Biblio

The browsing behavior of a user allows to infer personal details, such as health status, political interests, sexual orientation, etc. In order to protect this sensitive information and to cope with possible privacy threats, defense mechanisms like SSH tunnels and anonymity networks (e.g., Tor) have been established. A known shortcoming of these defenses is that website fingerprinting attacks allow to infer a user's browsing behavior based on traffic analysis techniques. However, website fingerprinting typically assumes access to the client's network or to a router near the client, which restricts the applicability of these attacks. In this work, we show that this rather strong assumption is not required for website fingerprinting attacks. Our client-side attack overcomes several limitations and assumptions of network-based fingerprinting attacks, e.g., network conditions and traffic noise, disabled browser caches, expensive training phases, etc. Thereby, we eliminate assumptions used for academic purposes and present a practical attack that can be implemented easily and deployed on a large scale. Eventually, we show that an unprivileged application can infer the browsing behavior by exploiting the unprotected access to the Android data-usage statistics. More specifically, we are able to infer 97% of 2,500 page visits out of a set of 500 monitored pages correctly. Even if the traffic is routed through Tor by using the Orbot proxy in combination with the Orweb browser, we can infer 95% of 500 page visits out of a set of 100 monitored pages correctly. Thus, the READ\_HISTORY\_BOOKMARKS permission, which is supposed to protect the browsing behavior, does not provide protection.

The ability to identify mobile apps in network traffic has significant implications in many domains, including traffic management, malware detection, and maintaining user privacy. App identification methods in the literature typically use deep packet inspection (DPI) and analyze HTTP headers to extract app fingerprints. However, these methods cannot be used if HTTP traffic is encrypted. We investigate whether Android apps can be identified from their launch-time network traffic using only TCP/IP headers. We first capture network traffic of 86,109 app launches by repeatedly running 1,595 apps on 4 distinct Android devices. We then use supervised learning methods used previously in the web page identification literature, to identify the apps that generated the traffic. We find that: (i) popular Android apps can be identified with 88% accuracy, by using the packet sizes of the first 64 packets they generate, when the learning methods are trained and tested on the data collected from same device; (ii) when the data from an unseen device (but similar operating system/vendor) is used for testing, the apps can be identified with 67% accuracy; (iii) the app identification accuracy does not drop significantly even if the training data are stale by several days, and (iv) the accuracy does drop quite significantly if the operating system/vendor is very different. We discuss the implications of our findings as well as open issues.

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.

The recent growth of anonymous social network services – such as 4chan, Whisper, and Yik Yak – has brought online anonymity into the spotlight. For these services to function properly, the integrity of user anonymity must be preserved. If an attacker can determine the physical location from where an anonymous message was sent, then the attacker can potentially use side information (for example, knowledge of who lives at the location) to de-anonymize the sender of the message. In this paper, we investigate whether the popular anonymous social media application Yik Yak is susceptible to localization attacks, thereby putting user anonymity at risk. The problem is challenging because Yik Yak application does not provide information about distances between user and message origins or any other message location information. We provide a comprehensive data collection and supervised machine learning methodology that does not require any reverse engineering of the Yik Yak protocol, is fully automated, and can be remotely run from anywhere. We show that we can accurately predict the locations of messages up to a small average error of 106 meters. We also devise an experiment where each message emanates from one of nine dorm colleges on the University of California Santa Cruz campus. We are able to determine the correct dorm college that generated each message 100\textbackslash% of the time.

For a multicast group of n receivers, existing techniques either achieve high throughput at the cost of prohibitively large (e.g., O(n)) feedback overhead, or achieve low feedback overhead but without either optimal or near-optimal throughput guarantees. Simultaneously achieving good throughput guarantees and low feedback overhead has been an open problem and could be the key reason why wireless multicast has not been successfully deployed in practice. In this paper, we develop a novel anonymous-query based rate control, which approaches the optimal throughput with a constant feedback overhead independent of the number of receivers. In addition to our theoretical results, through implementation on a software-defined ratio platform, we show that the anonymous-query based algorithm achieves low-overhead and robustness in practice.

