A Ring Based Onion Circuit for Hidden Services

The development of digital media, the increasing use of social networks, the easier access to modern technological devices, is perturbing thousands of people in their public and private lives. People love posting their personal news without consider the risks involved. Privacy has never been more important. Privacy enhancing technologies research have attracted considerable international attention after the recent news against users personal data protection in social media websites like Facebook. It has been demonstrated that even when using an anonymous communication system, it is possible to reveal user’s identities through intersection attacks or traffic analysis attacks. Combining a traffic analysis attack with Analysis Social Networks (SNA) techniques, an adversary can be able to obtain important data from the whole network, topological network structure, subset of social data, revealing communities and its interactions. The aim of this work is to demonstrate how intersection attacks can disclose structural properties and significant details from an anonymous social network composed of a university community.

Traffic analysis attacks can counteract end-to-end encryption and use leaked communication metadata to reveal information about communicating parties. With an ever-increasing amount of traffic by an ever-increasing number of networked devices, communication privacy is undermined. Therefore, Anonymous Communication Systems (ACSs) are proposed to hide the relationship between transmitted messages and their senders and receivers, providing privacy properties known as anonymity, unlinkability, and unobservability. This article aims to review research in the ACSs field, focusing on Dining Cryptographers Networks (DCNs). The DCN-based methods are information-theoretically secure and thus provide unconditional unobservability guarantees. Their adoption for anonymous communications was initially hindered because their computational and communication overhead was deemed significant at that time, and scalability problems occurred. However, more recent contributions, such as the possibility to transmit messages of arbitrary length, efficient disruption handling and overhead improvements, have made the integration of modern DCN-based methods more realistic. In addition, the literature does not follow a common definition for privacy properties, making it hard to compare the approaches’ gains. Therefore, this survey contributes to introducing a harmonized terminology for ACS privacy properties, then presents an overview of the underlying principles of ACSs, in particular, DCN-based methods, and finally, investigates their alignment with the new harmonized privacy terminologies. Previous surveys did not cover the most recent research advances in the ACS area or focus on DCN-based methods. Our comprehensive investigation closes this gap by providing visual maps to highlight privacy properties and discussing the most promising ideas for making DCNs applicable in resource-constrained environments.

In this paper, we study the problem of traffic analysis attacks in wireless body area sensor networks. When these networks are used in health-care for remote patient monitoring, traffic analysis can reveal the type of medical sensors mounted on the patient, and this information may be used to infer the patient's health problems. We show that simple signal processing methods can be used effectively for performing traffic analysis attacks and identifying the sensor types in a rather weak adversary model. We then investigate possible traffic obfuscation mechanisms aiming at hiding the regular patterns in the observable wireless traffic. Among the investigated countermeasures, traffic shaping, a mechanism that introduces carefully chosen delays for message transmissions, appears to be the best choice, as it achieves close to optimal protection and incurs no overhead.

The Tor anonymity network is one of the most popular and widely used tools to protect the privacy of online users. Tor provides defenses against multiple adversarial activities aiming to identify or trace the users. Traffic analysis is a very strong tool that can be used for internet surveillance. Traffic analysis attacks against Tor's anonymity network has been known as an open question in research. Moreover, the low-latency feature Tor tries to provide to its users imposes limitations in defending against traffic analysis attacks. In our study, we examine traffic analysis attacks from the perspective of the adopted adversary model and how much it fits within Tor's threat model. The purpose of this study is to evaluate how practical these attacks are on real-time Tor network.

We investigate the feasibility of mounting a de-anonymization attack against Tor and similar low-latency anonymous communication systems by using NetFlow records. Previous research has shown that adversaries with the ability to eavesdrop in real time at a few internet exchange points can effectively monitor a significant part of the network paths from Tor nodes to destination servers. However, the capacity of current networks makes packet-level monitoring at such a scale quite challenging. We hypothesize that adversaries could use less accurate but readily available monitoring facilities, such as Cisco’s NetFlow, to mount large-scale traffic analysis attacks. In this paper, we assess the feasibility and effectiveness of traffic analysis attacks against Tor using NetFlow data. We present an active traffic analysis technique based on perturbing the characteristics of user traffic at the server side, and observing a similar perturbation at the client side through statistical correlation. We evaluate the accuracy of our method using both in-lab testing and data gathered from a public Tor relay serving hundreds of users. Our method revealed the actual sources of anonymous traffic with 100% accuracy for the in-lab tests, and achieved an overall accuracy of 81.6% for the real-world experiments with a false positive rate of 5.5%.

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.

We introduce cMix, a new approach to anonymous communications. Through a precomputation, the core cMix protocol eliminates all expensive real-time public-key operations—at the senders, recipients and mixnodes—thereby decreasing real-time cryptographic latency and lowering computational costs for clients. The core real-time phase performs only a few fast modular multiplications. In these times of surveillance and extensive profiling there is a great need for an anonymous communication system that resists global attackers. One widely recognized solution to the challenge of traffic analysis is a mixnet, which anonymizes a batch of messages by sending the batch through a fixed cascade of mixnodes. Mixnets can offer excellent privacy guarantees, including unlinkability of sender and receiver, and resistance to many traffic-analysis attacks that undermine many other approaches including onion routing. Existing mixnet designs, however, suffer from high latency in part because of the need for real-time public-key operations. Precomputation greatly improves the real-time performance of cMix, while its fixed cascade of mixnodes yields the strong anonymity guarantees of mixnets. cMix is unique in not requiring any real-time public-key operations by users. Consequently, cMix is the first mixing suitable for low latency chat for light-weight devices. Our presentation includes a specification of cMix, security arguments, anonymity analysis, and a performance comparison with selected other approaches. We also give benchmarks from our prototype.

