TASTY Henecka, Wilko; K ögl, Stefan; Sadeghi, Ahmad-Reza ...
Proceedings of the 17th ACM conference on Computer and communications security,
10/2010
Conference Proceeding
Secure two-party computation allows two untrusting parties to jointly compute an arbitrary function on their respective private inputs while revealing no information beyond the outcome. Existing ...cryptographic compilers can automatically generate secure computation protocols from high-level specifications, but are often limited in their use and efficiency of generated protocols as they are based on either garbled circuits or (additively) homomorphic encryption only.
In this paper we present TASTY, a novel tool for automating, i.e., describing, generating, executing, benchmarking, and comparing, efficient secure two-party computation protocols. TASTY is a new compiler that can generate protocols based on homomorphic encryption and efficient garbled circuits as well as combinations of both, which often yields the most efficient protocols available today. The user provides a high-level description of the computations to be performed on encrypted data in a domain-specific language. This is automatically transformed into a protocol. TASTY provides most recent techniques and optimizations for practical secure two-party computation with low online latency. Moreover, it allows to efficiently evaluate circuits generated by the well-known Fairplay compiler.
We use TASTY to compare protocols for secure multiplication based on homomorphic encryption with those based on garbled circuits and highly efficient Karatsuba multiplication. Further, we show how TASTY improves the online latency for securely evaluating the AES functionality by an order of magnitude compared to previous software implementations. TASTY allows to automatically generate efficient secure protocols for many privacy-preserving applications where we consider the use cases for private set intersection and face recognition protocols.
The total fertility rate (TFR) in the Middle East and North Africa has experienced a declining trend in recent years. Accordingly, the present study was conducted to provide a clear picture of the ...most critical factors affecting the TFR decline in this region.
This study was a systematic review between the years 2000 and 2016. The different databases like Cochrane, PubMed, Scopus, and Science Direct and the Google Scholar search engine were used. At first, 270 articles and then 18 articles were selected and meticulously read for the final analysis.
The results indicated a declining trend in the TFR in the Middle East and North Africa, as in other parts of the world. Regarding the causes of this declining trend, several factors were identified and categorized into five main factors of health care-related, cultural, economic, social, and political.
While taking advantage of the experiences, it is necessary to identify the five main factors and their related issues and hence consider them in the population policy-making.
This paper presents a new direct power control (DPC) strategy for a double fed induction generator (DFIG) based wind energy generation system. Switching vectors for rotor side converter were selected ...from the optimal switching table using the estimated stator flux position and the errors of the active and reactive power. A few number of voltage vectors may cause undesired power and stator current ripple. In this paper the increased number of voltage vectors with application of the Discrete Space Vector Modulation (DSVM) will be presented. Then a new switching table in supersynchronous and subsynchronous frames will be proposed. Simulation results of a 2
MW DFIG system demonstrate the effectiveness and robustness of the proposed control strategy during variations of active and reactive power, machine parameters, and wind speed.
Federated learning (FL) is an emerging technology that allows participants to jointly train a machine learning model without sharing their private data with others. However, FL is vulnerable to ...poisoning attacks such as backdoor attacks. Consequently, a variety of defenses have recently been proposed, which have primarily utilized intermediary states of the global model (i.e., logits) or distance of the local models (i.e., L 2 −norm) with respect to the global model to detect malicious backdoors in FL. However, as these approaches directly operate on client updates (or weights), their effectiveness depends on factors such as clients' data distribution or the adversary's attack strategies. In this paper, we introduce a novel and more generic backdoor defense framework, called BayBFed, which proposes to utilize probability distributions over client updates to detect malicious updates in FL: BayBFed computes a probabilistic measure over the clients' updates to keep track of any adjustments made in the updates, and uses a novel detection algorithm that can leverage this probabilistic measure to efficiently detect and filter out malicious updates. Thus, it overcomes the shortcomings of previous approaches that arise due to the direct usage of client updates; nevertheless, our probabilistic measure will include all aspects of the local client training strategies. BayBFed utilizes two Bayesian NonParametric (BNP) extensions: (i) a Hierarchical Beta-Bernoulli process to draw a probabilistic measure given the clients' updates, and (ii) an adaptation of the Chinese Restaurant Process (CRP), referred by us as CRP-Jensen, which leverages this probabilistic measure to detect and filter out malicious updates. We extensively evaluate our defense approach on five benchmark datasets: CIFAR10, Reddit, IoT intrusion detection, MNIST, and FMNIST, and show that it can effectively detect and eliminate malicious updates in FL without deteriorating the benign performance of the global model.
