ANALYSIS THE IMPACT OF SYMMETRIC CRYPTOGRAPHIC ALGORITHMS ON POWER CONSUMPTION FOR VARIOUS DATA TYPES

With the emergence of communication techniques as the human beings become advanced day by day these communication techniques also get some advancement or development day by day. After the emergence of internet the communication of data from one place to another is increasing day by day, because as we all know that internet is very fast mode of data transfer as com pared to send your data through post with the help of post - office. As the data over the internet is increasing, it is very necessary that we must ensure to provide the best solution to offer the necessary protection against the data thefts & attacks. For that purpose we use many algorithms, and among these algorithms one of the best algorithms is Encryption algorithm, because it plays an important role in information security systems. But the main problems with such types of algorithms are that they consume a significant amount of computing resources such as CPU time, memory, an d battery power. Power Consumption is not a big deal or big issue in case of wired environment but the computing resources in the wireless environment is limited and limited battery power available. As the technology advances it leads to a lot of changes i n the processors and memory in the computers, by which they requires a lot of power, or in other words we can say that they needs power to boost up, but battery technology or battery backup technology is increa sing at much slower rate, and this cause to fo rming a "battery gap". As it is like the heart of the electronic devices and as most of the equipment of electronics including computing devices and communication devices also requires a good battery backup. Today, a s we all seen that Lap - tops, Palm - tops etc.are generally used instead of Desktop or PC and it is well known that all these are the wireless devices and for these devices the data communication also be wireless and on the contrary, the networking connection will als o be wireless. From above as w e seen, the increasing demand for services on wireless devices has pushed towards us into an important research which finding ways to overcome these limitation. The paper which I present of the behalf of thesis evaluate or analy ze the six most common encry ption algorithms namely AES (Rigndael), DES, 3DES, RC2, Blowfish and RC5. Now I ll try my best to find out the method to analyze the trade - offs between energy and security. There are different approaches used to reduce the energy consumption of security pr otocols. A comparative study also I planned to be conducted for those encryption algorithms at different settings for each algorithm such as different sizes of data blocks, different data types, battery power consumption, differen t key size and finally enc ryption/decryption speed

Energy conscious adaptive security scheme : a reliability-based stochastic approach

The increasing importance of information and communication, which plays a big role in a number of different fields in the modern era, brings with it the need for security. At the same time, encryption, which is an indispensable part of security architecture, is computationally intensive and may require a significant amount of energy consumption. Thus, it is of great importance to provide a sufficient level of security while properly utilising the available resources. This research suggests a security framework based on the Reliability Function, along with the added ability to dynamically adjust the security level with respect to energy consumption, either according to the severity of the requested service or according to a specified energy threshold

Performance Evaluation of Algorithms with Different Structure Representationson Power Consumption for Smartphone Devices

The need for energy awareness on mobile devices is becoming more crucial in the design and development of mobile applications. Since power conservation is a major aspect for mobile users, the thesis will try to explore several methods and techniques in order to evaluate the performance of algorithms with different data structure representations on the power consumption of Smartphone devices. In this thesis, we will control and administer the mobile application in such a way to get quantitative results and perform relevant analysis. We will present experiments that will measure the amount of power and CPU overhead; we will explore how changing the data structures for various algorithms with different time complexities could impact power consumption. Also this thesis will try to investigate other related topics that have impact on the battery device such as local/global variables, reusing objects, arrays versus sets and other factors. The thesis will record and analyze the experiments in terms of CPU cycles and battery consumption and their relation to the above mentioned case studies. The results shows that using different data structure representations on various algorithms (having different time complexities) have impact on power consumption and CPU overhead of Smartphone devices, the figures and the analysis shows the following: A- That algorithms having time complexity of n cube with its neutral case comes at the top most level of consuming battery life and the top level of CPU overhead. B- N square comes at the second level of consuming battery life and using CPU with the following ranking (high to low) of algorithms data structure representations: Data types adjustment as double -> linked list based algorithms -> array based algorithms. C- N LOG N comes at the third level of consuming battery life and using CPU with the following ranking (high to low) of algorithms data structure representations: Data types adjustment as double -> linked list based algorithms -> array based algorithms.إن الحاجة إلى إتخاذ الطاقة كعامل أساسي في تصميم وتطوير تطبيقات األ حيث أن الحفاظ على الطاقة يشكل جانبا رئيسا ومهما لمستخدمي الهواتف الذكية، من خالل هذه الرسالة سوف نقوم ببحث ودراسة عدة أساليب وتقنيات من أجل خفض إستهالك الطاقة في الهواتف الذكية. وذلك من خالل تقييم أداء الخوارزميات ذات اإلعدادات المختلفة.علما بأن النهج المتبع في هذه الرسالة هو الحصول على نتائج كمية من خالل التحكم بالتطبيقات ومن ثم إجراء التحليالت ذات الصلة.وكذلك من خالل هذه الرسالة سوف نقوم بالبحث عن عوامل أخرى من شأنها أن توثر على استهالك الطاقة في الهواتف الذكية. ومن هذه العوامل كيفية تأثير نمط البرمجة)كتعريف المتغيرات( في إستهالك الطاقة. ومن خالل النتائج تبين أن استخدام الخوارزميات بإعدادات متباينة له تأثير في خفض إستهالك الطاقة في الهواتف الذكية

