Anonymous Communication Research Articles

ДОСЛІДЖЕННЯ МОДЕЛЕЙ АНОНІМНОЇ МАРШРУТИЗАЦІЇ

Numerous solutions have been created for online anonymous communication. We do evaluations of security on several systems. We examine features such as Onion Routing, anonymous VPN services, probabilistic anonymity, and deterministic anonymity among different systems. There are also additional forms of anonymous communication that are discussed, including messaging, peer-to-peer communication, using the web, emailing, and using other Internet apps. We then go on to show several attack methods that aim to identify people who communicate anonymously. The objective of the research is to achieve an exact adjust between guaranteeing the adequacy and dependability of message delivery and ensuring customer anonymity. The NIAR model's non-interactive highlight makes it more valuable since it licenses secure communication without requiring nonstop client support. Communication privacy is threatened by an ever-growing volume of data generated by an ever-growing number of networked devices. Because of this, Anonymous Communication Systems (ACSs)—which offer the privacy qualities of anonymity, unsinkability, and observability—are recommended to conceal the relationship between transmitted communications and their senders and recipients. The objective of this essay is to evaluate the literature on Dining Cryptographers Networks (DCNs) in the subject of ACSs. Since the DCN-based techniques offer unconditional guarantees of observability, they are information-theoretically safe. Their computation and communication expense was considered high at the time, and scalability issues arose, which originally impeded their use for anonymous communications. By satisfying these targets, the research improves the state of encrypted communication systems and opens the door to a day when protecting client security will be a best need without sacrificing message delivery's significant dependability and efficiency.

Связь моральной направленности принимаемых решений в ситуациях потенциального кибербуллинга с индивидуально-психологическими особенностями студентов

Background. The Internet environment creates a special reality for communication, in which socially accepted systems of norms and values are often no longer valid. In conflict situations, the anonymity of Internet communication may reduce the degree of personal moral responsibility for the “digital deeds” and lead to the choice of unethical ways of behaviour, which include cyberbullying. Highlighting the system of cognitive and personal factors involved in the regulation of the moral orientation of behaviour in online communication is an urgent scientific task. Objective. The aim is to explore the regulation of moral orientation in decision-making in situations containing possibility of cyberbullying. The following psychological features of students are considered: the level of moral development, the level of communicative skill development, the perception of cyberbullying as a phenomenon. Study Participants. The sample included 85 respondents of varying ages, ranging from 18 to 26 years old (M = 21; SD = 1.8). Methods. The study engaged the following materials: the “Justice-Care” technique by S.V. Molchanov; communication skills test by L. Michelson (adapted by Yu.Z. Gilbukh); authors' techniques “Open questions” and “Case-method” applied for identifying the content of ideas about cyberbullying and orientation of decision-making (ethical/unethical) in situations of potential cyberbullying. Results. A significant positive correlation (ρ-Spearman; p < 0.05) was found between the ethical choice of decisions in situations of potential cyberbullying, subscales of moral development (“Self-sacrifice”, “Self-respect”) and the content of ideas about cyberbullying. Moreover, significant negative correlations (ρ-Spearman; p < 0.05) were identified between the unethical choices in the investigated situations, subscale of “Preconventional” level of moral development, and communication skills. Conclusions. The moral orientation of the decisions we make in situations of potential cyberbullying is significantly related to the following individual psychological features of students: (1) students who often choose ethical decisions have fully formed ideas about cyberbullying as a phenomenon, they do not prioritize their own interests and consider the values of others; (2) students who choose unethical decisions have low level of development of communication skills, look for personal gain in communication and less often consider the values of other people.

