Performance Analysis of Loss Multilevel Quantization on the Secret Key Generation Scheme in Indoor Wireless Environment

The necessity for secured communication devices that has limited computing power has encouraged the development of key generation scheme. The generation of a symmetric key scheme that utilizes randomness of wireless channels offers a most promising solution as a result of the easy distribution of secret key mechanisms. In the last few years, various schemes have been proposed, but there are trade-offs between the performance parameters used. The expected parameters are the low Key Disagreement Rate (KDR), the high Key Generation Rate (KGR), and the fulfillment of standard of randomness. In this paper, we propose the use of a combination of pre-processing methods with multilevel lossy quantization to overcome the trade-off of performance parameters of the Secret Key Generation (SKG) scheme. Pre-process method used to improve reciprocity so as to reduce KDR, whereas multilevel quantization is used to improve the KGR. We use Kalman as the pre-processing method and Adaptive Quantization, Modified Multi-Bit (MMB), and 2-ary Quantization as the multilevel lossy quantization. Testing is conducted by comparing the performance between direct quantization with the addition of the pre-processing method in various multilevel lossy quantization schemes. The test results show that the use of Kalman as pre-processing methods and multilevel lossy quantization can overcome the trade-off performance parameters by reducing KDR and increasing KGR, with the best performance, was obtained when we use adaptive quantization. The resulting secret key has also fulfilled 6 random tests with p values greater than 0.01

H2B: Heartbeat-based Secret Key Generation Using Piezo Vibration Sensors

We present Heartbeats-2-Bits (H2B), which is a system for securely pairing wearable devices by generating a shared secret key from the skin vibrations caused by heartbeat. This work is motivated by potential power saving opportunity arising from the fact that heartbeat intervals can be detected energy-efficiently using inexpensive and power-efficient piezo sensors, which obviates the need to employ complex heartbeat monitors such as Electrocardiogram or Photoplethysmogram. Indeed, our experiments show that piezo sensors can measure heartbeat intervals on many different body locations including chest, wrist, waist, neck and ankle. Unfortunately, we also discover that the heartbeat interval signal captured by piezo vibration sensors has low Signal-to-Noise Ratio (SNR) because they are not designed as precision heartbeat monitors, which becomes the key challenge for H2B. To overcome this problem, we first apply a quantile function-based quantization method to fully extract the useful entropy from the noisy piezo measurements. We then propose a novel Compressive Sensing-based reconciliation method to correct the high bit mismatch rates between the two independently generated keys caused by low SNR. We prototype H2B using off-the-shelf piezo sensors and evaluate its performance on a dataset collected from different body positions of 23 participants. Our results show that H2B has an overwhelming pairing success rate of 95.6%. We also analyze and demonstrate H2B's robustness against three types of attacks. Finally, our power measurements show that H2B is very power-efficient

Sparse Signal Processing Concepts for Efficient 5G System Design

As it becomes increasingly apparent that 4G will not be able to meet the emerging demands of future mobile communication systems, the question what could make up a 5G system, what are the crucial challenges and what are the key drivers is part of intensive, ongoing discussions. Partly due to the advent of compressive sensing, methods that can optimally exploit sparsity in signals have received tremendous attention in recent years. In this paper we will describe a variety of scenarios in which signal sparsity arises naturally in 5G wireless systems. Signal sparsity and the associated rich collection of tools and algorithms will thus be a viable source for innovation in 5G wireless system design. We will discribe applications of this sparse signal processing paradigm in MIMO random access, cloud radio access networks, compressive channel-source network coding, and embedded security. We will also emphasize important open problem that may arise in 5G system design, for which sparsity will potentially play a key role in their solution.Comment: 18 pages, 5 figures, accepted for publication in IEEE Acces

Skema Secret Key Generation (SKG) untuk Keamanan pada Sistem Komunikasi di Lingkungan Wireless

Skema Secret Key Generation (SKG) yang mengeksploitasi sifat reciprocity dan keacakan kanal wireless untuk membangkitkan secret key telah menjadi area penelitian yang semakin menarik dan menjanjikan. Terdapat 3 permasalahan utama dalam pembangunan skema SKG yang efisien yang harus diatasi, yaitu trade-off antara parameter performansi Key Disagreement Rate (KDR) dan Key Generation Rate (KGR), tingginya kompleksitas implementasi karena banyaknya tahapan yang harus dilalui, serta tidak efisiennya skema SKG yang dibangun sehingga tidak sesuai jika diimplementasikan pada perangkat Internet of Things(IoT) yang memiliki keterbatasan sumber daya. Disertasi ini berkontribusi dalam mengatasi ketiga permasalahan tersebut. Kontribusi pertama yang dilakukan untuk mengatasi trade-off antara parameter performansi KDR dan KGR adalah didapatkannya kombinasi yang optimal antara metode pra proses yaitu Kalman Filter, Modified Polynomial Regression (MPR), serta Savitzky Golay Filter dan kuantisasi multilevel. Hasil yang didapat adalah penurunan KDR dan peningkatan KGR dibandingkan dengan skema yang eksisting. Kontribusi kedua dari disertasi ini adalah mekanisme penyederhanaan skema SKG dengan kombinasi metode Modified Kalman (MK) serta Combined Multilevel Quantization (CMQ) sehingga bisa dihasilkan secret key yang identik tanpa melalui tahap rekonsiliasi informasi. Hasil pengujian yang dilakukan menghasilkan 4 blok 128-bit data di lingkungan tanpa halangan serta 2 blok 128-bit data yang memiliki KDR sebesar 0 sehingga tidak memerlukan koreksi untuk mendapatkan secret key yang identik. Kontribusi ketiga dari disertasi ini adalah didapatkannya skema SKG Signal Strength Exchange (SSE) yang efisien dalam hal waktu komputasi dan overhead komunikasi dengan menggunakan metode Synchronized Quantization (SQ) sebagai bagian dari skema SKG SSE. Hasil yang didapat menunjukkan penurunan waktu komputasi menjadi sebesar 3.8% dan overhead komunikasi menjadi sebesar 34% skema yang eksisting. Kontribusi yang dihasilkan dalam disertasi ini diharapkan dapat menjadi salah satu solusi alternatif pembentukan kunci simetris yang tidak membutuhkan kompleksitas komputasi serta Trusted Third Party (TTP), sehingga cocok jika digunakan pada berbagai aplikasi IoT