scholarly journals Energy/Area-Efficient Scalar Multiplication with Binary Edwards Curves for the IoT

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 720 ◽  
Author(s):  
Carlos Lara-Nino ◽  
Arturo Diaz-Perez ◽  
Miguel Morales-Sandoval
Keyword(s):  
Evaluation Method ◽  
Scalar Multiplication ◽  
Sensitive Information ◽  
Performance Improvements ◽  
Low Area ◽  
Edwards Curves ◽  
Trade Offs ◽  
Novel Approach ◽  
Availability Constraints ◽  
Implementation Costs

Making Elliptic Curve Cryptography (ECC) available for the Internet of Things (IoT) and related technologies is a recent topic of interest. Modern IoT applications transfer sensitive information which needs to be protected. This is a difficult task due to the processing power and memory availability constraints of the physical devices. ECC mainly relies on scalar multiplication (kP)—which is an operation-intensive procedure. The broad majority of kP proposals in the literature focus on performance improvements and often overlook the energy footprint of the solution. Some IoT technologies—Wireless Sensor Networks (WSN) in particular—are critically sensitive in that regard. In this paper we explore energy-oriented improvements applied to a low-area scalar multiplication architecture for Binary Edwards Curves (BEC)—selected given their efficiency. The design and implementation costs for each of these energy-oriented techniques—in hardware—are reported. We propose an evaluation method for measuring the effectiveness of these optimizations. Under this novel approach, the energy-reducing techniques explored in this work contribute to achieving the scalar multiplication architecture with the most efficient area/energy trade-offs in the literature, to the best of our knowledge.

scholarly journals Learning With Differential Privacy

2021 ◽  
pp. 372-395
Author(s):  
Poushali Sengupta ◽  
Sudipta Paul ◽  
Subhankar Mishra
Keyword(s):  
Privacy Protection ◽  
Differential Privacy ◽  
Intrusion Detection Systems ◽  
Sensitive Information ◽  
Detection Systems ◽  
Trade Offs ◽  
Personal Level ◽  
Encryption Decryption ◽  
Individual Trees ◽  
Prevention Methods

The leakage of data might have an extreme effect on the personal level if it contains sensitive information. Common prevention methods like encryption-decryption, endpoint protection, intrusion detection systems are prone to leakage. Differential privacy comes to the rescue with a proper promise of protection against leakage, as it uses a randomized response technique at the time of collection of the data which promises strong privacy with better utility. Differential privacy allows one to access the forest of data by describing their pattern of groups without disclosing any individual trees. The current adaption of differential privacy by leading tech companies and academia encourages authors to explore the topic in detail. The different aspects of differential privacy, its application in privacy protection and leakage of information, a comparative discussion on the current research approaches in this field, its utility in the real world as well as the trade-offs will be discussed.

Privacy in Control and Dynamical Systems

2018 ◽  
Vol 1 (1) ◽  
pp. 309-332 ◽  
Author(s):  
Shuo Han ◽  
George J. Pappas
Keyword(s):  
Dynamical Systems ◽  
Smart Grids ◽  
Differential Privacy ◽  
Side Information ◽  
Sensitive Information ◽  
Efficient Operation ◽  
The Public ◽  
Rigorous Approach ◽  
Trade Offs ◽  
User Data

Many modern dynamical systems, such as smart grids and traffic networks, rely on user data for efficient operation. These data often contain sensitive information that the participating users do not wish to reveal to the public. One major challenge is to protect the privacy of participating users when utilizing user data. Over the past decade, differential privacy has emerged as a mathematically rigorous approach that provides strong privacy guarantees. In particular, differential privacy has several useful properties, including resistance to both postprocessing and the use of side information by adversaries. Although differential privacy was first proposed for static-database applications, this review focuses on its use in the context of control systems, in which the data under processing often take the form of data streams. Through two major applications—filtering and optimization algorithms—we illustrate the use of mathematical tools from control and optimization to convert a nonprivate algorithm to its private counterpart. These tools also enable us to quantify the trade-offs between privacy and system performance.