Contactless communications have become omnipresent in our daily lives, from simple access cards to electronic passports. Such systems are particularly vulnerable to relay attacks, in which an adversary relays the messages from a prover to a verifier. Distance-bounding protocols were introduced to counter such attacks. Lately, there has been a very active research trend on improving the security of these protocols, but also on ensuring strong privacy properties with respect to active adversaries and malicious verifiers. In particular, a difficult threat to address is the terrorist fraud, in which a far-away prover cooperates with a nearby accomplice to fool a verifier. The usual defence against this attack is to make it impossible for the accomplice to succeed unless the prover provides him with enough information to recover his secret key and impersonate him later on. However, the mere existence of a long-term secret key is problematic with respect to privacy. In this paper, we propose a novel approach in which the prover does not leak his secret key but a reusable session key along with a group signature on it. This allows the adversary to impersonate him even without knowing his signature key. Based on this approach, we give the first distance-bounding protocol, called SPADE, integrating anonymity, revocability and provable resistance to standard threat models.

The Polish Power System is becoming increasingly more dependent on Information and Communication Technologies which results in its exposure to cyberattacks, including the evolved and highly sophisticated threats such as Advanced Persistent Threats or Distributed Denial of Service attacks. The most exposed components are SCADA systems in substations and Distributed Control Systems in power plants. When addressing this situation the usual cyber security technologies are prerequisite, but not sufficient. With the rapidly evolving cyber threat landscape the use of partnerships and information sharing has become critical. However due to several anonymity concerns the relevant stakeholders may become reluctant to exchange sensitive information about security incidents. In the paper a multi-agent architecture is presented for the Polish Power System which addresses the anonymity concerns.

Anonymous messaging applications have recently gained popularity as a means for sharing opinions without fear of judgment or repercussion. These messages propagate anonymously over a network, typically de ned by social connections or physical proximity. However, recent advances in rumor source detection show that the source of such an anonymous message can be inferred by certain statistical inference attacks. Adaptive di usion was recently proposed as a solution that achieves optimal source obfuscation over regular trees. However, in real social networks, the degrees difer from node to node, and adaptive di usion can be signicantly sub-optimal. This gap increases as the degrees become more irregular.

In order to quantify this gap, we model the underlying network as coming from standard branching processes with i.i.d. degree distributions. Building upon the analysis techniques from branching processes, we give an analytical characterization of the dependence of the probability of detection achieved by adaptive di usion on the degree distribution. Further, this analysis provides a key insight: passing a rumor to a friend who has many friends makes the source more ambiguous. This leads to a new family of protocols that we call Preferential Attachment Adaptive Di usion (PAAD). When messages are propagated according to PAAD, we give both the MAP estimator for nding the source and also an analysis of the probability of detection achieved by this adversary. The analytical results are not directly comparable, since the adversary's observed information has a di erent distribution under adaptive di usion than under PAAD. Instead, we present results from numerical experiments that suggest that PAAD achieves a lower probability of detection, at the cost of increased communication for coordination.

Privacy preservation is very essential in various real life applications such as medical science and financial analysis. This paper focuses on implementation of an asymmetric secure multi-party computation protocol using anonymization and public-key encryption where all parties have access to trusted third party (TTP) who (1) doesn't add any contribution to computation (2) doesn't know who is the owner of the input received (3) has large number of resources (4) decryption key is known to trusted third party (TTP) to get the actual input for computation of final result. In this environment, concern is to design a protocol which deploys TTP for computation. It is proposed that the protocol is very proficient (in terms of secure computation and individual privacy) for the parties than the other available protocols. The solution incorporates protocol using asymmetric encryption scheme where any party can encrypt a message with the public key but decryption can be done by only the possessor of the decryption key (private key). As the protocol works on asymmetric encryption and packetization it ensures following: (1) Confidentiality (Anonymity) (2) Security (3) Privacy (Data).

In cloud computing environments, the user authentication scheme is an important security tool because it provides the authentication, authorization, and accounting for cloud users. Therefore, many user authentication schemes for cloud computing have been proposed in recent years. However, we find that most of the previous authentication schemes have some security problems. Besides, it cannot be implemented in cloud computing. To solve the above problems, we propose a new ID-based user authentication scheme for cloud computing in this paper. Compared with the related works, the proposed scheme has higher security levels and lower computation costs. In addition, it can be easily applied to cloud computing environments. Therefore, the proposed scheme is more efficient and practical than the related works.

