pattern protection during the data processing and achieve private user information retrieve after the computation. We prove that the proposed LightCom can successfully achieve the goal of single cloud outsourced data processing to avoid the extra computation server and trusted computation server, and demonstrate the utility and the efficiency of LightCom using simulations.

Abstract Wearing smartwatches becomes increasingly popular in people’s lives. This paper shows that a smartwatch can help its bearer authenticate to a login system effectively and securely even if the bearer’s password has already been revealed. This idea is motivated by our observation that a sensor-rich smartwatch is capable of tracking the wrist motions of its bearer typing a password or PIN, which can be used as an authentication factor. The major challenge in this research is that a sophisticated attacker may imitate a user’s typing behavior as shown in previous research on keystroke dynamics based user authentication. We address this challenge by applying a set of machine learning and deep learning classifiers on the user’s wrist motion data that are collected from a smartwatch worn by the user when inputting his/her password or PIN. Our solution is user-friendly since it does not require users to perform any additional actions when typing passwords or PINs other than wearing smartwatches. We conduct a user study involving 51 participants so as to evaluate the feasibility and performance of our solution. User study results show that the best classifier is the Bagged Decision Trees, which yields 4.58% FRR and 0.12% FAR on a QWERTY keyboard, and 6.13% FRR and 0.16% FAR on a numeric keypad.

As a very attractive computing paradigm, cloud computing makes it possible for resource-constrained users to enjoy cost-effective and flexible resources of diversity. Considering the untrustworthiness of cloud servers and the data privacy of users, it is necessary to encrypt the data before outsourcing it to the cloud. However, the form of encrypted storage also poses a series of problems, such as: How can users search over the outsourced data? How to realize user-side verifiability of search results to resist malicious cloud servers? How to enable server-side verifiability of outsourced data to check malicious data owners? How to achieve payment fairness between the user and the cloud without introducing any third party? Towards addressing these challenging issues, in this paper, we introduce TKSE, a trustworthy keyword search scheme over encrypted data without any third party, trusted or not. In TKSE, the encrypted data index based on digital signature allows a user to search over the outsourced encrypted data and check whether the search result returned by the cloud fulfills the pre-specified search requirements. In particular, for the first time, TKSE realizes server-side verifiability which protects honest cloud servers from being framed by malicious data owners in the data storage phase. Furthermore, blockchain technologies and hash functions are used to enable payment fairness of search fees without introducing any third party even if the user or the cloud is malicious. Our security analysis and performance evaluation indicate that TKSE is secure and efficient and it is suitable for cloud computing.

Equipped with various sensors and intelligent systems, modern cars turn into entities with connectivity, autonomy, and safety. Car rental/car sharing is an innovative transportation concept and integral in today's urban living. It enables users to access a fleet of vehicles located throughout cities. Complementing public transportation, the car-sharing service helps people to meet their transportation needs economically and in an environmentally responsible manner. When a customer wants to rent a car from a rental company or an owner wants to share a private car with his/her friends or family members, the customer or the user should gain admission to the car, such as unlocking the door and starting the engine. In this paper, we proposed a novel and secure key-sharing system named hierarchical identity-based signature key sharing (HIBS-KSharing), which consists of key generation, key transmission, and key management (e.g., remote issuing, revocation of access rights, and their delegation to other users or sharers). We implemented our proposed system based on Nexus smartphones and near-field communication devices. Compared with existing key-sharing schemes of car rental/sharing, our proposed HIBS-KSharing system is secure and easily extended.

Current host-centric Internet Protocol (IP) networks are facing unprecedented challenges, such as network attacks and the exhaustion of IP addresses. Motivated by emerging demands for security, mobility, and distributed networking, many research projects have been initiated to design the future Internet from a clean slate. In order to obtain a thorough knowledge of security in future Internet architecture, we review a number of well-known projects, including named data networking, Content Aware Searching Retrieval and sTreaming, MobilityFirst Future Internet Architecture Project (MobilityFirst), eXpressive Internet Architecture, and scalability, control, and isolation on next-generation network. These projects aim to move away from the traditional host-centric networks and replace them with content-centric, mobility-centric, or service-centric networks. However, different principles and designs also raise various issues on network security. For each project, we describe its architecture design and how it deals with security issues. Furthermore, we compare these projects and discuss their pros and cons. Open security issues are pointed out for directing future research.

Nowadays, more and more multimedia websites appear in social network. It brings some security problems, such as privacy, piracy, disclosure of sensitive contents and so on. Aiming at copyright protection, the copy detection technology of multimedia contents becomes a hot topic. In our previous work, a new computer-based copyright control system used to detect the media has been proposed. Based on this system, this paper proposes an improved media feature matching measure and an entropy based copy detection method. The Levenshtein Distance was used to enhance the matching degree when using for feature matching measure in copy detection. For entropy based copy detection, we make a fusion of the two features of entropy matrix of the entropy feature we extracted. Firstly,we extract the entropy matrix of the image and normalize it. Then, we make a fusion of the eigenvalue feature and the transfer matrix feature of the entropy matrix. The fused features will be used for image copy detection. The experiments show that compared to use these two kinds of features for image detection singly, using feature fusion matching method is apparent robustness and effectiveness. The fused feature has a high detection for copy images which have been received some attacks such as noise, compression, zoom, rotation and so on. Comparing with referred methods, the method proposed is more intelligent and can be achieved good performance.