Efficient Lightweight Hardware Structures of Point Multiplication on Binary Edwards Curves for Elliptic Curve Cryptosystems

2019 ◽  
Vol 28 (09) ◽  
pp. 1950149
Author(s):  
Bahram Rashidi ◽  
Mohammad Abedini
Keyword(s):  
High Speed ◽  
Critical Path ◽  
Low Cost ◽  
Path Delay ◽  
Point Multiplication ◽  
Low Area ◽  
Elliptic Curve Cryptosystems ◽  
Edwards Curves ◽  
Special Cases ◽  
Field Multiplication

This paper presents efficient lightweight hardware implementations of the complete point multiplication on binary Edwards curves (BECs). The implementations are based on general and special cases of binary Edwards curves. The complete differential addition formulas have the cost of [Formula: see text] and [Formula: see text] for general and special cases of BECs, respectively, where [Formula: see text] and [Formula: see text] denote the costs of a field multiplication, a field squaring and a field multiplication by a constant, respectively. In the general case of BECs, the structure is implemented based on 3 concurrent multipliers. Also in the special case of BECs, two structures by employing 3 and 2 field multipliers are proposed for achieving the highest degree of parallelization and utilization of resources, respectively. The field multipliers are implemented based on the proposed efficient digit–digit polynomial basis multiplier. Two input operands of the multiplier proceed in digit level. This property leads to reduce hardware consumption and critical path delay. Also, in the structure, based on the change of input digit size from low digit size to high digit size the number of clock cycles and input words are different. Therefore, the multiplier can be flexible for different cryptographic considerations such as low-area and high-speed implementations. The point multiplication computation requires field inversion, therefore, we use a low-cost Extended Euclidean Algorithm (EEA) based inversion for implementation of this field operation. Implementation results of the proposed architectures based on Virtex-5 XC5VLX110 FPGA for two fields [Formula: see text] and [Formula: see text] are achieved. The results show improvements in terms of area and efficiency for the proposed structures compared to previous works.

Dynamic Combined with Static Analysis for Mining Network Protocol's Hidden Behavior

2017 ◽  
Vol 13 (2) ◽  
pp. 1-14
Author(s):  
Yanjing Hu ◽  
Qingqi Pei
Keyword(s):  
Static Analysis ◽  
Evaluation Method ◽  
Prototype System ◽  
Sensitive Information ◽  
Taint Analysis ◽  
Dynamic Triggering ◽  
Public Behavior ◽  
Protocol Execution ◽  
Virtual Platform ◽  
Object Dynamic

Unknown protocol's hidden behavior is becoming a new challenge in network security. This paper takes the captured messages and the binary code that implement the protocol both as the studied object. Dynamic Taint Analysis combined with Static Analysis is used for protocol analyzing. Firstly, monitor and analyze the process of protocol program parses the message in the virtual platform HiddenDisc prototype system developed by the authors, record the protocol's public behavior, then based on the authors' proposed Hidden Behavior Perception and Mining algorithm, static analyze the protocol's hidden behavior trigger conditions and hidden behavior instruction sequences. According to the hidden behavior trigger conditions, new protocol messages with the sensitive information are generated, and the hidden behaviors are executed by dynamic triggering. HiddenDisc prototype system can sense, trigger and analyze the protocol's hidden behaviors. According to the statistical analysis results, the authors propose the evaluation method of Protocol Execution Security. The experimental results show that the present method can accurately mining the protocol's hidden behaviors, and can evaluate unknown protocol's execution security.

To breed or not: a novel approach to estimate breeding propensity and potential trade-offs in an Arctic-nesting species

Ecology ◽  
2014 ◽  
Vol 95 (10) ◽  
pp. 2745-2756 ◽  
Author(s):  
Guillaume Souchay ◽  
Gilles Gauthier ◽  
Roger Pradel
Keyword(s):  
Trade Offs ◽  
Novel Approach ◽  
Breeding Propensity

scholarly journals Recommendations for performance optimizations when using GATK3.8 and GATK4

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Jacob R Heldenbrand ◽  
Saurabh Baheti ◽  
Matthew A Bockol ◽  
Travis M Drucker ◽  
Steven N Hart ◽  
...  
Keyword(s):  
Large Population ◽  
Variant Calling ◽  
Cost Effective ◽  
Performance Improvements ◽  
Computational Performance ◽  
Trade Offs ◽  
Genome Analysis Toolkit ◽  
The Cost ◽  
Multiple Samples ◽  
Parameter Values