Modeling Power Consumption of Applications Software Running on Servers

Reducing power consumption in computational processes is important to software devel- opers. Ideally, a tremendous amount of software design efforts goes into considerations that are critical to power efficiencies of computer systems. Sometimes, software is designed by a high-level developer not aware of underlying physical components of the system architecture, which can be exploited. Furthermore, even if a developer is aware, they design software geared towards mass end-user adoption and thus go for cross-compatibility. The challenge for the soft- ware designer is to utilize dynamic hardware adaptations. Dynamic hardware adaptations make it possible to reduce power consumption and overall chip temperature by reducing the amount of available performance. However these adaptations generally rely on input from temperature sensors, and due to thermal inertia in microprocessor packaging, the detection of temperature changes significantly lag the power events that caused them. This work provides energy performance evaluation and power consumption estimation of ap- plications running on a server using performance counters. Counter data of various performance indicators are collected using the CollectD tool. Simultaneously, during the test, a Power Meter (TED5000) is used to monitor the actual power drawn by the computer server. Furthermore, stress tests are performed to examine power fluctuations in response to the performance counts of four hardware subsystems: CPU, memory, disk, and network interface. A neural network model (NNM) and a linear polynomial model (LPM) have been developed based on process count information gathered by CollectD. These two models have been validated by four different scenarios running on three different platforms (three real servers.) Our experimental results show that system power consumption can be estimated with an average mean absolute error (MAE) between 11% to 15% on new system servers. While on old system servers, the average MAE is between 1% to 4%. Also, we find that NNM has better estimation results than the LPM, resulting in 1.5% reduction in MAE of energy estimation when compared to the LPM. The detailed contributions of the thesis are as follows: (i) develop a non-exclusive test bench to measure the power consumption of an application running on a server; (ii) provide a practical approach to extracting system performance counters and simplifying them to get the model pa- rameters; (iii) a modeling procedure is proposed and implemented for predicting the power cost of application software using performance counters. All of our contributions and the proposed procedure have been validated with numerous measurements on a real test bench. The results of this work can be used by application developers to make implementation-level decisions that affect the energy efficiency of software applications

