Cryptographically secure random number generators usually require an outside seed to be initialized. Other solutions instead use a continuous entropy stream to ensure that the internal state of the generator always remains unpredictable. This thesis analyses four such generators with entropy inputs. Furthermore, different ways to estimate entropy is presented and a new method useful for the generator analysis is developed. The developed entropy estimator performs well in tests and is used to analyse entropy gathered from the different generators. Furthermore, all the analysed generators exhibit some seemingly unintentional behaviour, but most should still be safe for use. / Kryptografiskt säkra slumptalsgeneratorer behöver ofta initialiseras med ett oförutsägbart frö. En annan lösning är att istället konstant ge slumptalsgeneratorer entropi. Detta gör det möjligt att garantera att det interna tillståndet i generatorn hålls oförutsägbart. I den här rapporten analyseras fyra sådana generatorer som matas med entropi. Dessutom presenteras olika sätt att skatta entropi och en ny skattningsmetod utvecklas för att användas till analysen av generatorerna. Den framtagna metoden för entropiskattning lyckas bra i tester och används för att analysera entropin i de olika generatorerna. Alla analyserade generatorer uppvisar beteenden som inte verkar optimala för generatorns funktionalitet. De flesta av de analyserade generatorerna verkar dock oftast säkra att använda.

The race to computing power increases every day in the simulation community. A few years ago, scientists have started to harness the computing power of Graphics Processing Units (GPUs) to parallelize their simulations. As with any parallel architecture, not only the simulation model implementation has to be ported to the new parallel platform, but all the tools must be reimplemented as well. In the particular case of stochastic simulations, one of the major element of the implementation is the pseudorandom numbers source. Employing pseudorandom numbers in parallel applications is not a straightforward task, and it has to be done with caution in order not to introduce biases in the results of the simulation. This problematic has been studied since parallel architectures are available and is called pseudorandom stream distribution. While the literature is full of solutions to handle pseudorandom stream distribution on CPU-based parallel platforms, the young GPU programming community cannot display the same experience yet. In this thesis, we study how to correctly distribute pseudorandom streams on GPU. From the existing solutions, we identified a need for good software engineering solutions, coupled to sound theoretical choices in the implementation. We propose a set of guidelines to follow when a PRNG has to be ported to GPU, and put these advice into practice in a software library called ShoveRand. This library is used in a stochastic Polymer Folding model that we have implemented in C++/CUDA. Pseudorandom streams distribution on manycore architectures is also one of our concerns. It resulted in a contribution named TaskLocalRandom, which targets parallel Java applications using pseudorandom numbers and task frameworks. Eventually, we share a reflection on the methods to choose the right parallel platform for a given application. In this way, we propose to automatically build prototypes of the parallel application running on a wide set of architectures. This approach relies on existing software engineering tools from the Java and Scala community, most of them generating OpenCL source code from a high-level abstraction layer.

Surveillance wireless sensor networks (WSNs) are highly vulnerable to the failure of the base station (BS) because attackers can easily render the network useless for relatively long periods of time by only destroying the BS. The time and effort needed to destroy the BS is much less than that needed to destroy the numerous sensing nodes. Previous works have tackled BS failure by deploying a mobile BS or by using multiple BSs, which requires extra cost. Moreover, despite using the best electronic countermeasures, intrusion tolerance systems and anti-traffic analysis strategies to protect the BSs, an adversary can still destroy them. The new BS cannot trust the deployed sensor nodes. Also, previous works lack both the procedures to ensure network reliability and security during BS failure such as storing then sending reports concerning security threats against nodes to the new BS and the procedures to verify the trustworthiness of the deployed sensing nodes. Otherwise, a new WSN must be re-deployed which involves a high cost and requires time for the deployment and setup of the new WSN. In this thesis, we address the problem of reliable recovery from a BS failure by proposing a new security architecture called Surveillance Security (SurvSec). SurvSec continuously monitors the network for security threats and stores data related to node security, detects and authenticates the new BS, and recovers the stored data at the new BS. SurvSec includes encryption for security-related information using an efficient dynamic secret sharing algorithm, where previous work has high computations for dynamic secret sharing. SurvSec includes compromised nodes detection protocol against collaborative work of attackers working at the same time where previous works have been inefficient against collaborative work of attackers working at the same time. SurvSec includes a key management scheme for homogenous WSN, where previous works assume heterogeneous WSN using High-end Sensor Nodes (HSN) which are the best target for the attackers. SurvSec includes efficient encryption architecture against quantum computers with a low time delay for encryption and decryption, where previous works have had high time delay to encrypt and decrypt large data size, where AES-256 has 14 rounds and high delay. SurvSec consists of five components, which are: 1. A Hierarchical Data Storage and Data Recovery System. 2. Security for the Stored Data using a new dynamic secret sharing algorithm. 3. A Compromised-Nodes Detection Algorithm at the first stage. 4. A Hybrid and Dynamic Key Management scheme for homogenous network. 5. Powerful Encryption Architecture for post-quantum computers with low time delay. In this thesis, we introduce six new contributions which are the followings: 1. The development of the new security architecture called Surveillance Security (SurvSec) based on distributed Security Managers (SMs) to enable distributed network security and distributed secure storage. 2. The design of a new dynamic secret sharing algorithm to secure the stored data by using distributed users tables. 3. A new algorithm to detect compromised nodes at the first stage, when a group of attackers capture many legitimate nodes after the base station destruction. This algorithm is designed to be resistant against a group of attackers working at the same time to compromise many legitimate nodes during the base station failure. 4. A hybrid and dynamic key management scheme for homogenous network which is called certificates shared verification key management. 5. A new encryption architecture which is called the spread spectrum encryption architecture SSEA to resist quantum-computers attacks. 6. Hardware implementation of reliable network recovery from BS failure. The description of the new security architecture SurvSec components is done followed by a simulation and analytical study of the proposed solutions to show its performance.

