On Implementing Deniable Storage Encryption for Mobile Devices

Data confidentiality can be effectively preserved through encryption. In certain situations, this is inadequate, as users may be coerced into disclosing their decryption keys. In this case, the data must be hidden so that its very existence can be denied. Steganographic techniques and deniable encryption algorithms have been devised to address this specific problem. Given the recent proliferation of smartphones and tablets, we examine the feasibility and efficacy of deniable storage encryption for mobile devices. We evaluate existing, and discover new, challenges that can compromise plausibly deniable encryption (PDE) in a mobile environment. To address these obstacles, we design a system called Mobiflage that enables PDE on mobile devices by hiding encrypted volumes within random data on a device’s external storage. We leverage lessons learned from known issues in deniable encryption in the desktop environment, and design new countermeasures for threats specific to mobile systems. Key features of Mobiflage include: deniable file systems with limited impact on throughput; efficient storage use with no data expansion; and restriction/prevention of known sources of leakage and disclosure. We provide a proof-of-concept implementation for the Android OS to assess the feasibility and performance of Mobiflage. We also compile a list of best practices users should follow to restrict other known forms of leakage and collusion that may compromise deniability

On implementing deniable storage encryption for mobile devices

Abstrac

A Protected And Lightweight Data Distribution Program For Mobile Cloud Computing

Because of the widespread adoption of cloud computing, mobile devices may now store and access personal data from any location at any time. As a result, the data security issue in mobile cloud is becoming increasingly serious, impeding the growth of mobile cloud. There have been several researches undertaken in order to enhance cloud security. However, because mobile devices have limited processing capabilities and power, the majority of them are not suitable for mobile cloud. Mobile cloud applications require solutions with a low computational overhead. We propose a lightweight data sharing mechanism for mobile cloud computing in this work. It provides attribute description fields to achieve lazy-revocation, which is a difficult problem in CP-ABE systems based on programs. The experimental findings suggest that when users share data in mobile cloud settings, a lightweight data sharing technique may effectively minimize the overhead on the mobile device side

A New LDSS for Mobile Cloud Computing

We suggest a lightweight data sharing scheme (LDSS) for mobile cloud computing. It adopts CP-ABE, an access control innovation utilized as a part of ordinary cloud condition, yet changes the structure of access control tree to make it appropriate for portable cloud situations. LDSS moves a huge part of the computational serious access control tree change in CP-ABE from cell phones to outer intermediary servers. Moreover, to decrease the client repudiation cost, it acquaints trait portrayal fields with actualize languid renouncement, which is a prickly issue in program based CP-ABE frameworks

A LDSS-CP-ABE Algorithm to Migrate Major Computation Overhead from Mobile Devices on to Proxy Server

Cloud has hugequantity of resources. In such a situation, to attain the acceptable presentation, it is indispensable to usage the possessionsdelivered by the cloud service provider (CSP) to stock and segment the data. At the moment, many cloud mobile claims have been extensivelycastoff. In these claims, data owners can upload their photos, videos, documents and other files to the cloud and segment these data with other data users they like to stake.  Explanations with stumpy computational overhead are in prodigious need for mobile cloud applications. In this paper, we recommend a lightweight data sharing scheme (LDSS) for mobile cloud computing.  The investigational results show that LDSS can confirm data concealment in mobile cloud and decrease the overhead on users’ side in mobile cloud

An Empirical Study on Android for Saving Non-shared Data on Public Storage

With millions of apps that can be downloaded from official or third-party market, Android has become one of the most popular mobile platforms today. These apps help people in all kinds of ways and thus have access to lots of user's data that in general fall into three categories: sensitive data, data to be shared with other apps, and non-sensitive data not to be shared with others. For the first and second type of data, Android has provided very good storage models: an app's private sensitive data are saved to its private folder that can only be access by the app itself, and the data to be shared are saved to public storage (either the external SD card or the emulated SD card area on internal FLASH memory). But for the last type, i.e., an app's non-sensitive and non-shared data, there is a big problem in Android's current storage model which essentially encourages an app to save its non-sensitive data to shared public storage that can be accessed by other apps. At first glance, it seems no problem to do so, as those data are non-sensitive after all, but it implicitly assumes that app developers could correctly identify all sensitive data and prevent all possible information leakage from private-but-non-sensitive data. In this paper, we will demonstrate that this is an invalid assumption with a thorough survey on information leaks of those apps that had followed Android's recommended storage model for non-sensitive data. Our studies showed that highly sensitive information from billions of users can be easily hacked by exploiting the mentioned problematic storage model. Although our empirical studies are based on a limited set of apps, the identified problems are never isolated or accidental bugs of those apps being investigated. On the contrary, the problem is rooted from the vulnerable storage model recommended by Android. To mitigate the threat, we also propose a defense framework