Abstract Background Use of the Genome Analysis Toolkit (GATK) continues to be the standard practice in genomic variant calling in both research and the clinic. Recently the toolkit has been rapidly evolving. Significant computational performance improvements have been introduced in GATK3.8 through collaboration with Intel in 2017. The first release of GATK4 in early 2018 revealed rewrites in the code base, as the stepping stone toward a Spark implementation. As the software continues to be a moving target for optimal deployment in highly productive environments, we present a detailed analysis of these improvements, to help the community stay abreast with changes in performance. Results We re-evaluated multiple options, such as threading, parallel garbage collection, I/O options and data-level parallelization. Additionally, we considered the trade-offs of using GATK3.8 and GATK4. We found optimized parameter values that reduce the time of executing the best practices variant calling procedure by 29.3% for GATK3.8 and 16.9% for GATK4. Further speedups can be accomplished by splitting data for parallel analysis, resulting in run time of only a few hours on whole human genome sequenced to the depth of 20X, for both versions of GATK. Nonetheless, GATK4 is already much more cost-effective than GATK3.8. Thanks to significant rewrites of the algorithms, the same analysis can be run largely in a single-threaded fashion, allowing users to process multiple samples on the same CPU. Conclusions In time-sensitive situations, when a patient has a critical or rapidly developing condition, it is useful to minimize the time to process a single sample. In such cases we recommend using GATK3.8 by splitting the sample into chunks and computing across multiple nodes. The resultant walltime will be nnn.4 hours at the cost of $41.60 on 4 c5.18xlarge instances of Amazon Cloud. For cost-effectiveness of routine analyses or for large population studies, it is useful to maximize the number of samples processed per unit time. Thus we recommend GATK4, running multiple samples on one node. The total walltime will be ∼34.1 hours on 40 samples, with 1.18 samples processed per hour at the cost of $2.60 per sample on c5.18xlarge instance of Amazon Cloud.

scholarly journals BAT—Block Analytics Tool Integrated with Blockchain Based IoT Platform

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1525
Author(s):  
Chathurangi Edussuriya ◽  
Kasun Vithanage ◽  
Namila Bandara ◽  
Janaka Alawatugoda ◽  
Manjula Sandirigama ◽  
...  
Keyword(s):  
Security And Privacy ◽  
Sensitive Information ◽  
Pharmaceutical Drugs ◽  
Case Scenario ◽  
Real World Data ◽  
Data Set ◽  
Pharmaceutical Supply Chain ◽  
Iot Platform ◽  
Novel Approach ◽  
Iot Devices

The Internet of Things (IoT) is the novel paradigm of connectivity and the driving force behind state-of-the-art applications and services. However, the exponential growth of the number of IoT devices and services, their distributed nature, and scarcity of resources has increased the number of security and privacy concerns ranging from the risks of unauthorized data alterations to the potential discrimination enabled by data analytics over sensitive information. Thus, a blockchain based IoT-platform is introduced to address these issues. Built upon the tamper-proof architecture, the proposed access management mechanisms ensure the authenticity and integrity of data. Moreover, a novel approach called Block Analytics Tool (BAT), integrated with the platform is proposed to analyze and make predictions on data stored on the blockchain. BAT enables the data-analysis applications to be developed using the data stored in the platform in an optimized manner acting as an interface to off-chain processing. A pharmaceutical supply chain is used as the use case scenario to show the functionality of the proposed platform. Furthermore, a model to forecast the demand of the pharmaceutical drugs is investigated using a real-world data set to demonstrate the functionality of BAT. Finally, the performance of BAT integrated with the platform is evaluated.

scholarly journals LNDIR: A lightweight non-increasing delivery-latency interval-based routing for duty-cycled sensor networks