We introduce Tiny Garble, a novel automated methodology based on powerful logic synthesis techniques for generating and optimizing compressed Boolean circuits used in secure computation, such as ...Yao's Garbled Circuit (GC) protocol. Tiny Garble achieves an unprecedented level of compactness and scalability by using a sequential circuit description for GC. We introduce new libraries and transformations, such that our sequential circuits can be optimized and securely evaluated by interfacing with available garbling frameworks. The circuit compactness makes the memory footprint of the garbling operation fit in the processor cache, resulting in fewer cache misses and thereby less CPU cycles. Our proof-of-concept implementation of benchmark functions using Tiny Garble demonstrates a high degree of compactness and scalability. We improve the results of existing automated tools for GC generation by orders of magnitude, for example, Tiny Garble can compress the memory footprint required for 1024-bit multiplication by a factor of 4,172, while decreasing the number of non-XOR gates by 67%. Moreover, with Tiny Garble we are able to implement functions that have never been reported before, such as SHA-3. Finally, our sequential description enables us to design and realize a garbled processor, using the MIPS I instruction set, for private function evaluation. To the best of our knowledge, this is the first scalable emulation of a general purpose processor.
Due to the recent upward trend in utilizing renewable energies (REs) as a result of economic reasons and global trend in reducing greenhouse gases (GHG) emission, the independent system operators ...(ISOs) have been confronted with several obstacles. The system operators have to overcome not only the fluctuating nature of renewable generation, but also the transmission of large amounts of REs from plants to the load centers. This is because of avoiding network congestion to obtain full utilization of renewable generation capacity. In addition, the cleaner production of power systems is one of the major concerns of today’s world. Transportable battery-based energy storage (TBES) system is a novel idea, which utilizes rail roads as a complementary infrastructure to transmit electric power in the form of stored energy in batteries. In this paper, a multi-objective stochastic network constrained unit commitment (NCUC) problem with TBES and demand response (DR) program is presented to minimize the operation cost as well as the total GHG emission of the power grid. The ε-constrained approach is utilized to solve the multi-objective problem and the compromise solution for each case is defined by the min-max method. To manage the wind and load uncertainty the stochastic optimization approach is applied using Monte Carlo simulation method. Moreover, DR programs are introduced as one of the flexible resources to manage the uncertainties, provide cleaner operation and reduce the overall cost by modifying the load profile and peak load shaving. The proposed model is implemented on a 6-bus power system coordinated with 3-station railway network. Simulation results revealed that considering TBES and DR reduces the transmission congestion, total operation cost and GHG emission. The overall operation cost, without considering the emission constraints, is decremented by 11.2% in case of using TBES and DR. On the other side, applying emission constraints led to an increase in overall cost to obtain the compromise solution. However, the total GHG emission is reduced by 17.2% in case of developing TBES and DR.
•The impact of mobile ESS on cleaner operation and total cost of the power grid is presented.•A multi-objective scheme is presented for the cost of power and transportation system as well as pollutant emission.•The stochastic optimization approach is presented to manage wind power and load uncertainties.•The DR program is applied for emission reduction, smoothing load profile, and reducing optimized cost.
•Proposing a decentralized mechanism for coordinated local-regional energy systems.•Using an iteration based two-step framework to solve the introduced model.•Including energy storage resources in ...the integrated local-regional energy systems.•Applying a stochastic approach to handle the uncertainties of the integrated system.•Presenting a linearized gas network model considering linepack.
A multi-energy system (MES) provides greater flexibility for the operation of different energy carriers. It increases the reliability and efficiency of the networks in the presence of renewable energy sources (RESs). Various energy carriers such as power, gas, and heat can be interconnected by energy storage systems (ESSs) and combined heat and power units at different levels (e.g., within a region or a local). Non-coordinated optimization of energy systems at local and regional levels does not verify the whole optimal operation of systems since the systems are operated without considering their interactions with each other. One of the most famous sources of flexibility is ESSs. Hence, this paper presents a stochastic decentralized approach to evaluate the impact of ESSs on regional-local MES market-clearing within a bi-level framework. On the regional level, the economic interaction between the electricity and natural gas (NG) systems is carried out by a centralized system operator (CSO). In addition, coordination between various energy carriers is implemented by the energy hub operator at the local level. To ameliorate the flexibility of the NG system in the regional MES, the linepack model of gas pipelines has been considered. Local MES modeling is performed through multiple input/output ports using a linear energy hub model. The proposed model is a mixed-integer linear programming (MILP), which is solved by CPLEX solver in GAMS software.
