Sharif Digital Repository

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... 

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... 

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... 

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... 

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... 

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... 

The expansion of technology and the increasing use of mobile devices and smartphones have aected various aspects of personal and social life. These include the use of personal mobile devices in enterprise environments called BYODs have a number of positive and negative eects. On the one hand, it would be more cost-eective for an organization or business environment for users to use their own devices, but on the other hand, it poses numerous security and information challenges that are important to manage. These include disrupting the user’s privacy or disseminating organization information to personal devices and thus violating the organization’s security policies. In this study, a model is... 

Cloud computing has a significant role in expanding applications of the Internet of Things (IoT). Currently, applications such as virtual reality and augmented reality require low latency, which is not achievable using traditional cloud computing in some scenarios. Edge computing is a new approach in IoT, which solves some of the limitations of the cloud computing by extending and developing its operations. Reducing response time and network traffic are some of the most important achievements of edge computing. Despite of its numerous advantages over cloud computing, edge computing faces serious challenges such as virtualization, implementation infrastructure, resource allocation and task... 

The rapid growth of Android operating system alongside its open-source nature has made it as the most popular operating system of mobile devices. On the other hand, regarding the increasing computational power of mobile devices, a wide variety of applications are coming to this type of devices. Meanwhile unfortunately many malicious softwares trying to keep up with other applications, are targeting this popular operating system. Therefore with regard to the fact that this type of devices usually store private and sensitive information of their users, security of mobile operating systems is considered very important. Having this matter in mind, the goal of this research work has been... 

Privacy preserving data mining helps organizations and companies not only to deal with privacy concerns of customers and regular limitations, but also to benefit from collaborative data mining. Utilizing cryptographic techniques and secure multiparty computation (SMC) are among widely employed approaches for preserving privacy in distributed data mining. The general purpose of secure multiparty computation protocols to compute specific functions on private inputs of parties in a collaborative manner and without revealing their private inputs. Providing rigorous security proof of secure multiparty computation makes it a good choice for privacy preservation, despite of its cryptographic... 

One of the applications of Internet of things (IoT) is its usage in the eHealth area. Various types of sensors (e.g., sensor to measure heart health, blood sugar levels, and respiratory) exist that not only provide required information for patients, but also send the health information to hospital staff through the network. Leveraging this technology in various intensive care units of hospital facilitate nurses and medical staff in monitoring of patients. However, moving towards these environments leads to new security challenges. One of the most important challenges is controlling access to sensors’ data and preserving patients privacy so that doctor and nurses should access patients’... 

Cloud computing is a new computing environment where computing infrastructure, platform and software are provided as a service. Rapid growth of cloud environments has increased the importance of security requirements and challenges for both service providers and users in cloud. Two main security issues in software as a service (SaaS) delivery model are access control and privacy preserving in basic web services and also in composite services obtaining through the automatic composition and inference of policies from the ones specified for basic services. In this thesis, we present a privacy preserving access control model and framework for service composition in SaaS delivery model of cloud... 

While data outsourcing provides some benefits, it suffers from new privacy and security concerns, mainly about the confidentiality and integrity of the stored sensitive data, as well as enforcing access control policies. Current solutions to these aims are not comprehensive and consider only one aspect of security requirements. A secure DBMS architecture is introduced that simultaneously considers confidentiality, integrity and access control enforcement requirements. The transparency of security functions from data owner, service providers, and applications facilitates the operationality of the solution.Additionally, a new indexing technique for character encrypted data is proposed that... 

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... 

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... 

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... 

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... 

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... 

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...