Ensuring data confidentiality via plausibly deniable encryption and secure deletion – a survey

Ensuring confidentiality of sensitive data is of paramount importance, since data leakage may not only endanger dataowners’ privacy, but also ruin reputation of businesses as well as violate various regulations like HIPPA andSarbanes-Oxley Act. To provide confidentiality guarantee, the data should be protected when they are preserved inthe personal computing devices (i.e.,confidentiality duringtheirlifetime); and also, they should be rendered irrecoverableafter they are removed from the devices (i.e.,confidentiality after their lifetime). Encryption and secure deletion are usedto ensure data confidentiality during and after their lifetime, respectively.This work aims to perform a thorough literature review on the techniques being used to protect confidentiality of thedata in personal computing devices, including both encryption and secure deletion. Especially for encryption, wemainly focus on the novel plausibly deniable encryption (PDE), which can ensure data confidentiality against both acoercive (i.e., the attacker can coerce the data owner for the decryption key) and a non-coercive attacker

SoK: Plausibly Deniable Storage

Data privacy is critical in instilling trust and empowering the societal pacts of modern technology-driven democracies. Unfortunately, it is under continuous attack by overreaching or outright oppressive governments, including some of the world\u27s oldest democracies. Increasingly-intrusive anti-encryption laws severely limit the ability of standard encryption to protect privacy. New defense mechanisms are needed. Plausible deniability (PD) is a powerful property, enabling users to hide the existence of sensitive information in a system under direct inspection by adversaries. Popular encrypted storage systems such as TrueCrypt and other research efforts have attempted to also provide plausible deniability. Unfortunately, these efforts have often operated under less well-defined assumptions and adversarial models. Careful analyses often uncover not only high overheads but also outright security compromise. Further, our understanding of adversaries, the underlying storage technologies, as well as the available plausible deniable solutions have evolved dramatically in the past two decades. The main goal of this work is to systematize this knowledge. It aims to: - identify key PD properties, requirements, and approaches; - present a direly-needed unified framework for evaluating security and performance; - explore the challenges arising from the critical interplay between PD and modern system layered stacks; - propose a new trace-oriented PD paradigm, able to decouple security guarantees from the underlying systems and thus ensure a higher level of flexibility and security independent of the technology stack. This work is meant also as a trusted guide for system and security practitioners around the major challenges in understanding, designing, and implementing plausible deniability into new or existing systems

Deniable Storage Encryption for Mobile Devices

Smartphones, and other mobile computing devices, are being widely adopted globally as the de-facto personal computing platform. Given the amount of sensitive information accumulated by these devices, there are serious privacy and security implications for both personal use and enterprise deployment. Confidentiality of data-at-rest can be effectively preserved through storage encryption. All major mobile OSes now incorporate some form of storage encryption. In certain situations, this is inadequate, as users may be coerced into disclosing their decryption keys. In this case, the data must be hidden so that its very existence can be denied. Steganographic techniques and deniable encryption algorithms have been devised to address this specific problem. This dissertation explores the feasibility and efficacy of deniable storage encryption for mobile devices. A feature that allows the user to feign compliance with a coercive adversary, by decrypting plausible and innocuous decoy data, while maintaining the secrecy of their sensitive or contentious hidden data. A deniable storage encryption system, Mobiflage, was designed and implemented for the Android OS, the first such application for mobile devices. Current mobile encryption mechanisms all rely, in some way, on a user secret. Users notoriously choose weak passwords that are easily guessed/cracked. This thesis offers a new password scheme for use with storage encryption. The goal is to create passwords that are suitably strong for protection of encryption keys, easier to input on mobile devices, and build on memorability research in cognitive psychology for a better user experience than current password guidelines