Anonymous Communication Networks Research Articles

Threading Statistical Disclosure Attack with EM: An Algorithm for Revealing Identity in Anonymous Communication Networks

Messages sent across multiple platforms can be correlated to infer users’ attitudes, behaviors, preferences, lifestyles, and more. Therefore, research on anonymous communication systems has intensified in the last few years. This research introduces a new algorithm, Threading Statistical Disclosure Attack with EM (TSDA-EM), that employs real-world data to reveal communication’s behavior in an anonymous social network. In this study, we utilize a network constructed from email exchanges to represent interactions between individuals within an institution. The proposed algorithm is capable of identifying communication patterns within a mixed network, even under the observation of a global passive attacker. By employing multi-threading, this implementation reduced the average execution time by a factor of five when using a dataset with a large number of participants. Additionally, it has markedly improved classification accuracy, detecting more than 79% of users’ communications in large networks and more than 95% in small ones.

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%.

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.

Exploring Dark Web Crawlers: A Systematic Literature Review of Dark Web Crawlers and Their Implementation

Strong encryption algorithms and reliable anonymity routing have made cybercrime investigation more challenging. Hence, one option for law enforcement agencies (LEAs) is to search through unencrypted content on the Internet or anonymous communication networks (ACNs). The capability of automatically harvesting web content from web servers enables LEAs to collect and preserve data prone to serve as potential leads, clues, or evidence in an investigation. Although scientific studies have explored the field of web crawling soon after the inception of the web, few research studies have thoroughly scrutinised web crawling on the "dark web" or via ACNs such as I2P, IPFS, Freenet, and Tor. The current paper presents a systematic literature review (SLR) that examines the prevalence and characteristics of dark web crawlers. From a selection of 58 peer-reviewed articles mentioning crawling and the dark web, 34 remained after excluding irrelevant articles. The literature review showed that most dark web crawlers were programmed in Python, using either Selenium or Scrapy as the web scraping library. The knowledge gathered from the systematic literature review was used to develop a Tor-based web crawling model into an already existing software toolset customised for ACN-based investigations. Finally, the performance of the model was examined through a set of experiments. The results indicate that the developed crawler was successful in scraping web content from both clear and dark web pages, and scraping dark marketplaces on the Tor network. The scientific contribution of this paper entails novel knowledge concerning ACN-based web crawlers. Furthermore, it presents a model for crawling and scraping clear and dark websites for the purpose of digital investigations. The conclusions include practical implications of dark web content retrieval and archival, such as investigation clues and evidence, and the related future research topics.

Discerning the traffic in anonymous communication networks using machine learning: concepts, techniques and future trends

Discerning the traffic in anonymous communication networks using machine learning: concepts, techniques and future trends

Discerning the traffic in Anonymous Communication Networks using Machine Learning: Concepts, Techniques and Future Trends

Discerning the traffic in Anonymous Communication Networks using Machine Learning: Concepts, Techniques and Future Trends

A Covert-Aware Anonymous Communication Network for Social Communication

To effectively protect the communication content and communication behavior of social networks, anonymous communication technologies are widely used. However, the anonymous communication networks represented by Tor and I2P lack the covertness of the control plane design, which leads to important user behavioral characteristics in the process of accessing anonymous communication networks. Therefore, network monitors can analyze users' communication behavior by tracking these characteristics. In this paper, the concept of covert measurement is proposed. On this basis, a software-defined anonymous communication network architecture is presented, which also considers the covertness of the anonymous communication network control plane and the data plane. According to the theoretical analysis and experimental results, the anonymous communication network architecture proposed in this paper has better anonymity and usability than traditional anonymous communication networks, such as Tor.

A protocol for anonymous short communications in social networks and its application to proximity-based services

Several innovative applications could be advantageously placed within social networks, to be effective, attractive, and pervasive. Examples of application domains that could benefit from social networks are e-democracy, e-participation, online surveys, crowdsourcing, and proximity-based services. In all the above cases, users’ anonymity could represent a considerable added value or could be even necessary to develop the service. We observe that all the above domains are characterized by the fact that only a few asynchronous messages should be exchanged. Therefore, we do not need the full communication power of anonymous communication networks, in which low-latency and connection-oriented communication should be supported. On the other hand, unlike communication networks, the threat model we have to consider assumes the presence of an adversary (represented by an honest-but-curious social network provider) able to monitor the entire flow of the exchanged messages. In this paper, we propose an anonymous communication protocol for short communications in social networks, based on a collaborative approach. The proposed solution hides from the social network provider not only the content of the messages but also the communication itself, which, per se, can result in considerable privacy leakage (think of the case of proximity testing performed between two users). This enables the implementation, within the social network, of the above-mentioned applications. To give a concrete proof of this statement, we develop a privacy-preserving proximity-based solution which provides both symmetric and asymmetric proximity testing entirely within social networks.

A Traffic Splitting Algorithm for Load Balancing in Tor.