On the Closed-Form Detection Error Rate Analysis in Physical Layer Anonymous Communications

On the Closed-Form Detection Error Rate Analysis in Physical Layer Anonymous Communications

A Secure Anonymous Identity-Based Virtual-Space Agreement Method for Crowds-Based Anonymous Communicate Scheme

Anonymous data exchange is in great demand in many situations, especially in remote control systems, in which a stable, secure, and secret data channel must be established between the controlling and controlled parties to distribute control commands and return data. In the previous work, we built a two-level Virtual-Space anonymous communication scheme based on the Crowds System for performing secret data exchange in remote control systems. However, as an essential part of security and anonymity, participating nodes’ identity declaration and session key agreement phases were not well designed. In this paper, we redesign the identity agreement and declaration process and design an identity-based Virtual-Space agreement method using the extended Chebyshev Chaotic Maps. In this approach, we transform the identity declaration process into a multilevel Virtual-Space agreement problem, where a series of security-progressive Virtual-Space addresses are negotiated between the controller and the controlled nodes. The protocol can handle the case where there are multiple controllers in the system, and the negotiated Virtual-Space depends on the identity of the controller and the controlled node, so different controllers do not affect each other. The designed protocol is verified on Freenet, and we conclude this paper with a detailed security analysis of the method to prove that the method satisfies forward security.

An Intersectional Analysis of Aotearoa New Zealand Journalists’ Online and Offline Experiences of Abuse, Threats and Violence

ABSTRACT Criticism towards journalists has increased significantly since the internet created easy and anonymous communication and has turned more abusive and threatening in recent years, becoming a regular feature of journalists’ work environment, particularly for women. This article presents survey data about the amount and nature of online and offline abuse, threats and violence experienced by journalists at Aotearoa New Zealand's largest news media company, Stuff. All respondents had experienced abuse, violence and/or threats, which they widely considered to be part of the job, but women received more identity and appearance-based abuse and men experienced more in-person threats of, and actual violence. Gender plays a part in how the journalists cope with the abrasive abuse received because of their job, with many more women and particularly Māori women considering leaving the profession. In line with calls for more intersectional analysis of journalists’ workplace experiences, our study considers the complex and nuanced ways that ethnicity intersects with gender to shape Māori and Pākehā journalists’ encounters with abuse, threats and violence. For instance, our subset of Māori women journalists experienced the highest rates of offline threats and violence.

Enhancing the Unlinkability of Circuit-Based Anonymous Communications with k-Funnels

Anonymous communication systems are essential tools for preserving privacy and freedom of expression. However, traffic analysis attacks make it challenging to maintain unlinkability in circuit-based anonymity networks like Tor, enabling adversaries to deanonymize communications. To address this problem, we introduce k-funnel, a new security primitive that enhances the unlinkability of circuit-based anonymity networks, and we present BriK, a Tor pluggable transport that implements k-funnels. k-Funnels offer k-anonymity to a group of k clients by jointly tunneling their circuits' traffic through a bridge while ensuring that the client-generated flows are indistinguishable. BriK incorporates several defense mechanisms against traffic analysis attacks, including traffic shaping schemes, synchronization protocols, and approaches for monitoring exposure to statistical disclosure attacks. Our evaluation shows that BriK is able to support web browsing and video streaming while offering k-anonymity. We evaluate the security of BriK against traffic correlation attacks leveraging state-of-the-art deep learning classifiers without considering auxiliary information and find it highly resistant. Although k-funnels require the cooperation of mutually trusted clients, limiting their coordination, our work presents a new practical solution to strengthen unlinkability in circuit-based anonymity systems.

A comprehensive analysis of website fingerprinting defenses on Tor

Website fingerprinting (WF) enables eavesdroppers to identify the website a user is visiting by network surveillance, even if the traffic is protected by anonymous communication technologies such as Tor. To avoid this, several defense schemes have been proposed to protect users from the hazard of website fingerprinting attacks. However, some defenses are defeated by new attacks soon since they can not provide provable security guarantees; some defenses can not be deployed in practice since they incur high bandwidth overhead and latency overhead. In this paper, we survey existing WF defense schemes and make a comprehensive analysis. First, we divide WF defenses into four categories and introduce their principles and characteristics separately. Then, we point out some unreasonable settings in previous works and use a new experimental setting to evaluate WF defenses on a public dataset. We find many WF defenses are not as effective as they claim to be. Besides, we investigate the deployment of WF defenses and discuss some potential problems. Finally, we make some suggestions for researchers to design a feasible WF defense and make suggestions for users to protect their privacy.