Surveillance wireless sensor networks (WSNs) are highly vulnerable to the failure of the base station (BS) because attackers can easily render the network useless for relatively long periods of time by only destroying the BS. The time and effort needed to destroy the BS is much less than that needed to destroy the numerous sensing nodes. Previous works have tackled BS failure by deploying a mobile BS or by using multiple BSs, which requires extra cost. Moreover, despite using the best electronic countermeasures, intrusion tolerance systems and anti-traffic analysis strategies to protect the BSs, an adversary can still destroy them. The new BS cannot trust the deployed sensor nodes. Also, previous works lack both the procedures to ensure network reliability and security during BS failure such as storing then sending reports concerning security threats against nodes to the new BS and the procedures to verify the trustworthiness of the deployed sensing nodes. Otherwise, a new WSN must be re-deployed which involves a high cost and requires time for the deployment and setup of the new WSN. In this thesis, we address the problem of reliable recovery from a BS failure by proposing a new security architecture called Surveillance Security (SurvSec). SurvSec continuously monitors the network for security threats and stores data related to node security, detects and authenticates the new BS, and recovers the stored data at the new BS. SurvSec includes encryption for security-related information using an efficient dynamic secret sharing algorithm, where previous work has high computations for dynamic secret sharing. SurvSec includes compromised nodes detection protocol against collaborative work of attackers working at the same time where previous works have been inefficient against collaborative work of attackers working at the same time. SurvSec includes a key management scheme for homogenous WSN, where previous works assume heterogeneous WSN using High-end Sensor Nodes (HSN) which are the best target for the attackers. SurvSec includes efficient encryption architecture against quantum computers with a low time delay for encryption and decryption, where previous works have had high time delay to encrypt and decrypt large data size, where AES-256 has 14 rounds and high delay. SurvSec consists of five components, which are: 1. A Hierarchical Data Storage and Data Recovery System. 2. Security for the Stored Data using a new dynamic secret sharing algorithm. 3. A Compromised-Nodes Detection Algorithm at the first stage. 4. A Hybrid and Dynamic Key Management scheme for homogenous network. 5. Powerful Encryption Architecture for post-quantum computers with low time delay. In this thesis, we introduce six new contributions which are the followings: 1. The development of the new security architecture called Surveillance Security (SurvSec) based on distributed Security Managers (SMs) to enable distributed network security and distributed secure storage. 2. The design of a new dynamic secret sharing algorithm to secure the stored data by using distributed users tables. 3. A new algorithm to detect compromised nodes at the first stage, when a group of attackers capture many legitimate nodes after the base station destruction. This algorithm is designed to be resistant against a group of attackers working at the same time to compromise many legitimate nodes during the base station failure. 4. A hybrid and dynamic key management scheme for homogenous network which is called certificates shared verification key management. 5. A new encryption architecture which is called the spread spectrum encryption architecture SSEA to resist quantum-computers attacks. 6. Hardware implementation of reliable network recovery from BS failure. The description of the new security architecture SurvSec components is done followed by a simulation and analytical study of the proposed solutions to show its performance.