Energy Performance Analysis of Software Applications on Servers

The power cost of running a data center is a significant portion of its total annual operating budget. Although the hardware subsystems, namely, processors, memory, disk, and network interfaces of a server actually consume power, it is the software activities that drive the operations of the hardware subsystems leading to varying dynamic power cost. With the aim of reducing power bills of data centers, "Green Computing" has emerged with the primary goal of making software more energy efficient without compromising the performance. Developers play an important role in controlling the energy cost of data center software while writing code. Bearing green principles in mind during design and coding stages of the software life-cycle can have a great impact on the energy efficiency of the final software product. There are a number of ways to optimize application programs at their design stages but it is difficult for the developers to analyse their applications in terms of power cost on the real servers. Reading big data, moving large amount of data from one server to another, compressing data to gain storage space, and decompressing it back are some key operations that are performed extensively on large scale servers in data centers. In the first part of this thesis, we present the design of an automated test bench to measure the power cost of an application running on a server. We show how our test bench can be used by software developers to measure and improve the energy cost of two Java file access methods. Another benefit of our test bench has been demonstrated by comparing the energy footprint measurements of compression and decompression features provided by two popular Linux packages: 7z and rar. This information will be helpful in choosing a Green Software among others to perform a desired function. In the second part, we show how software developers can contribute to energy efficiency of servers by choosing energy efficient APIs (Application Programming Interface) with the optimal choice of parameters while implementing file reading, file copy, file compression and file decompression operations in Java. We performed extensive measurements of energy cost of those operations on a Dell Power Edge 2950 machine running Linux and Windows servers. Measurement results show that energy costs of various APIs for those operations are sensitive to the buffer size selection. The choice of a particular Java API for file reading with different buffer sizes has significant impact on the energy cost, giving an opportunity to save up to 76%. To save energy while copying files, it is important to use APIs with tunable buffer sizes, rather than APIs using fixed size buffers. In addition, there is a trade off between compression ratio and energy cost: because of higher compression ratio, xz compression API consumes more energy than zip and gzip compression APIs. The third part of the thesis presents a design of a framework in which one developer generates energy cost models for the common design options. Afterwords, other developers can make use of those models to find the energy costs for the same design options instead of direct measurements. Overall, this thesis makes a contribution to reduce the perception gap between high level programs and the concept of energy efficiency

Energy Efficient Security Framework for Wireless Local Area Networks

Wireless networks are susceptible to network attacks due to their inherentvulnerabilities. The radio signal used in wireless transmission canarbitrarily propagate through walls and windows; thus a wireless networkperimeter is not exactly known. This leads them to be more vulnerable toattacks such as eavesdropping, message interception and modifications comparedto wired-line networks. Security services have been used as countermeasures toprevent such attacks, but they are used at the expense of resources that arescarce especially, where wireless devices have a very limited power budget.Hence, there is a need to provide security services that are energy efficient.In this dissertation, we propose an energy efficient security framework. Theframework aims at providing security services that take into account energyconsumption. We suggest three approaches to reduce the energy consumption ofsecurity protocols: replacement of standard security protocol primitives thatconsume high energy while maintaining the same security level, modification ofstandard security protocols appropriately, and a totally new design ofsecurity protocol where energy efficiency is the main focus. From ourobservation and study, we hypothesize that a higher level of energy savings isachievable if security services are provided in an adjustable manner. Wepropose an example tunable security or TuneSec system, which allows areasonably fine-grained security tuning to provide security services at thewireless link level in an adjustable manner.We apply the framework to several standard security protocols in wirelesslocal area networks and also evaluate their energy consumption performance.The first and second methods show improvements of up to 70% and 57% inenergy consumption compared to plain standard security protocols,respectively. The standard protocols can only offer fixed-level securityservices, and the methods applied do not change the security level. The thirdmethod shows further improvement compared to fixed-level security by reducing(about 6% to 40%) the energy consumed. This amount of energy saving can bevaried depending on the configuration and security requirements

Modelling the Power Cost of Application Software Running on Servers

One of the most important aspects of managing data centres is controlling the power consumption of applications running on servers. Developers, in particular, should evaluate each of their applications from a power consumption point of view. One can conduct an evaluation by creating models that predict power usage while running applications on servers. For this purpose, this study creates a non-exclusive test bench that can collect data on subsystem utilization by using a performance counter tool. Based on the selected subsystem performance, various models have been created to estimate the power consumption of applications running on servers. The author's models are created based on collecting the performance on four subsystems (i.e. the CPU, Memory, Disk and Interface) by Collectd tool, and the actual power consumption of a machine using a TED5000 power meter. These subsystems have been chosen because they are the components of the server that consume the most power. In addition, as the experiments in this study demonstrate, using these subsystems as the model's input is the most efficient selection across different hardware platforms. The accuracy of the models is affected by the model inputs selection. Creating the model requires several steps: (i) connect the power meter to the server and install all the required packages such as Collectd; (ii) perform workloads on the selected subsystems; (iii) collect and simplify the data (subsystems counters and actual power) that has been stored during performing the workloads; and (iv) train the data by a modelling technique in order to create the model. This work has seven dimensions; (i) collection of the performance counters and the actual power consumption of a system, and simplification of the collected data; (ii) introduction of a simple test bench for modelling and estimation of the power consumption of an application; (iii) introduction of two modelling techniques: Neural Network and Linear Regression; (iv) design of two types of workloads; (v) use of three real servers with different configurations; (vi) use of four scenarios to validate the models; (vii) proof of the importance of the subsystems selection; and (viii) automation of the test bench. With these models, power meter devices will no longer be necessary in measuring power consumption. Instead, the models can be used to predict power consumption. Generally, Neural Network models have fewer errors than Linear Regression models, and all the models (Neural Network or Linear Regression) perform better with long time workload design