Port-Based Anonymous Communication Network: An Efficient and Secure Anonymous Communication Network.

With the rise of the internet, there has been an increasing focus on user anonymity. Anonymous communication networks (ACNs) aim to protect the identity privacy of users in the network. As a typical ACN, Tor achieves user anonymity by relaying user data through a series of relay nodes. However, this results in higher latency due to the transmission of network traffic between multiple nodes. This paper proposes a port-based anonymous communication network (PBACN) to address this issue. First, we propose a path construction algorithm. This algorithm describes constructing paths by partitioning the communication path information, which can reduce the probability of being discovered by adversaries. Secondly, we design a port-based source routing addressing method. During data transmission from the source to the destination, each node can directly forward the data by resolving the address into the port of each node. This method eliminates the need for table lookups, reducing the complexity of routing. Lastly, we propose an entropy-based metric to measure the anonymity of different ACNs. In terms of experimental evaluation, we quantitatively analyze the anonymity and end-to-end delay of various ACNs. The experimental results show that our proposed method reduces end-to-end delay by approximately 25% compared to Tor. When the adversary fraction is 20%, PBACN can improve the anonymity degree by approximately 4%.

A practical multi-tab website fingerprinting attack

The rapid development of Internet of Things technology has allowed a massive number of devices to be connected, resulting in a lot of private data being transmitted over the network. To protect the security and privacy, anonymous communication technologies such as Tor are widely deployed. They use complex mechanisms such as encryption and multi-hop forwarding to hide the communication relationship and content. However, much existing work on the website fingerprinting attack has proven that there is still a risk of privacy disclosure. Website fingerprinting attacks can extract side channel information from encrypted traffic to form a fingerprint that identifies the victim’s destination website. But most work is conducted in the ideal environments, assuming the absence of background traffic, which raises doubts about the effectiveness in the real world. In this paper, we relax the strong assumptions of the attack model and propose a practical multi-tab website fingerprinting attack. We first constructed a CNN model to distinguish whether the unknown traffic is generated by accessing a single web page or multiple web pages. Then we design a split point recognition method based on the BalanceCascade algorithm to separate the overlapping traffic. Furthermore, we build recognition models based on ResNet and multi-head self-attention mechanism to identify the tail-missing and head-overlapping traffic sequences respectively. Extensive experiments are carried out in the real-world scenario to evaluate the proposed method. When the time interval is randomly selected within 5–15s, we achieve an accuracy of 77.34% in split point recognition. And the accuracy of identifying the two pages is 88.19% and 63.02% respectively.

BCMIX: A Blockchain-Based Dynamic Self-Reconfigurable Mixnet

The increasing awareness of privacy preservation has led to a strong focus on mix networks (mixnets) protecting anonymity. As an efficient mixnet, cMix greatly reduces the latency, but brings privacy leakage risks due to the use of presetting mix nodes controlled by service providers. Besides, cMix is susceptible to blocking attacks that paralyze the anonymous service. In this paper, we combine blockchain with cMix, and come up with a BlockChain-based dynamic self-reconfigurable MIXnet (BCMIX) approach for anonymous communication. In BCMIX, we design PoW voting, IP sharding and VRF voting algorithms to select mix nodes from blockchain miners. With these voting algorithms, BCMIX can mitigate blocking attacks and blockchain Sybil attacks. Then we present an additive homomorphic mixnet protocol altered from cMix. Furthermore, we design a transaction-based key-exchange protocol for users and mix nodes to negotiate keys with each other, which resists Man-in-the-Middle attacks that exist in cMix. We also demonstrate the security and anonymity of BCMIX under formal security models. To evaluate BCMIX, we leverage the distribution of mining pools in the real-world to test the system’s performance and ability to resist the mentioned attacks. The results show that with the proper mining difficulty, the probability of an attacker launching collusion attacks and Sybil attacks is negligible. Compared with the existing anonymous systems, BCMIX provides better resilience to known attacks while enabling low-latency anonymous communication without requiring significant bandwidth or storage resources.