As the most popular anonymous communication system, Tor provides anonymous protection for users by sending their messages through a series of relays. Due to the use of the bandwidth-weighted path selection algorithm, many more users choose routers with high bandwidth as relays. This will cause the utilization of high bandwidth routers to be much higher than that of low bandwidth routers, which will bring congestion risk. The Quality of Service (QoS) is difficult to guarantee for users who need delay-sensitive services such as web browsing and instant messaging. To reduce the average load of routers and improve the network throughput, we propose a circuit construction method with multiple parallel middle relays and conduct a dynamic load allocation method. The experiment demonstrates that our proposed method can provide better load balancing. Compared with other multipath anonymous communication networks, our proposed method can provide better anonymity.

A Comparative Study on Anonymizing Networks: TOR, I2P, and Riffle Networks Comparison

Background and Objectives: Among miscellaneous networks, onion-based routing network technologies such as The Onion-based Routing (ToR), Invisible Internet Project (I2P), and Riffle networks are used to communicate anonymously by different worldwide users for security, privacy, and safety requirements. Sometimes, these types of networks sacrifice anonymity for the sake of efficient communication or vice-versa. This paper surveys aforementioned networks for investigating their potential and challenges.Methods: Onion-routing networks encapsulate messages in several layers of encryption similar to layers of an onion. The anonymous communication networks are involved dining cryptographers (DC) problem so-called DC-nets, which need sending anonymous message with unconditional sender and untraceable receipt. So, DC-nets must be resistant against traffic analysis attacks although they will attenuate the network bandwidth. In this line, ToR is a free software that provides anonymous communication, I2P networks are based on hidden internet service project which uses tunnelling for anonymous communications, and Riffle networks include a small set of camouflaging servers that provide anonymity for authorized users. This paper presents a comparative study on anonymizing ToR, I2P, and Riffle networks in terms of associated prominent parameters in this vein.Results: The comparison is based on similarities, differences, and challenges in network behaviors. This comparison is beneficial for further researches and future improvements.Conclusion: The review of the current paper reveals that the Riffle networks are more resilient and have great confidentiality and integrity against other onion-based routing networks.

A Systems Approach Toward Addressing Anonymous Abuses: Technical and Policy Considerations

Can we prevent the abuses of anonymous communication networks without affecting their ability to enhance privacy and evade censorship? We evaluate approaches for balancing the need for anonymity with the desire to mitigate anonymous abuses.

Balancing anonymity and resilience in anonymous communication networks

Anonymous communication networks (ACNs) are intended to protect the metadata privacy during the communication. As typical ACNs, onion mix-nets adopt source routing where the source defines a static path and wraps the message with the public keys of on-path nodes so that the message could be delivered to the destination. However, onion mix-nets lack resilience when the static on-path mixes fail, which could result in message loss, communication failure and even de-anonymization attacks. Therefore, it is desirable to achieve routing resilience in onion mix-nets for persistent routing capability even against node failure. The state-of-the-art solutions mainly adopt mix groups and thus need to share secrets among all the group members, which may cause single point of failure and render massive loss of anonymity.To address the above problem, in this work we design a hybrid routing approach, which essentially embeds the onion mix-net with hop-by-hop routing to achieve desirable routing resilience. Furthermore, we extend our scheme with a threshold setting, and propose T-hybrid routing to mitigate the anonymity loss when group mixes are compromised. Besides, we propose the active defense mechanism to defend replay attacks in the scenario of mix groups. As for experimental evaluations, we conduct a quantitative analysis of the resilience and anonymity for various schemes, and demonstrate that T-hybrid routing can achieve a good balance between resilience and anonymity. In addition, we manage to realize the full T-hybrid routing prototype and test its performance in the cloud hosting environment. The experimental results show that compared with typical onion mix-nets, our T-hybrid routing mechanism only increases about 20%-25% regarding the end-to-end delay, and thus is still practical while with better resilience.

PriFi: Low-Latency Anonymity for Organizational Networks

AbstractOrganizational networks are vulnerable to trafficanalysis attacks that enable adversaries to infer sensitive information fromnetwork traffic—even if encryption is used. Typical anonymous communication networks are tailored to the Internet and are poorly suited for organizational networks.We present PriFi, an anonymous communication protocol for LANs, which protects users against eavesdroppers and provides high-performance traffic-analysis resistance. PriFi builds onDining Cryptographers networks (DC-nets), but reduces the high communication latency of prior designs via a new client/relay/server architecture, in which a client’s packets remain on their usual network path without additional hops, and in which a set of remote servers assist the anonymization process without adding latency. PriFi also solves the challenge of equivocation attacks, which are not addressed by related work, by encrypting traffic based on communication history. Our evaluation shows that PriFi introduces modest latency overhead (≈ 100ms for 100 clients) and is compatible with delay-sensitive applications such as Voice-over-IP.

