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While trawling online/offline password guessing has been intensively studied, only a few studies have examined targeted online guessing, where an attacker guesses a specific victim's password for a service, by exploiting the victim's personal information such as one sister password leaked from her another account and some personally identifiable information (PII). A key challenge for targeted online guessing is to choose the most effective password candidates, while the number of guess attempts allowed by a server's lockout or throttling mechanisms is typically very small.We propose TarGuess, a framework that systematically characterizes typical targeted guessing scenarios with seven sound mathematical models, each of which is based on varied kinds of data available to an attacker. These models allow us to design novel and efficient guessing algorithms. Extensive experiments on 10 large real-world password datasets show the effectiveness of TarGuess. Particularly, TarGuess I∼IV capture the four most representative scenarios and within 100 guesses: (1) TarGuess-I outperforms its foremost counterpart by 142% against security-savvy users and by 46% against normal users; (2) TarGuess-II outperforms its foremost counterpart by 169% on security-savvy users and by 72% against normal users; and (3) Both TarGuess-III and IV gain success rates over 73% against normal users and over 32% against security-savvy users. TarGuess-III and IV, for the first time, address the issue of cross-site online guessing when given the victim's one sister password and some PII.

Remote data integrity checking (RDIC) enables a data storage server, say a cloud server, to prove to a verifier that it is actually storing a data owner's data honestly. To date, a number of RDIC protocols have been proposed in the literature. However, most of the constructions suffer from the issue of requiring complex key management. That is, they rely on the expensive public key infrastructure (PKI), which might hinder the deployment of RDIC in practice. In this paper, we propose a new construction of identity-based (ID-based) RDIC protocol by making use of key-homomorphic cryptographic primitive to reduce the system complexity and the cost for establishing and managing the public key authentication framework in PKI based RDIC schemes. We formalize ID-based RDIC and its security model including security against a malicious cloud server and zero knowledge privacy against a third party verifier. The proposed ID-based RDIC protocol leaks no information of the stored data to the verifier during the RDIC process. The new construction is proven secure against the malicious server in the generic group model and achieves zero knowledge privacy against a verifier. Extensive security analysis and implementation results demonstrate that the proposed protocol is provably secure and practical in the real-world applications. Abstract-Remote data integrity checking (RDIC) enables a data storage server, say a cloud server, to prove to a verifier that it is actually storing a data owner's data honestly. To date, a number of RDIC protocols have been proposed in the literature. However, most of the constructions suffer from the issue of requiring complex key management. That is, they rely on the expensive public key infrastructure (PKI), which might hinder the deployment of RDIC in practice. In this paper, we propose a new construction of identity-based (ID-based) RDIC protocol by making use of key-homomorphic cryptographic primitive to reduce the system complexity and the cost for establishing and managing the public key authentication framework in PKI based RDIC schemes. We formalize ID-based RDIC and its security model including security against a malicious cloud server and zero knowledge privacy against a third party verifier. The proposed ID-based RDIC protocol leaks no information of the stored data to the verifier during the RDIC process. The new construction is proven secure against the malicious server in the generic group model and achieves zero knowledge privacy against a verifier. Extensive security analysis and implementation results demonstrate that the proposed protocol is provably secure and practical in the real-world applications.

Certificate-based encryption was introduced in Eurocrypt'03 to solve the certificate management problem in public key encryption. Recently, this idea was extended to certificate-based signatures. Several new schemes and security models of certificate-based signatures have been proposed. In this paper, we first take a closer look at the certificate-based signature by comparing it with digital signatures in other popular public key systems. We introduce a new security model of certificate-based signature, which defines several new types of adversaries against certificate-based signatures, along with the security model of certificate-based signatures against them. The new model is clearer and more elaborated compared with other existing ones. We then investigate the relationship between certificate-based signatures and certificateless signatures, and propose a generic construction of certificate-based signatures. We prove that the generic construction is secure (in the random oracle model) against all types of adversaries defined in this paper, assuming the underlying certificateless signatures satisfying certain security notions. Based on our generic construction, we are able to construct new certificate-based signature schemes, which are more efficient in comparison with other schemes with similar security levels.

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Fog computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage and application services to end users. In this article, we elaborate the motivation and advantages of Fog computing and analyse its applications in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined networks. We discuss the state of the art of Fog computing and similar work under the same umbrella. Distinguished from other reviewing work of Fog computing, this paper further discloses the security and privacy issues according to current Fog computing paradigm. As an example, we study a typical attack, man-in-the-middle attack, for the discussion of system security in Fog computing. We investigate the stealthy features of this attack by examining its CPU and memory consumption on Fog device. In addition, we discuss the authentication and authorization techniques that can be used in Fog computing. An example of authentication techniques is introduced to address the security scenario where the connection between Fog and Cloud is fragile.In the past few years, Cloud computing has provided many opportunities for enterprises by offering their customers a range of computing services. Current 'pay-as-you-go' Cloud computing model becomes an efficient alternative to owning and managing private data centres for customers facing Web applications and batch processing [8]. Cloud computing frees the enterprises and their end users from the specification of many details, such as storage resources, computation limitation and network communication cost. However, this bliss becomes a problem for latency-sensitive applications, which require nodes in the vicinity to meet their delay requirements [2]. When techniques and devices of IoT are getting more involved in people's life, current Cloud computing paradigm can hardly satisfy their requirements of mobility support, location awareness and low latency.Fog computing is proposed to address the aforementioned problem [1]. As Fog computing is implemented at the edge of the network, it provides low latency, location awareness and improves quality-of-services (QoS) for streaming and real time applications. Typical examples include industrial automation, transportation and networks of sensors and actuators. Moreover, this new infrastructure supports heterogeneity as Fog devices include end-user devices, access points, edge routers and switches. The Fog paradigm is well positioned for real time big data analytics, supports densely distributed data collection points and provides advantages in entertainment, advertising, personal computing and other applications. WHAT CAN WE DO WITH FOG?We elaborate on the role of Fog computing in the following six motivating scenarios. The advantages of Fog computing satisfy the requirements of applications in these scenarios.Smart Grid: Energy load balancing applications may run on network edge devices, such as smart metres and micro-grids [9]. Ba...