Timed-Release of Self-Emerging Data Using Distributed Hash Tables

Releasing private data to the future is a challenging problem. Making private data accessible at a future point in time requires mechanisms to keep data secure and undiscovered so that protected data is not available prior to the legitimate release time and the data appears automatically at the expected release time. In this paper, we develop new mechanisms to support self-emerging data storage that securely hide keys of encrypted data in a Distributed Hash Table (DHT) network that makes the encryption keys automatically appear at the predetermined release time so that the protected encrypted private data can be decrypted at the release time. We show that a straight-forward approach of privately storing keys in a DHT is prone to a number of attacks that could either make the hidden data appear before the prescribed release time (release-ahead attack) or destroy the hidden data altogether (drop attack). We develop a suite of self-emerging key routing mechanisms for securely storing and routing encryption keys in the DHT. We show that the proposed scheme is resilient to both release-ahead attack and drop attack as well as to attacks that arise due to traditional churn issues in DHT networks. Our experimental evaluation demonstrates the performance of the proposed schemes in terms of attack resilience and churn resilience

Emerge: Self-Emerging Data Release Using Cloud Data Storage

In the age of Big Data, advances in distributed technologies and cloud storage services provide highly efficient and cost-effective solutions to large scale data storage and management. Supporting self-emerging data using clouds is a challenging problem. While straight-forward centralized approaches provide a basic solution to the problem, unfortunately they are limited to a single point of trust. Supporting attack-resilient timed release of encrypted data stored in clouds requires new mechanisms for self emergence of data encryption keys that enables encrypted data to become accessible at a future point in time. Prior to the release time, the encryption key remains undiscovered and unavailable in a secure distributed system, making the private data unavailable. In this paper, we propose Emerge, a self-emerging timed data release protocol for securely hiding data encryption keys of private encrypted data in a large-scale Distributed Hash Table (DHT) network that makes the data available and accessible only at the defined release time. We develop a suite of erasure-coding-based routing path construction schemes for securely storing and routing encryption keys in DHT networks that protect an adversary from inferring the encryption key prior to the release time (release-ahead attack) or from destroying the key altogether (drop attack). Through extensive experimental evaluation, we demonstrate that the proposed schemes are resilient to both release-ahead attack and drop attack as well as to attacks that arise due to traditional churn issues in DHT networks

Decentralized Privacy-preserving Timed Execution in Blockchain-based Smart Contract Platforms

Timed transaction execution is critical for various decentralized privacy-preserving applications powered by blockchain-based smart contract platforms. Such privacy-preserving smart contract applications need to be able to securely maintain users' sensitive inputs off the blockchain until a prescribed execution time and then automatically make the inputs available to enable on-chain execution of the target function at the execution time, even if the user goes offline. While straight-forward centralized approaches provide a basic solution to the problem, unfortunately they are limited to a single point of trust. This paper presents a new decentralized privacy-preserving transaction scheduling approach that allows users of Ethereum-based decentralized applications to schedule transactions without revealing sensitive inputs before an execution time window selected by the users. The proposed approach involves no centralized party and allows users to go offline at their discretion after scheduling a transaction. The sensitive inputs are privately maintained by a set of trustees randomly selected from the network enabling the inputs to be revealed only at the execution time. The proposed protocol employs secret key sharing and layered encryption techniques and economic deterrence models to securely protect the sensitive information against possible attacks including some trustees destroying the sensitive information or secretly releasing the sensitive information prior to the execution time. We demonstrate the attack-resilience of the proposed approach through rigorous analysis. Our implementation and experimental evaluation on the Ethereum official test network demonstrates that the proposed approach is effective and has a low gas cost and time overhead associated with it