Across a diverse landscape of anonymity designs, the dominant paradigms—onion routing (e.g., Tor) and mix networks (e.g., Loopix)—carry intrinsic constraints: long-lived circuits invite traffic correlation, and mixnets often rely on a network-wide state, making it hard to reconcile anonymity and scalability. This paper presents Draughts, a fully decentralized system in which each packet follows an independent and dynamically determined transmission path. Built upon Jump routing, Draughts introduces three key innovations: (i) replacing global state O(N) with local two-hop neighborhood knowledge O(k2); (ii) supporting anonymous replies to enable real-time bidirectional communication; and (iii) proposing a path-length control mechanism that balances anonymity and transmission efficiency. Evaluation results show that Draughts achieves strong sender anonymity, resists predecessor and traffic analysis attacks, and reduces receiver buffer maintenance overhead, achieving a favorable trade-off between anonymity and performance.

In many regions of the world, nation-states enforce Internet censorship policies that prevent unrestricted access to information and services by their citizens. Over the years, many censorship circumvention tools have been proposed which, however, require either the deployment of a dedicated infrastructure within trusted ISPs, or are vulnerable to state-of-the-art traffic analysis techniques. To fill this gap, we propose to build a practical censorship-circumvention service that exhibits strong resistance against traffic analysis attacks. By relying on a recent proposal for creating covert channels through WebRTC streams, we discuss the design of a distributed system named Censorship-Resistant Overlay Network (CRON). CRON aims at offering to the users located in censored regions a set of services that allow them to locate proxies positioned in the free Internet region, and set up secure covert tunnels for accessing arbitrary sites on the Internet. We present the key challenges and explore the solutions in making CRON robust against state-level attacks.

We present a novel web page fingerprinting attack that is able to defeat several recently proposed defenses against traffic analysis attacks, including the application-level defenses HTTPOS and randomized pipelining over Tor. Regardless of the defense scheme, our attack was able to guess which of 100 web pages a victim was visiting at least 50% of the time and, with some defenses, over 90% of the time. Our attack is based on a simple model of network behavior and out-performs previously proposed ad hoc attacks. We then build a web site fingerprinting attack that is able to identify whether a victim is visiting a particular web site with over 90% accuracy in our experiments.Our results strongly suggest that ad hoc defenses against traffic analysis are not likely to succeed. Consequently, we describe a defense scheme that provides provable security properties, albeit with potentially higher overheads.

Virtualization is the cornerstone of the developing third party compute industry, allowing cloud providers to instantiate multiple virtual machines (VMs) on a single set of physical resources. Customers utilize cloud resources alongside unknown and untrusted parties, creating the co-resident threat -- unless perfect isolation is provided by the virtual hypervisor, there exists the possibility for unauthorized access to sensitive customer information through the exploitation of covert side channels.

Despite increasing popularity of anonymous communications, current anonymity networks are still vulnerable to traffic analysis attacks. We propose Homomorphic EnCrypTion enabled Onion Routing (HECTor) to defeat existing traffic analysis attacks. Instead of mixing traffic at the packet level as current anonymity networks, HECTor mixes traffic at the bit level with network coding techniques. In HECTor, homomorphic encryption enables onion-like layered encryption which has been proven successful in existing anonymity networks. We theoretically analyze the performance of HECTor. Our extensive experiments on HECTor show that HECTor can effectively mitigate existing traffic analysis attacks with high throughput.

Popular anonymity mechanisms such as Tor provide low communication latency but are vulnerable to traffic analysis attacks that can de-anonymize users. Moreover, known traffic-analysis-resistant techniques such as Dissent are impractical for use in latency-sensitive settings such as wireless networks. In this paper, we propose PriFi, a low-latency protocol for anonymous communication in local area networks that is provably secure against traffic analysis attacks. This allows members of an organization to access the Internet anonymously while they are on-site, via privacy-preserving WiFi networking, or off-site, via privacy-preserving virtual private networking (VPN). PriFi reduces communication latency using a client/relay/server architecture in which a set of servers computes cryptographic material in parallel with the clients to minimize unnecessary communication latency. We also propose a technique for protecting against equivocation attacks, with which a malicious relay might de-anonymize clients. This is achieved without adding extra latency by encrypting client messages based on the history of all messages they have received so far. As a result, any equivocation attempt makes the communication unintelligible, preserving clients' anonymity while holding the servers accountable.

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.

We present BitBlender, an efficient protocol that provides an anonymity layer for BitTorrent traffic. BitBlender works by creating an ad-hoc multi-hop network consisting of special called peers that proxy requests and replies on behalf of other peers. To understand the effect of introducing relay into the BitTorrent system architecture, we provide an analysis of the expected path lengths as the ratio of relay to normal varies. A prototype is implemented and experiments are conducted on Planetlab to quantify the performance overhead associated with the protocol. We also propose protocol extensions to add confidentiality and access control mechanisms, countermeasures against traffic analysis attacks, and selective caching policies that simultaneously increase both anonymity and performance. We finally discuss the potential legal obstacles to deploying an anonymous file sharing protocol. This work is among the first to propose a privacy enhancing system that is designed specifically for a particular class of peer-to-peer traffic.