Data-Explainable Website Fingerprinting with Network Simulation

Website fingerprinting (WF) attacks allow an adversary to associate a website with the encrypted traffic patterns produced when accessing it, thus threatening to destroy the client-server unlinkability promised by anonymous communication networks. Explainable WF is an open problem in which we need to improve our understanding of (1) the machine learning models used to conduct WF attacks; and (2) the WF datasets used as inputs to those models. This paper focuses on explainable datasets; that is, we develop an alternative to the standard practice of gathering low-quality WF datasets using synthetic browsers in large networks without controlling for natural network variability. In particular, we demonstrate how network simulation can be used to produce explainable WF datasets by leveraging the simulator's high degree of control over network operation. Through a detailed investigation of the effect of network variability on WF performance, we find that: (1) training and testing WF attacks in networks with distinct levels of congestion increases the false-positive rate by as much as 200%; (2) augmenting the WF attacks by training them across several networks with varying degrees of congestion decreases the false-positive rate by as much as 83%; and (3) WF classifiers trained on completely simulated data can achieve greater than 80% accuracy when applied to the real world.

Data Classification of Dark Web using SVM and S3VM

Abstract: There are many issues regarding the dark web structural Type. It also increases the number of cybercrimes like illegal trade, forums, Terrorist activity. By understanding online criminal’s actions are challenging because the data is available in a very great extent amount. In a recent day the Online crimes are increasing all over the world. The data related to different types of frauds and scams, such as phishing schemes, identity theft etc. The data and discussion related to the act of hacking (hacktivist) activities, this often involve political or social causes. In some parts of dark web might be used for anonymous communication and the losing of sensitive information to explore wrong doing by governments or corporations. But in some countries the dark web might be used as a means to access information and content that is hardly restricted. The primary focus of this research is to develop a hybrid classification model that combines the strengths of deep learning and natural language processing algorithms. The model leverages a curated dataset of Dark Web content, meticulously labeled by content category, ranging from illegal commerce to cyber threats. By extracting relevant features from the textual and visual components of the data, the model demonstrates superior accuracy in distinguishing between different content categories

Enter the Paraverse: Challenging Assumptions of Live Music in the Metaverse

The Metaverse, a concept and buzzword echoing throughout industry and academic spaces, does not exist. In this paper we theorize about the object that does exist: the Paraverse, the global set of disconnected virtual worlds and virtual world platforms working independently to advance virtual world technology and culture. We present a novel system within the Paraverse named Soundscape.social: a multi-user virtual world where participants explore concert spaces containing pre-recorded, synchronous performances by independent musicians during the early stages of the COVID-19 pandemic. Through its design and implementation, we demonstrate how small teams of independent developers may quickly contribute to the fringes of the Paraverse, and thus play an essential role in driving innovation. We assessed the platform’s ability to foster communal listening experience through virtual ethnography, in-game data collection, and interviews with attendees and performers. Soundscape.social was successful at preventing abusive behaviour despite anonymous communication, respecting participant privacy through minimal in-game data collection, modelling anarchic community through a performance format that challenged hierarchical structures of listening, and fostering a novel understanding of liveness through listener autonomy and a novel asynchronous communication feature of interest we name "virtual graffiti." We further discuss opportunities for future work developing technologies that aid developers looking to create independent Paraverse applications, contributing to the future of virtual worlds and, perhaps, the Metaverse.

