Sharif Digital Repository

Opportunistic delay tolerance networks are widely used networks that do not require infrastructure. Many routing algorithms have been proposed for these networks in which nodes need to compare their metrics (such as visit frequency, node geographical location, etc.)Therefore, routing in these networks has a high security risk and the possibility of violating privacy. There are many ways to protect privacy, but these methods have limitations: some are limited to vehicles and some are limited to social networks and node communities. Also, more general methods require a lot of complexity, including processing time, storage resources, and key management.In this study, we propose a method with... 

Coming to the generation of technology, where everything is possible through the Internet contributes a significant proportion to privacy protection. Several Privacy protection technologies have been launched to maintain the confidentiality of user information. Tor, also known as an Onion Router, is indeed the largest global anonymized network technology, including over 7000 distinct domain controller endpoints located all over the globe. Various kinds of wrongdoings are increasing day by day such as terrorism, abuse of the child is increasing using the network. To stop this monitoring plan is needed to develop. To enable this all the hacking mechanisms along with the architecture were... 

With the help of cloud computing, easy and fast access to a wide range of computing resources through the network is provided for a wide range of users. Cloud computing, on the other hand, faces security challenges in protecting users' privacy and access control because the cloud service provider is not a trusted entity, so it is possible to access or disclose sensitive data. Various solutions have been proposed to simultaneously meet the above two security requirements. The most well-known solution in this field is "Attribute-Based Encryption".In this dissertation, after reviewing the existing schemes to respond to the obstacles to implementing attribute-based encryption, an attribute-based... 

Nowadays, intelligent transportation systems have become possible and practical with the help of vehicular ad-hoc networks. This network is a subset of mobile ad-hoc networks introduced and studied separately due to its unique properties. With the help of vehicular ad-hoc networks, the level of road and drivers safety is increased and safety messages can be sent to road side units or other vehicles, so real-time is one of the main requirements of these networks. Other advantages of implementing such networks include providing entertainment and internet access services.On the other hand, these networks face various challenges, including routing data packets, preserving security requirements,... 

Impressive progress in hardwares and developing encryption algorithms in last two decades are caused increase in using encryption protocols in network communications. In last decade, users use privacy preserving networks like Jap and Tor to protect their privacy. These networks protect users' data from eavesdroppers by using three-layer encryption and intermediate nodes between user and target website. Recent researches show that Deep Neural Networks can predict websites viewed by users with high accuracy. In other words, privacy preserving networks suffer from information leakage. In this research, we introduced some of the most powerful methods in encrypted traffic classification and then... 

Differential privacy provides a powerful definition for protecting data privacy by adding noise. Differential privacy mechanisms add noise to the responses of queries made to a database. Differential privacy challenges the learning of useful information from a dataset without leaking any information about the individuals present in that dataset. However, studies have shown that these mechanisms make assumptions about the data that, if not met, can lead to privacy leaks. One of these assumptions is the lack of correlation between data. If an attacker is aware of the correlation between data, common mechanisms cannot guarantee differential privacy.This thesis proposes a solution for adding... 

Recent advances in Machine Learning and specially Deep Learning, have caused a dramatic increase in the use of these algorithms in different applications, such as sickness diagnosis, anomaly detection, malware detection, and etc. Since training deep neural networks requires a high cost in terms of both gathering loads of labeled data and computing and human resources, deep learning models are a part of an organization’s intellectual property and so, the importance of securing these models is increasing. One of the most important types of attacks that compromises the security of deep neural networks is black-box adversarial example attack. In adversarial example attacks, the adversary... 

With the dramatic advancements in information technology and the industry requirements for security and privacy, proof systems play a crucial role in cryptography. Among the vast variety of proof systems, succinct non-interactive arguments (SNARG) seem to be the most appealing class of proof systems, due to their attractive properties. SNARGs are usually made up of two constructive components, namely the information theoretic part and the cryptographic part. The GKR protocol was introduced as a proof system for a tractable family of languages called “log-Space Uniform Circuits”. The log-space uniformity is a necessary condition for the protocol to be succinct. Hence, it is not possible to... 

The security and convenience of digital payment methods have made them an essential part of people's daily lives. As a result, the possibility of using these methods in an offline environment without the need to communicate with the payment service provider is of great importance. To make this possible, a digital currency system should enable users to securely control their assets without the help of an intermediary and act according to established laws to combat financial crimes. Otherwise, this system will not be usable by the public or on a large scale. To solve this problem, a scheme with the possibility of offline payment by customers, prevention and detection of double spending by... 

The problem of separation of audio sources is one of the oldest issues raised in the field of audio processing, which has been studied for more than half a century. The main focus of recent research in this field has been on improving the sound quality resulting from the separation of sound sources with the help of deep neural networks. This is despite the fact that in most applications of audio source separation, such as the application of meeting transcription, we do not need the separated audio of people. Rather, we need a pipeline of converting overlapping speech to text, which, by receiving the audio in which several people have spoken, outputs the text spoken by the people present in... 

The multi people tracking is considered a fundamental problem in computer vision, which has received considerable attention from academic and commercial fields. This issue deals with a set of proposed methods that track the movement path of several humans in a video-like sequence. The problem of multi people tracking is the foundation of other computer vision problems, including human gesture estimation, motion recognition, and behavioral analysis, and is mainly used in emerging fields such as automatic car driving, smart security, service robots, etc. Although many methods have been proposed and investigated to solve the above problem; But there are still serious challenges, such as severe... 

large-scale data collection from multiple sources to a single entity, such as a cloud provider, poses a challenging problem for implementing centralized machine learning algorithms. Constraints such as privacy protection and restrictive access policies that prevent accessing personally identifiable information hinder the development of centralized machine learning algorithms in important and sensitive domains like healthcare. However, from early disease detection to discovering new drugs, leveraging artificial intelligence in this domain is a fun-damental necessity. As a potential solution, federated learning has been proposed, allowing data owners (users) to jointly train a shared machine... 

With the dramatic advancements in information technology and the industry requirements for security and privacy, proof systems play a crucial role in cryptography. Among the vast variety of proof systems, succinct non-interactive arguments (SNARG) seem to be the most appealing class of proof systems, due to their attractive properties. SNARGs are usually made up of two constructive components, namely the information theoretic part and the cryptographic part. The GKR protocol was introduced as a proof system for a tractable family of languages called “log-Space Uniform Circuits”. The log-space uniformity is a necessary condition for the protocol to be succinct. Hence, it is not possible to... 

The applications of Internet of Things technology are increasing day by day. In the Internet of Things, various devices are connected to each other with the help of the Internet and perform various operations automatically. Today, this technology has various applications in smart city, smart home, smart car, as well as military industries and industrial factories. One of the newest applications is its use in the field of health and hygiene, which is known as the Internet of Medical Things or Smart Health. With the emergence of new epidemic diseases, the importance of this application becomes more clear. Smart health helps the patient. without going to the hospital and doctor in person, to... 

The rapid evolution of artificial intelligence (AI) technologies has led to the widespread adoption of AI systems in diverse research and industrial fields. Deep neural networks, at the forefront of AI's power, demonstrate high performance by leveraging large volumes of training data. However, acquiring such vast amounts of data requires collaboration among individual data owners, who may have concerns about privacy. To address these concerns, various privacy-preserving methodologies have been proposed. These methodologies share a common goal of striking a balance between preserving privacy and maintaining data utility. This study aims to explore and analyze these privacy protection...