Substring search over encrypted data

Our data, be it personal or professional, is increasingly outsourced. This results from the development of cloud computing in the past ten years, a paradigm that shifts computing to a utility. Even without realizing it, cloud computing has entered our lives inexorably: every owner of a smartphone, every user of a social network is using cloud computing, as most IT companies and tech giants in particular are using infrastructure as a service to offer services in the model of software as a service. These services (dropbox, google, facebook, twitter...) are simple to use, flexible...and free! Users just send their data and they get all services without paying. Actually, these companies are making most of their revenues by profiling the users thanks to the data that the users willingly provide. The data is the indirect payment to benefit from these services. This raises privacy concerns at the personal level, as well as confidentiality issues for sensitive documents in a professional environment. The classical way of dealing with confidentiality is to conceal the data through encryption. However, cloud providers need access to data in order to provide useful services, not only to profile users. Take a cloud email service as example, where the emails are stored and archived in the cloud and only downloaded to the user's phone or computer when the user wants to read them. If the emails are encrypted in the cloud, the cloud cannot access them and confidentiality is enforced. However, the cloud can also not provide any useful service to the user such as a search functionality over emails. To meet these conflicting requirements (hiding the data and accessing the data) a solution is to develop mechanisms that allow computation on encrypted data. While generic protocols for computation on encrypted data have been researched developed, such as Gentry's breakthrough fully homomorphic encryption, their performance remains unsatisfactory. On the contrary, tailoring solutions to specific needs result in more practical and efficient solution. In the case of searching over encrypted data, searchable encryptions algorithms have been developed for over decade and achieve now satisfactory performance (linear in the size of the dictionary). Most of the work in this field focus on single keyword search in the symmetric setting. To overcome this limitation, we first proposed a scheme based on letter orthogonalization that allows testing of string membership by performing efficient inner products (AsiaCCS 2013). Going further, we now propose a general solution to the problem of efficient substring search over encrypted data. The solution enhances existing "keyword" searchable encryption schemes by allowing searching for any part of encrypted keywords without requiring one to store all possible combinations of substrings from a given dictionary. The proposed technique is based on the previous idea of letter orthogonalization. We first propose SED-1, the base protocol for substring search. We then identify some attacks on SED-1 that demonstrate the complexity of the substring search problem under different threat scenarios. This leads us to propose our second and main protocol SED-2. The protocol is also efficient in that the search complexity is linear in the size of the keyword dictionary. We run several experiments on a sizeable real world dataset to evaluate the performance of our protocol. This final work has been accepted for publication in the IOS journal of computer security https://content.iospress.com/articles/journal-of-computer-security/jcs14652.qscienc

A novel hybrid methodology to secure GOOSE messages against cyberattacks in smart grids

: IEC 61850 is emerging as a popular communication standard for smart grids. Standardized communication in smart grids has an unwanted consequence of higher vulnerability to cyber-attacks. Attackers exploit the standardized semantics of the communication protocols to launch different types of attacks such as false data injection (FDI) attacks. Hence, there is a need to develop a cybersecurity testbed and novel mitigation strategies to study the impact of attacks and mitigate them. This paper presents a testbed and methodology to simulate FDI attacks on IEC 61850 standard compliant Generic Object-Oriented Substation Events (GOOSE) protocol using real time digital simulator (RTDS) together with open-source tools such as Snort and Wireshark. Furthermore, a novel hybrid cybersecurity solution by the name of sequence content resolver is proposed to counter such attacks on the GOOSE protocol in smart grids. Utilizing the developed testbed FDI attacks in the form of replay and masquerade attacks on are launched and the impact of attacks on electrical side is studied. Finally, the proposed hybrid cybersecurity solution is implemented with the developed testbed and its effectiveness is demonstrated

The FfF_f-Family of Protocols for RFID-Privacy and Authentication

In this paper, we present the design of the lightweight $F_f$ family of privacy-preserving authentication protocols for RFID-systems. $F_f$ is based on a new algebraic framework for reasoning about and analyzing this kind of authentication protocols. $F_f$ offers user-adjustable, strong authenticity and privacy against known algebraic and also recent SAT-solving attacks. In contrast to related work, $F_f$ achieves these two security properties without requiring an expensive cryptographic hash function. $F_f$ is designed for a challenge-response protocol, where the tag sends random nonces and the results of HMAC-like computations of one of the nonces together with its secret key. In this paper, the authenticity and privacy of $F_f$ is evaluated using analytical and experimental methods

Privacy-enhanced social-network routing

This work is supported by the UK Engineering and Physical Sciences Research Council and the Technology Strategy Board as part of the Privacy Value Networks project, EP/G002606/1.Opportunistic networking—forwarding messages in a disconnected mobile ad hoc network via any encountered nodes — offers a new mechanism for exploiting the mobile devices that many users now carry. Forwarding messages in such a network often involves the use of social-network routing— sending messages via nodes in the sender or recipient’s friends list. Simple social-network routing, however, may broadcast these friends lists, which introduces privacy concerns. This paper presents a threat analysis of the privacy risks in social-network routing. We introduce two complementary methods for enhancing privacy in social-network routing by obfuscating the friends lists used to inform routing decisions. We evaluate these methods using three real-world datasets, and find that it is possible to obfuscate the friends lists without leading to a significant decrease in routing performance, as measured by delivery cost, delay and ratio. We quantify the increase in security provided by this obfuscation, with reference to classes of attack which are mitigated.PreprintPeer reviewe

Facebook or Fakebook? : The effects of simulated mobile applications on simulated mobile networks

This work was supported by the Engineering and Physical Sciences Research Council [grant number EP/G002606/1].The credibility of mobile ad hoc network simulations depends on accurate characterisations of user behaviour, e.g., mobility and application usage. If simulated nodes communicate at different rates to real nodes, or move in an unrealistic fashion, this may have a large impact on the network protocols being simulated and tested. Many future mobile network protocols, however, may also depend on future mobile applications. Different applications may be used at different rates or in different manners. But how can we determine realistic user behaviour for such applications that do not yet exist? One common solution is again simulation, but this time simulation of these future applications. This paper examines differences in user behaviour between a real and simulated mobile social networking application through a user study (n=80). We show that there are distinct differences in privacy behaviour between the real and simulated groups. We then simulate a mobile opportunistic network application using two real-world traces to demonstrate the impact of using real and simulated applications. We find large differences between using real and synthetic models of privacy behaviour, but smaller differences between models derived from the real and simulated applications.PostprintPeer reviewe