MQTT-A: A Broker-Bridging P2P Architecture to Achieve Anonymity in MQTT

The demand for privacy in the current digital era is continuously growing. This is particularly true in the context of IoT, in which huge amounts of data are handled. Communication anonymity is a fundamental requirement when high privacy levels should be guaranteed. On the other hand, very little attention has been devoted to this problem in the past scientific literature, when referring to MQTT, which is the de-facto standard for IoT communication. In this paper, we try to cover this gap. Specifically, we propose a new protocol, called MQTT-A, which extends the MQTT bridging mechanism to support the anonymity of both publishers and subscribers. This task is accomplished through the P2P collaboration of intermediate bridge brokers, which forward the requests of clients so that the final broker cannot understand the actual source/destination. Moreover, an anonymity-preserving topic discovery mechanism is provided, which allows clients to discover available topics and associated brokers, preventing client identification. Importantly, all the MQTT-A messages are exchanged by leveraging standard MQTT primitives and the bridging mechanism natively offered by MQTT. This allows us not to require changes in the standard MQTT infrastructure. To validate the performance of our solution, we performed a deep experimental campaign by deploying the bridge brokers on cloud platforms in various countries of the world. The experimental validation shows that, the price of latency we have to pay because of the trade-off with anonymity is quite reasonable. Moreover, no significant impact on goodput occurs in the case of good network conditions.

Blockchain-Based Decentralized and Lightweight Anonymous Authentication for Federated Learning

Federated learning (FL) is a promising technology for achieving privacy-preserving edge intelligence and has attracted extensive attention from industry and academia. However, in the FL training process, the server directly aggregates local models from mobile devices, which poses serious privacy and security threats. The identity authentication mechanism can provide FL with local model integrity and source authentication. However, the existing schemes are centralized, and most of them are computationally expensive, resulting in limited performance. To address these issues, this paper proposes a decentralized and lightweight anonymous FL identity authentication scheme, namely DAFL. In our scheme, we first design a decentralized and simplified storage FL authentication framework by combining the directed acyclic graph (DAG) blockchain and accumulator. Then, we propose a lightweight digital signature algorithm that supports batch verification for authentication. Finally, nodes interact through pseudonyms to achieve anonymous communication, and the trusted authority (TA) can track and recover the real identities of nodes when malicious behavior occurs. We theoretically prove the security of the proposed DAFL. The extensive experiments demonstrate that DAFL achieves lower authentication overhead and better convergence performance compared to existing authentication schemes and vanilla FL systems.

Anonymity in decentralized apps: Study of implications for cybercrime investigations

In the digital age, cybercrime facilitated by anonymous communication apps raises significant concerns. Criminals exploit the anonymity provided by these apps, creating challenges for law enforcement and cybersecurity professionals when investigating and combating cybercrime. The complexity of decentralized applications (DApps) without centralized servers further complicates evidence certification. Although anonymity features to protect privacy, they impede the establishment of connections between digital accounts and real-world identities. In centralized server environments, data access for investigations is relatively straightforward. However, this study reveals that DApps present challenges due to decentralized control, anonymity, encrypted communication, and jurisdictional issues. DApps designed for anonymous communication allow users to interact without revealing their identities, making it challenging to trace criminals. While cybercrime investigations in centralized environments involve systematic evidence collection, correlation, analyzing communication patterns, collaboration with agencies, tracking IP addresses, legal authorization, and forensic analysis of digital devices, DApps-based investigations require vital intelligence gathering through open-source techniques (OSINT). This includes retrieving digital footprints, analyzing social media profiles, and tracing ownership information. Moreover, investigators may exploit human vulnerabilities, engage in deceptive communication, or use social engineering techniques to gather information while carefully considering the balance between user privacy and investigative requirements. In this study, we explore the many facets of anonymity in DApps and what challenges they impose for the investigation of cybercrime. The anonymity of users and their transactions in the context of new blockchain and decentralized technology presents difficulties for law enforcement. In the end, our research helps shed light on the complex relationship between anonymity in decentralized systems and the need for fairness online.