A Scalable, Secure, and Energy-Efficient Image Representation for Wireless Systems

The recent growth in wireless communications presents a new challenge to multimedia communications. Digital image transmission is a very common form of multimedia communication. Due to limited bandwidth and broadcast nature of the wireless medium, it is necessary to compress and encrypt images before they are sent. On the other hand, it is important to efficiently utilize the limited energy in wireless devices. In a wireless device, two major sources of energy consumption are energy used for computation and energy used for transmission. Computation energy can be reduced by minimizing the time spent on compression and encryption. Transmission energy can be reduced by sending a smaller image file that is obtained by compressing the original highest quality image. Image quality is often sacrificed in the compression process. Therefore, users should have the flexibility to control the image quality to determine whether such a tradeoff is acceptable. It is also desirable for users to have control over image quality in different areas of the image so that less important areas can be compressed more, while retaining the details in important areas. To reduce computations for encryption, a partial encryption scheme can be employed to encrypt only the critical parts of an image file, without sacrificing security. This thesis proposes a scalable and secure image representation scheme that allows users to select different image quality and security levels. The binary space partitioning (BSP) tree presentation is selected because this representation allows convenient compression and scalable encryption. The Advanced Encryption Standard (AES) is chosen as the encryption algorithm because it is fast and secure. Our experimental result shows that our new tree construction method and our pruning formula reduces execution time, hence computation energy, by about 90%. Our image quality prediction model accurately predicts image quality to within 2-3dB of the actual image PSNR

Performance-efficient cryptographic primitives in constrained devices

PhD ThesisResource-constrained devices are small, low-cost, usually fixed function and very limitedresource devices. They are constrained in terms of memory, computational capabilities, communication bandwidth and power. In the last decade, we have seen widespread use of these devices in health care, smart homes and cities, sensor networks, wearables, automotive systems, and other fields. Consequently, there has been an increase in the research activities in the security of these devices, especially in how to design and implement cryptography that meets the devices’ extreme resource constraints. Cryptographic primitives are low-level cryptographic algorithms used to construct security protocols that provide security, authenticity, and integrity of the messages. The building blocks of the primitives, which are built heavily on mathematical theories, are computationally complex and demands considerable computing resources. As a result, most of these primitives are either too large to fit on resource-constrained devices or highly inefficient when implemented on them. There have been many attempts to address this problem in the literature where cryptography engineers modify conventional primitives into lightweight versions or build new lightweight primitives from scratch. Unfortunately, both solutions suffer from either reduced security, low performance, or high implementation cost. This thesis investigates the performance of the conventional cryptographic primitives and explores the effect of their different building blocks and design choices on their performance. It also studies the impact of the various implementations approaches and optimisation techniques on their performance. Moreover, it investigates the limitations imposed by the tight processing and storage capabilities in constrained devices in implementing cryptography. Furthermore, it evaluates the performance of many newly designed lightweight cryptographic primitives and investigates the resources required to run them with acceptable performance. The thesis aims to provide an insight into the performance of the cryptographic primitives and the resource needed to run them with acceptable performance. This will help in providing solutions that balance performance, security, and resource requirements for these devices.The Institute of Public Administration in Riyadh, and the Saudi Arabian Cultural Bureau in Londo