Comprehensive Anonymity Trilemma: User Coordination is not enough

Abstract For anonymous communication networks (ACNs), Das et al. recently confirmed a long-suspected trilemma result that ACNs cannot achieve strong anonymity, low latency overhead and low bandwidth overhead at the same time. Our paper emanates from the careful observation that their analysis does not include a relevant class of ACNs with what we call user coordination where users proactively work together towards improving their anonymity. We show that such protocols can achieve better anonymity than predicted by the above trilemma result. As the main contribution, we present a stronger impossibility result that includes all ACNs we are aware of. Along with our formal analysis, we provide intuitive interpretations and lessons learned. Finally, we demonstrate qualitatively stricter requirements for the Anytrust assumption (all but one protocol party is compromised) prevalent across ACNs.

On Privacy Notions in Anonymous Communication

Abstract Many anonymous communication networks (ACNs) with different privacy goals have been developed. Still, there are no accepted formal definitions of privacy goals, and ACNs often define their goals ad hoc. However, the formal definition of privacy goals benefits the understanding and comparison of different flavors of privacy and, as a result, the improvement of ACNs. In this paper, we work towards defining and comparing privacy goals by formalizing them as privacy notions and identifying their building blocks. For any pair of notions we prove whether one is strictly stronger, and, if so, which. Hence, we are able to present a complete hierarchy. Using this rigorous comparison between notions, we revise inconsistencies between the existing works and improve the understanding of privacy goals.

A probabilistic model for anonymity analysis of anonymous communication networks

An anonymous communication network (ACN) is supposed to provide its users with anonymity attributes. As a practical matter, we need to have a means to predict the level of the anonymity provided by ACN. In this paper, we propose a probabilistic model for the security analysis of ACNs, thereby quantifying their loss of anonymity. To be precise, we have tried to obtain the probability distribution of potential senders of a message sent from an unknown source to a specific destination. With the probability distribution in hand, it is possible to define and derive some anonymity metrics. The evaluated metrics help us to gain an understanding of how much such a network may be vulnerable to attacks aiming at revealing the identity of senders of messages. Consequently, new rerouting policies and strategies can be utilized to increase the anonymity level of the network. The quantitative analysis is performed from a general perspective and the applicability of the model is not limited to a specific network. The evaluation process of the metrics using the proposed model is clarified by an illustrative example.

An efficient protocol for power consumption in wireless enterprise ad hoc virtual community network with Triso framework

Today's global technology has various security treats which made the identity protection essential among user's for establishing communication over internet. Generally these identity protecting network were well known as anonymous communication networks. Mix networks are multistage systems which provide efficient mechanisms for anonymous communication over internet. According to which these networks have various traffic analysis attacks which need to compromise the identities of users. The major objective of this paper is to present a diversity mix techniques against traffic analysis attacks, disclosure attack and spam attack. In this work, we propose traffic re-allocation which involves in varying the size as well as number of messages in the network. By means of enabling this bursting and blending of messages among the network nodes the attacker get confused with the varied message count and sizes. The performance of our proposed work is examined against the three attacks in order to check its security and anonymity. The obtained result proves the effectiveness of our proposed techniques.

An efficient protocol for power consumption in wireless enterprise ad hoc virtual community network with Triso framework

Today's global technology has various security treats which made the identity protection essential among user's for establishing communication over internet. Generally these identity protecting network were well known as anonymous communication networks. Mix networks are multistage systems which provide efficient mechanisms for anonymous communication over internet. According to which these networks have various traffic analysis attacks which need to compromise the identities of users. The major objective of this paper is to present a diversity mix techniques against traffic analysis attacks, disclosure attack and spam attack. In this work, we propose traffic re-allocation which involves in varying the size as well as number of messages in the network. By means of enabling this bursting and blending of messages among the network nodes the attacker get confused with the varied message count and sizes. The performance of our proposed work is examined against the three attacks in order to check its security and anonymity. The obtained result proves the effectiveness of our proposed techniques.

De-anonymizing and countermeasures in anonymous communication networks

To fulfill global requirements for network security and privacy, anonymous communication systems have been extensively investigated and deployed over the world to provide anonymous communication services for users. Nonetheless, diverse de-anonymizing techniques have been proposed to compromise anonymity and impose a severe threat to anonymous communication systems. In this article, we classify the existing de-anonymizing techniques and provide an overview of these techniques. In addition, corresponding countermeasures are studied to mitigate the risks posed by these de-anonymizing techniques.

A Least Squares Approach to the Static Traffic Analysis of High-Latency Anonymous Communication Systems

Mixes, relaying routers that hide the relation between incoming and outgoing messages, are the main building block of high-latency anonymous communication networks. A number of so-called disclosure attacks have been proposed to effectively de-anonymize traffic sent through these channels. Yet, the dependence of their success on the system parameters is not well-understood. We propose the Least Squares Disclosure Attack (LSDA), in which user profiles are estimated by solving a least squares problem. We show that LSDA is not only suitable for the analysis of threshold mixes, but can be easily extended to attack pool mixes. Furthermore, contrary to previous heuristic-based attacks, our approach allows us to analytically derive expressions that characterize the profiling error of LSDA with respect to the system parameters. We empirically demonstrate that LSDA recovers users' profiles with greater accuracy than its statistical predecessors and verify that our analysis closely predicts actual performance.