To address data rights and trust issues, we develop fundamental technologies that leverage blockchain as a large-scale data analysis platform, ensuring data integrity, ownership, and availability. This paper outlines the design and implementation of our envisioned blockchain data analysis platform.

Unmanned Vehicles (UVs) have been being utilized for various applications, such as surveillance, search/rescue, and monitoring. The information they transmit is critical for decision-making. However, UVs are vulnerable to white-box attacks due to improvements in reverse engineering techniques and the openness of their software. Therefore, attackers with sufficient knowledge of a target UV can steal secret information stored in the UV by exploiting its vulnerabilities. Recently, several white-box cryptography techniques have been introduced to protect secret keys from being extracted by converting them into large look-up tables. However, none of them provide approaches to securely update the look-up tables. Thus, once a remote attacker succeeds in extracting the static look-up table from a UV, he/she can use it to decrypt past/future communications or to send false information to the control station by impersonating the UV. In this paper, we propose a look-up table shuffling mechanism that supports white-box cryptography with dynamics. The mechanism makes it hard for attackers to determine the positions of the table entries, and thus to decrypt/encrypt ciphertexts/plaintexts. To show the practicality of the block cipher with our mechanism, we implemented it on a board equipped with a GPU and show its GPU-accelerated performance.

Many localization techniques for wireless sensor networks have been proposed to estimate sensor positions even when there is malicious location information which distorts the estimate. Some of those solutions efficiently estimate sensor positions using the Minimum Mean Square Estimation methods and the Degree-Of-Consistency (DOC). Although such solutions can filter out most of malicious information, if an attacker knows the position of the target sensor, the attacker can significantly alter its estimated position. In this paper, we introduce two attacks based on the knowledge of target sensor positions. The first attack, called Aligned-Beacon-Position (ABP) attack, exploits beacon nodes that are aligned in a line. The second attack, called inside-attack, disables the DOC filtering algorithm by placing malicious location references inside benign location references. To protect against those two known sensor position attacks, we introduce two defense schemes. First, we propose a novel beacon placement strategy to protect against ABP attacks. Second, we present a filtering technique that can filter out malicious location references introduced by inside-attacks. Finally, we propose a localization algorithm which has enhanced accuracy and efficiency compared with previous algorithms. We assess the impact of those attacks and the performance of our defense schemes by simulation and test-bed experiments.

Several solutions have recently been proposed to securely estimate sensor positions even when there is malicious location information which distorts the estimate. Some of those solutions are based on the Minimum Mean Square Estimation (MMSE) methods which efficiently estimate sensor positions. Although such solutions can filter out most of malicious information, if an attacker knows the position of a target sensor, the attacker can significantly alter the position information. In this paper, we introduce such a new attack, called Inside-Attack, and a technique that is able to detect and filter out malicious location information. Based on this technique, we propose an algorithm to effectively estimate sensor positions. We illustrate the impact of inside attacks on the existing algorithms and report simulation results concerning our algorithm.

KIWI is a SQL-on-Hadoop system enabling batch and interactive analytics for big data. In database systems, materialized views, stored pre-computed results for queries, are one of the most commonly used techniques to improve the query processing speed. However, the key challenge in using materialized views is maintaining their freshness as base data changes. This paper introduces a new approach for accelerating OLAP query processing using query workload statistics and query column sets instead of materialized views. We present an architecture of SQL-on-Hadoop system using query column sets of original tables in database. The experimental results demonstrate that our system can provide improved performance by 1.77x on average in terms of TPC-H query processing.

Smart meters are integral to demand response in emerging smart grids, by reporting the electricity consumption of users to serve application needs. But reporting real-time usage information for individual households raises privacy concerns. Existing techniques to guarantee differential privacy (DP) of smart meter users either are not fault tolerant or achieve (possibly partial) fault tolerance at high communication overheads. In this paper, we propose a fault-tolerant protocol for smart metering that can handle general communication failures while ensuring DP with significantly improved efficiency and lower errors compared with the state of the art. Our protocol handles fail-stop faults proactively by using a novel design of future ciphertexts, and distributes trust among the smart meters by sharing secret keys among them. We prove the DP properties of our protocol and analyze its advantages in fault tolerance, accuracy, and communication efficiency relative to competing techniques. We illustrate our analysis by simulations driven by real-world traces of electricity consumption.