Security architecture for authorized anonymous communication in 5G MEC

The use of services provided in modern mobile networks using edge servers (5G MEC) requires extended security solutions. One of them is an access control system adapted to the different needs and requirements of end users and service providers. Another, equally important, is the protection against the takeover of the service during its lifetime, which leads to the inevitable leakage of information and economic losses. In this paper, we present a new access control architecture for the 5G MEC network, which meets both security requirements in a flexible and lightweight way. First, we specify the architecture scheme and its central element, MEC Enabler, which manages access control security policies and generates access credentials (tokens). Next, we describe the method of securing data packets in the communication process related to the service provided by the MEC server, preventing the session from being intercepted by an unauthorized user. The countermeasure is designed to protect data identifying packets (node addresses, port numbers) and prevent identification of packets’ connection with the protected service. Experiments on the operation of the service with the implemented protection mechanism made in a testbed show that the proposed security solution has a negligible effect on the MEC-hosted application delays.

B-Tor: Anonymous communication system based on consortium blockchain

B-Tor: Anonymous communication system based on consortium blockchain

Examining the Hydra: Simultaneously Shared Links in Tor and the Effects on its Performance

Tor is a popular privacy-enhancing technology that allows anonymous communication using onion routing. However, such technologies are only helpful if used; therefore, performance is an important aspect. One of the main performance bottlenecks of Tor is the cross-circuit interference (CCI) problem. Tor multiplexes multiple circuits over a single Transport Layer Security (TLS) 1.2 connection if they share a path segment (link). Therefore, they have the same congestion window, which can yield unfair bandwidth allocation. However, there has been little work in understanding this problem in more depth. This paper investigates the number of simultaneously shared links in the current Tor network, which are the root cause of CCI. We developed a novel shared links simulator called SALSA to investigate this problem. Our results show that 3.7 % of active links are shared, and the involving Onion Routers (ORs) have the most common bandwidth capabilities. Additionally, we show that the internal circuits and exit policy influence the CCI problem. Furthermore, we model the number of shared links when the demand grows further and show that the number of shared links can go up to 16 %. Finally, we run Shadow simulations with a 25 % down-scaled Tor network and show that a network without shared links is faster.

Research on Blockchain Anonymous Communication Based on Key Derivation

Abstract With the continuous development of the Internet and communication technologies, network communication provides convenience but also brings security problems such as exposure of users' personal privacy information and theft, private tampering, and forgery of false information. Modern cryptography technology is an important safeguard against message eavesdropping and tampering, while the rapidly developing anonymous communication technology in this century makes it difficult for attackers to infer user's personal information and communication relationships. In response to the potential threats of traditional centralized systems such as central nodes being vulnerable to attacks and data storage being tampered with, this paper proposes a blockchain anonymous communication algorithm KDAC based on key derivation, which takes advantage of the decentralization, data immutability, consensus mechanism and anonymity of blockchain and combines the ECC cryptographic derivation algorithm and anonymous communication technology to realize the key-at-a-time, one-address-at-a-time The key derivation scheme ensures the message integrity and tamper-evident while effectively hiding the identity information of both communication parties. In addition, this paper also optimizes the blockchain anonymous communication system with key derivation. Users only need the initial key of blockchain nodes to join the network for communication, and the information transmission is difficult to trace based on the blockchain network, which can effectively guarantee communication security and anonymity. The experimental results show that the efficiency of the derived key algorithm is roughly in the same order of magnitude as that of the 256-bit AES symmetric encryption algorithm, which can play a better role in practical applications. On the other hand, the derived key generated based on the algorithm has complete randomness in association verification, and it is impossible to reverse the initial parameters, which can well guarantee the anonymity of user identity.