Protecting data privacy with decentralized self-emerging data release systems

In the age of Big Data, releasing private data at a future point in time is critical for various applications. Such self-emerging data release requires the data to be protected until a prescribed data release time and be automatically released to the target recipient at the release time. While straight-forward centralized approaches such as cloud storage services may provide a simple way to implement self-emerging data release, unfortunately, they are limited to a single point of trust and involves a single point of control. This dissertation proposes new decentralized designs of self-emerging data release systems using large-scale peer-to-peer (P2P) networks as the underlying infrastructure to eliminate a single point of trust or control. The first part of the dissertation presents the design of decentralized self-emerging data release systems using two different P2P network infrastructures, namely Distributed Hash Table (DHT) and blockchain. The second part of this dissertation proposes new mechanisms for supporting two key functionalities of self-emerging data release, namely (i) enabling the release of self-emerging data to blockchain-based smart contracts for facilitating a wide range of decentralized applications and (ii) supporting a cost-effective gradual release of self-emerging data in the decentralized infrastructure. We believe that the outcome of this dissertation would contribute to the development of decentralized security primitives and protocols in the context of timed release of private data

Decentralized Release of Self-emerging Data using Smart Contracts

In the age of Big Data, releasing protected sensitive data at a future point in time is critical for various applications. Such self-emerging data release requires the data to be protected until a prescribed data release time and be automatically released to the recipient at the release time, even if the data sender goes offline. While straight-forward centralized approaches provide a basic solution to the problem, unfortunately they are limited to a single point of trust and involve a single point of control. This paper presents decentralized techniques for supporting self-emerging data using smart contracts in Ethereum blockchain networks. We design a credible and enforceable smart contract for supporting self-emerging data release. The smart contract employs a set of Ethereum peers to jointly follow the proposed timed-release service protocol allowing the participating peers to earn the remuneration paid by the service users.We model the problem as an extensive-form game with imperfect information to protect against possible adversarial attacks including some peers destroying the private data (drop attack) or secretly releasing the private data before the release time (release-ahead attack). We demonstrate the efficacy and attack-resilience of the proposed techniques through rigorous analysis and experimental evaluation. Our implementation and experimental evaluation on the Ethereum official test network demonstrate the low monetary cost and the low time overhead associated with the proposed approach and validate its guaranteed security properties

Airborne Network Data Availability Using Peer to Peer Database Replication on a Distributed Hash Table

The concept of distributing one complex task to several smaller, simpler Unmanned Aerial Vehicles (UAVs) as opposed to one complex UAV is the way of the future for a vast number of surveillance and data collection tasks. One objective for this type of application is to be able to maintain an operational picture of the overall environment. Due to high bandwidth costs, centralizing all data may not be possible, necessitating a distributed storage system such as mobile Distributed Hash Table (DHT). A difficulty with this maintenance is that for an Airborne Network (AN), nodes are vehicles and travel at high rates of speed. Since the nodes travel at high speeds they may be out of contact with other nodes and their data becomes unavailable. To address this the DHT must include a data replication strategy to ensure data availability. This research investigates the percentage of data available throughout the network by balancing data replication and network bandwidth. The DHT used is Pastry with data replication using Beehive, running over an 802.11 wireless environment, simulated in Network Simulator 3. Results show that high levels of replication perform well until nodes are too tightly packed inside a given area which results in too much contention for limited bandwidth

Using Timed-Release Cryptography to Mitigate Preservation Risk of Embargo Periods

This research defines Time-Locked Embargo, a framework designed to mitigate the Preservation Risk Interval: the preservation risk associated with embargoed scholarly material. Due to temporary access restrictions, embargoed data cannot be distributed freely and thus preserved via data refreshing during the embargo time interval. A solution to mitigate the risk of data loss has been developed by suggesting a data dissemination framework that allows data refreshing of encrypted instances of embargoed content in an open, unrestricted scholarly community. This framework has been developed by exploiting implementations of existing technologies to time-lock data using Timed-Release Cryptology (TRC) so that it can be deployed s digital resources encoded in the MPEG-21 Digital Item Description Language (DIDL) complex object format to harvesters interested in harvesting a local copy of content by utilizing The Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH), a widely accepted interoperability standard for the exchange of metadata. The framework successfully demonstrates dynamic record identification, time-lock puzzle (TLP) encryption, encapsulation and dissemination as XML documents. This thesis dissertation presents the framework architecture and provides a quantitative analysis of an implementation. The framework demonstrates successful data harvest of time-locked embargoed data with minimum time overhead without compromising data security and integrity