In many envisioned drone-based applications, drones will communicate with many different smart objects, such as sensors and embedded devices. Securing such communications requires an effective and efficient encryption key establishment protocol. However, the design of such a protocol must take into account constrained resources of smart objects and the mobility of drones. In this paper, a secure communication protocol between drones and smart objects is presented. To support the required security functions, such as authenticated key agreement, non-repudiation, and user revocation, we propose an efficient Certificateless Signcryption Tag Key Encapsulation Mechanism (eCLSC-TKEM). eCLSC-TKEM reduces the time required to establish a shared key between a drone and a smart object by minimizing the computational overhead at the smart object. Also, our protocol improves drone's efficiency by utilizing dual channels which allows many smart objects to concurrently execute eCLSC-TKEM. We evaluate our protocol on commercially available devices, namely AR.Drone2.0 and TelosB, by using a parking management testbed. Our experimental results show that our protocol is much more efficient than other protocols.

Several solutions have recently been proposed to securely estimate sensor positions even when there is malicious location information which distorts the estimate. Some of those solutions are based on the Minimum Mean Square Estimation (MMSE) methods which efficiently estimate sensor positions. Although such solutions can filter out most of malicious information, if an attacker knows the position of a target sensor, the attacker can significantly alter the position information. In this paper, we introduce such a new attack, called Inside-Attack, and a technique that is able to detect and filter out malicious location information.

Recently, wireless sensor networks (WSNs) have been deployed for a wide variety of applications, including military sensing and tracking, patient status monitoring, traffic flow monitoring, where sensory devices often move between different locations. Securing data and communications requires suitable encryption key protocols. In this paper, we propose a certificateless-effective key management (CL-EKM) protocol for secure communication in dynamic WSNs characterized by node mobility. The CL-EKM supports efficient key updates when a node leaves or joins a cluster and ensures forward and backward key secrecy. The protocol also supports efficient key revocation for compromised nodes and minimizes the impact of a node compromise on the security of other communication links. A security analysis of our scheme shows that our protocol is effective in defending against various attacks. We implement CL-EKM in Contiki OS and simulate it using Cooja simulator to assess its time, energy, communication, and memory performance.

CertificateLess Hybrid SignCryption (CL-HSC) scheme is useful for efficiently encapsulating symmetric keys for secure communications. It solves the key escrow problem and the certificate management problem. However, the existing scheme is not suitable for Advanced Metering Infrastructure (AMI) networks because of the utilization of expensive pairing operations. As smart meter devices have limited computing power, we need efficient algorithms for AMI networks. In this poster, we propose a novel CL-HSC scheme without pairing operations. In order to evaluate its performance, we implemented our CL-HSC scheme and conventional hybrid encryption approaches. The experimental results show that our CL-HSC scheme is efficient and suitable for secure communications in AMI networks.

Smart meters are integral to demand response in emerging smart grids, by reporting the electricity consumption of users to serve application needs. But reporting real-time usage information for individual households raises privacy concerns. Existing techniques to guarantee differential privacy (DP) of smart meter users either are not fault tolerant or achieve (possibly partial) fault tolerance at high communication overheads. In this paper, we propose a fault-tolerant protocol for smart metering that can handle general communication failures while ensuring DP with significantly improved efficiency and lower errors compared with the state of the art. Our protocol handles fail-stop faults proactively by using a novel design of future ciphertexts, and distributes trust among the smart meters by sharing secret keys among them. We prove the DP properties of our protocol and analyze its advantages in fault tolerance, accuracy, and communication efficiency relative to competing techniques. We illustrate our analysis by simulations driven by real-world traces of electricity consumption.

Bi temporal databases allow users to record retroactive (past) and proactive (future planned) versions of an entity, and to retrieve the appropriate versions for bi temporal queries that involve both valid time and transaction time. Currently used timestamp representations are mainly for either valid time or transaction time databases. We first categorize the types of problems that can occur in existing models. These are: ambiguity; priority specification; and lost information. We then propose a 2TDB model that allows both retroactive and proactive versions, overcomes the identified problems, and permits the correction of recorded facts.