Dronecrypt - An Efficient Cryptographic Framework for Small Aerial Drones

Aerial drones are becoming an integral part of application domains including but not limited to, military operations, package delivery, construction, monitoring and search/rescue operations. It is critical to ensure the cyber security of networked aerial drone systems in these applications. Standard cryptographic services can be deployed to provide basic security services; however, they have been shown to be inefficient in terms of energy and time consumption, especially for small aerial drones with resource-limited processors. Therefore, there is a significant need for an efficient cryptographic framework that can meet the requirements of small aerial drones. We propose an improved cryptographic framework for small aerial drones, which offers significant energy efficiency and speed advantages over standard cryptographic techniques. (i) We create (to the best of our knowledge) the first optimized public key infrastructure (PKI) based framework for small aerial drones, which provides energy efficient techniques by harnessing special precomputation methods and optimized elliptic curves. (ii) We also integrate recent light-weight symmetric primitives into our PKI techniques to provide a full-fledged cryptographic framework. (iii) We implemented standard counterparts and our proposed techniques on an actual small aerial drone (Crazyflie 2.0), and provided an in-depth energy analysis. Our experiments showed that our improved cryptographic framework achieves up to 35$\times$ lower energy consumption than its standard counterpart

Lattice-Based Public Key Searchable Encryption from Experimental Perspectives

Public key Encryption with Keyword Search (PEKS) aims in mitigating the impacts of data privacy versus utilization dilemma by allowing {\em any user in the system} to send encrypted files to the server to be searched by a receiver. The receiver can retrieve the encrypted files containing specific keywords by providing the corresponding trapdoors of these keywords to the server. Despite their merits, the existing PEKS schemes introduce a high end-to-end delay that may hinder their adoption in practice. Moreover, they do not scale well for large security parameters and provide no post-quantum security promises. In this paper, we propose two novel lattice-based PEKS schemes that offer a high computational efficiency along with better security assurances than that of the existing alternatives. Specifically, our NTRU-PEKS scheme achieves 18 times lower end-to-end delay than the most efficient pairing-based alternatives. Our LWE-PEKS offers provable security in the standard model with a reduction to the worst-case lattice problems. We fully implemented our NTRU-PEKS scheme and benchmarked its performance as deployed on Amazon Web Services cloud infrastructures

Compact Energy and Delay-Aware Authentication

Authentication and integrity are fundamental security services that are critical for any viable system. However, some of the emerging systems (e.g., smart grids, aerial drones) are delay-sensitive, and therefore their safe and reliable operation requires delay-aware authentication mechanisms. Unfortunately, the current state-of-the-art authentication mechanisms either incur heavy computations or lack scalability for such large and distributed systems. Hence, there is a crucial need for digital signature schemes that can satisfy the requirements of delay-aware applications. In this paper, we propose a new digital signature scheme that we refer to as Compact Energy and Delay-aware Authentication (CEDA). In CEDA, signature generation and verification only require a small-constant number of multiplications and Pseudo Random Function (PRF) calls. Therefore, it achieves the lowest end-to-end delay among its counterparts. Our implementation results on an ARM processor and commodity hardware show that CEDA has the most efficient signature generation on both platforms, while offering a fast signature verification. Among its delay-aware counterparts, CEDA has a smaller private key with a constant-size signature. All these advantages are achieved with the cost of a larger public key. This is a highly favorable trade-off for applications wherein the verifier is not memory-limited. We open-sourced our implementation of CEDA to enable its broad testing and adaptation

Forward-Private Dynamic Searchable Symmetric Encryption with Efficient Search

Dynamic Searchable Symmetric Encryption (DSSE) allows to delegate keyword search and file update over an encrypted database via encrypted indexes, and therefore provides opportunities to mitigate the data privacy and utilization dilemma in cloud storage platforms. Despite its merits, recent works have shown that efficient DSSE schemes are vulnerable to statistical attacks due to the lack of forward-privacy, whereas forward-private DSSE schemes suffer from practicality concerns as a result of their extreme computation overhead. Due to significant practical impacts of statistical attacks, there is a critical need for new DSSE schemes that can achieve the forward-privacy in a more practical and efficient manner. We propose a new DSSE scheme that we refer to as Forward-private Sublinear DSSE (FS-DSSE). FS-DSSE harnesses special secure update strategies and a novel caching strategy to reduce the computation cost of repeated queries. Therefore, it achieves forward-privacy, sublinear search complexity, low end-to-end delay, and parallelization capability simultaneously. We fully implemented our proposed method and evaluated its performance on a real cloud platform. Our experimental evaluation results showed that the proposed scheme is highly secure and highly efficient compared with state-of-the-art DSSE techniques. Specifically, FS-DSSE is one to three magnitude of times faster than forward-secure DSSE counterparts