Smart factories, critical infrastructures, and medical devices largely rely on embedded systems that need to satisfy realtime constraints to complete crucial tasks. Recent studies and reports have ...revealed that many of these devices suffer from crucial vulnerabilities that can be exploited with fatal consequences. Despite the security and safety-critical role of these devices, they often do not feature state-of-the-art security mechanisms. Moreover, since realtime systems have strict timing requirements, integrating new security mechanisms is not a viable option as they often influence the device's runtime behavior. One solution is to offload security enhancements to a remote instance, the so-called remote attestation.
We present RealSWATT, the first software-based remote attestation system for realtime embedded devices. Remote attestation is a powerful security service that allows a party to verify the correct functionality of an untrusted remote device. In contrast to previous remote attestation approaches for realtime systems, RealSWATT does neither require custom hardware extensions nor trusted computing components. It is designed to work within real-world IoT networks, connected through Wi-Fi. RealSWATT leverages a dedicated processor core for remote attestation and provides the required timing guarantees without hardware extensions. We implement RealSWATT on the popular ESP32 microcontroller, and we evaluate it on a real-world medical device with realtime constraints. To demonstrate its applicability, we furthermore integrate RealSWATT into a framework for off-the-shelf IoT devices and apply it to a smart plug, a smoke detector, and a smart light bulb.
•Transportable Battery Energy Storage is modeled to improve the flexibility of wind-based power system.•Coordinated scheduling of TBES and DR program is presented to compensate the wind power ...variations.•An IGDT-based NCUC problem is proposed as a non-probabilistic scheme for uncertainty management.
In recent years, the use of renewable energy (RE) sources has an upward trend due to the environmental and economic reasons. However, finding a solution method to manage the fluctuating nature of these sources and more efficient utilization of total generation capacity are challenging problems, especially when there is a high penetration of REs in power systems. On the other side, the network congestion in power grids is another obstacle that inhibits the full utilization of REs. Battery-based energy storage transportation using a railway network leads to emerging high-efficiency technology called transportable battery-based energy storage (TBES) system. TBES technology is a practical and economical option to reduce transmission congestion and increase the utilization of the energy storage systems’ (ESSs’) capacity by providing additional facility to transfer power. As a flexible resource, TBES can adapt to the load profile of the system at peak-load hours and result in cost reduction and more prudent management of wind power variations. The demand response (DR) program is another solution to deal with wind power uncertainty and has a considerable impact on reducing power network congestion and total operation cost by peak-load shaving. Hence, to overcome the mentioned challenges and obstacles, this paper focuses on solving a robust network constrained unit commitment (NCUC) with TBES and DR programs. To manage the wind power uncertainty, an information gap decision theory (IGDT)-based robust optimization technique is proposed to obtain maximum robustness against the wind power uncertainty. The advantage of the presented model is that neither probability distribution functions (PDFs) nor scenario generation are required. The 6-bus power system coordinated with the 3-station railway network is applied as the test system. Numerical studies pointed out that integrating TBES technology in IGDT-based robust NCUC problems and considering the DR program has improved the power system’s flexibility and uncertainty management of wind power, alleviated the congestion, and reduced the optimized cost. Simulation results revealed a 6.5% cost reduction by applying TBES and also 11.3% cost decrement by developing coordinated TBES and DR.
RFID-based tokens are increasingly used in electronic payment and ticketing systems for mutual authentication of tickets and terminals. These systems typically use cost-effective tokens without ...expensive hardware protection mechanisms and are exposed to hardware attacks that copy and maliciously modify tokens. Physically Unclonable Functions (PUFs) are a promising technology to protect against such attacks by binding security critical data to the physical characteristics of the underlying hardware. However, existing PUF-based authentication schemes for RFID do not support mutual authentication, are often vulnerable to emulation and denial-of service attacks, and allow only for a limited number of authentications.
In this paper, we present a new PUF-based authentication scheme that overcomes these drawbacks: it supports PUF-based mutual authentication between tokens and readers, is resistant to emulation attacks, and supports an unlimited number of authentications without requiring the reader to store a large number of PUF challenge/response pairs. In this context, we introduce reverse fuzzy extractors, a new approach to correct noise in PUF responses that allows for extremely lightweight implementations on the token. Our proof-of-concept implementation shows that our scheme is suitable for resource-constrained devices.
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