2018 ◽  
Vol 14 (4) ◽  
pp. 155014771876760 ◽  
Author(s):  
Muhammad K Shahzad ◽  
Dang Tu Nguyen ◽  
Vyacheslav Zalyubovskiy ◽  
Hyunseung Choo
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Nodes ◽  
Traffic Load ◽  
Wireless Sensor ◽  
Neighbor Discovery ◽  
Performance Improvements ◽  
Novel Approach ◽  
Minimum Latency ◽  
Latency Interval

Wireless sensor networks are composed of low-energy, small-size, and low-range unattended sensor nodes. Recently, it has been observed that by periodically turning on and off the sensing and communication capabilities of sensor nodes, we can significantly reduce the active time and thus prolong network lifetime. However, this duty cycling may result in high network latency, routing overhead, and neighbor discovery delays due to asynchronous sleep and wake-up scheduling. These limitations call for a countermeasure for duty-cycled wireless sensor networks which should minimize routing information, routing traffic load, and energy consumption. In this article, we propose a lightweight non-increasing delivery-latency interval routing referred as LNDIR. This scheme can discover minimum latency routes at each non-increasing delivery-latency interval instead of each time slot. Simulation experiments demonstrated the validity of this novel approach in minimizing routing information stored at each sensor. Furthermore, this novel routing can also guarantee the minimum delivery latency from each source to the sink. Performance improvements of up to 12-fold and 11-fold are observed in terms of routing traffic load reduction and energy efficiency, respectively, as compared to existing schemes.

Constrained multi-objective aerofoil design using a multi-level optimisation strategy

2015 ◽  
Vol 119 (1217) ◽  
pp. 833-854
Author(s):  
L. Cameron ◽  
J. Early ◽  
R. McRoberts ◽  
M. Price
Keyword(s):  
Leading Edge ◽  
Boundary Layer Transition ◽  
Layer Transition ◽  
Multi Objective ◽  
Trade Offs ◽  
Novel Approach ◽  
Design Variables ◽  
Business Jet ◽  
Global And Local ◽  
Local Optimisation

AbstractA novel approach for the multi-objective design optimisation of aerofoil profiles is presented. The proposed method aims to exploit the relative strengths of global and local optimisation algorithms, whilst using surrogate models to limit the number of computationally expensive CFD simulations required. The local search stage utilises a re-parameterisation scheme that increases the flexibility of the geometry description by iteratively increasing the number of design variables, enabling superior designs to be generated with minimal user intervention. Capability of the algorithm is demonstrated via the conceptual design of aerofoil sections for use on a lightweight laminar flow business jet. The design case is formulated to account for take-off performance while reducing sensitivity to leading edge contamination. The algorithm successfully manipulates boundary layer transition location to provide a potential set of aerofoils that represent the trade-offs between drag at cruise and climb conditions in the presence of a challenging constraint set. Variations in the underlying flow physics between Pareto-optimal aerofoils are examined to aid understanding of the mechanisms that drive the trade-offs in objective functions.

scholarly journals Performance benchmarking of GATK3.8 and GATK4

2018 ◽  
Author(s):  
Jacob R. Heldenbrand ◽  
Saurabh Baheti ◽  
Matthew A. Bockol ◽  
Travis M. Drucker ◽  
Steven N. Hart ◽  
...  
Keyword(s):  
Variant Calling ◽  
Performance Improvements ◽  
Performance Benchmarking ◽  
Computational Performance ◽  
Trade Offs ◽  
Code Base ◽  
Different Types ◽  
Genome Analysis Toolkit ◽  
Optimal Deployment ◽  
Genomic Variant

AbstractUse of the Genome Analysis Toolkit (GATK) continues to be the standard practice in genomic variant calling in both research and the clinic. Recently the toolkit has been rapidly evolving. Significant computational performance improvements have been introduced in GATK3.8 through collaboration with Intel in 2017. The first release of GATK4 in early 2018 revealed significant rewrites in the code base, as the stepping stone toward a Spark implementation. As the software continues to be a moving target for optimal deployment in highly productive environments, we present a detailed analysis of these improvements, to help the community stay abreast with changes in performance. We re-evaluated the options previously identified as advantageous, such as threading, parallel garbage collection, I/O options and data-level parallelization. Based on our results, we consider the performance and cost trade-offs of using GATK3.8 and GATK4 for different types of analyses.

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