TACHYON: Fast Signatures from Compact Knapsack

We introduce a simple, yet efficient digital signature scheme which offers post-quantum security promise. Our scheme, named $\texttt{TACHYON}$, is based on a novel approach for extending one-time hash-based signatures to (polynomially bounded) many-time signatures, using the additively homomorphic properties of generalized compact knapsack functions. Our design permits $\texttt{TACHYON}$ to achieve several key properties. First, its signing and verification algorithms are the fastest among its current counterparts with a higher level of security. This allows $\texttt{TACHYON}$ to achieve the lowest end-to-end delay among its counterparts, while also making it suitable for resource-limited signers. Second, its private keys can be as small as $\kappa$ bits, where $\kappa$ is the desired security level. Third, unlike most of its lattice-based counterparts, $\texttt{TACHYON}$ does not require any Gaussian sampling during signing, and therefore, is free from side-channel attacks targeting this process. We also explore various speed and storage trade-offs for $\texttt{TACHYON}$, thanks to its highly tunable parameters. Some of these trade-offs can speed up $\texttt{TACHYON}$ signing in exchange for larger keys, thereby permitting $\texttt{TACHYON}$ to further improve its end-to-end delay

Hardware-Supported ORAM in Effect: Practical Oblivious Search and Update on Very Large Dataset

The ability to query and update over encrypted data is an essential feature to enable breach- resilient cyber-infrastructures. Statistical attacks on searchable encryption (SE) have demonstrated the importance of sealing information leaks in access patterns. In response to such attacks, the community has proposed the Oblivious Random Access Machine (ORAM). However, due to the logarithmic communication overhead of ORAM, the composition of ORAM and SE is known to be costly in the conventional client-server model, which poses a critical barrier toward its practical adaptations. In this paper, we propose a novel hardware-supported privacy-enhancing platform called Practical Oblivious Search and Update Platform (POSUP), which enables oblivious keyword search and update operations on large datasets with high efficiency. We harness Intel SGX to realize efficient oblivious data structures for oblivious search/update purposes. We implemented POSUP and evaluated its per- formance on a Wikipedia dataset containing ≥ 229 keyword-file pairs. Our implementation is highly efficient, taking only 1 ms to access a 3 KB block with Circuit-ORAM. Our experiments have shown that POSUP offers up to 70× less end-to-end delay with 100× reduced network bandwidth consump- tion compared with the traditional ORAM-SE composition without secure hardware. POSUP is also at least 4.5× faster for up to 99.5% of keywords that can be searched compared with state-of-the-art Intel SGX-assisted search platforms

Discovering Physical Interaction Vulnerabilities in IoT Deployments

Internet of Things (IoT) applications drive the behavior of IoT deployments according to installed sensors and actuators. It has recently been shown that IoT deployments are vulnerable to physical interactions, caused by design flaws or malicious intent, that can have severe physical consequences. Yet, extant approaches to securing IoT do not translate the app source code into its physical behavior to evaluate physical interactions. Thus, IoT consumers and markets do not possess the capability to assess the safety and security risks these interactions present. In this paper, we introduce the IoTSeer security service for IoT deployments, which uncovers undesired states caused by physical interactions. IoTSeer operates in four phases (1) translation of each actuation command and sensor event in an app source code into a hybrid I/O automaton that defines an app's physical behavior, (2) combining apps in a novel composite automaton that represents the joint physical behavior of interacting apps, (3) applying grid-based testing and falsification to validate whether an IoT deployment conforms to desired physical interaction policies, and (4) identification of the root cause of policy violations and proposing patches that guide users to prevent them. We use IoTSeer in an actual house with 13 actuators and six sensors with 37 apps and demonstrate its effectiveness and performance