Mobile ad hoc networks have the features of open medium, dynamic topology, cooperative algorithms, lack of centralized monitoring etc. Due to these, mobile ad hoc networks are much vulnerable to security attacks when compared to wired networks. There are various routing protocols that have been developed to cope up with the limitations imposed by the ad hoc networks. But none of these routing schemes provide complete unlinkability and unobservability. In this paper we have done a survey about anonymous routing and secure communications in mobile ad hoc networks. Different routing protocols are analyzed based on public/private key pairs and cryptosystems, within that USOR can well protect user privacy against both inside and outside attackers. It is a combination of group signature scheme and ID based encryption scheme. These are run during the route discovery process. We implement USOR on ns2, and then its performance is compared with AODV.

In bound applications, the locations of events reportable by a device network have to be compelled to stay anonymous. That is, unauthorized observers should be unable to notice the origin of such events by analyzing the network traffic. The authors analyze 2 forms of downsides: Communication overhead and machine load problem. During this paper, the authors give a new framework for modeling, analyzing, and evaluating obscurity in device networks. The novelty of the proposed framework is twofold: initial, it introduces the notion of "interval indistinguishability" and provides a quantitative live to model obscurity in wireless device networks; second, it maps supply obscurity to the applied mathematics downside the authors showed that the present approaches for coming up with statistically anonymous systems introduce correlation in real intervals whereas faux area unit unrelated. The authors show however mapping supply obscurity to consecutive hypothesis testing with nuisance Parameters ends up in changing the matter of exposing non-public supply data into checking out associate degree applicable knowledge transformation that removes or minimize the impact of the nuisance data victimization sturdy cryptography algorithmic rule. By doing therefore, the authors remodeled the matter of analyzing real valued sample points to binary codes, that opens the door for committal to writing theory to be incorporated into the study of anonymous networks. In existing work, unable to notice unauthorized observer in network traffic. However this work in the main supported enhances their supply obscurity against correlation check, the most goal of supply location privacy is to cover the existence of real events.

This paper proposes a novel wireless MAC-layer approach towards achieving channel access anonymity. Nodes autonomously select periodic TDMA-like time-slots for channel access by employing a novel channel sensing strategy, and they do so without explicitly sharing any identity information with other nodes in the network. An add-on hardware module for the proposed channel sensing has been developed and the proposed protocol has been implemented in Tinyos-2.x. Extensive evaluation has been done on a test-bed consisting of Mica2 hardware, where we have studied the protocol's functionality and convergence characteristics. The functionality results collected at a sniffer node using RSSI traces validate the syntax and semantics of the protocol. Experimentally evaluated convergence characteristics from the Tinyos test-bed were also found to be satisfactory.

In recent years, Wireless Sensor Networks (WSNs) have become valuable assets to both the commercial and military communities with applications ranging from industrial control on a factory floor to reconnaissance of a hostile border. A typical WSN topology that applies to most applications allows sensors to act as data sources that forward their measurements to a central sink or base station (BS). The unique role of the BS makes it a natural target for an adversary that desires to achieve the most impactful attack possible against a WSN. An adversary may employ traffic analysis techniques such as evidence theory to identify the BS based on network traffic flow even when the WSN implements conventional security mechanisms. This motivates a need for WSN operators to achieve improved BS anonymity to protect the identity, role, and location of the BS. Many traffic analysis countermeasures have been proposed in literature, but are typically evaluated based on data traffic only, without considering the effects of network synchronization on anonymity performance. In this paper we use evidence theory analysis to examine the effects of WSN synchronization on BS anonymity by studying two commonly used protocols, Reference Broadcast Synchronization (RBS) and Timing-synch Protocol for Sensor Networks (TPSN).

In this paper we introduce PADAVAN, a novel anonymous data collection scheme for Vehicular Ad Hoc Networks (VANETs). PADAVAN allows users to submit data anonymously to a data consumer while preventing adversaries from submitting large amounts of bogus data. PADAVAN is comprised of an n-times anonymous authentication scheme, mix cascades and various principles to protect the privacy of the submitted data itself. Furthermore, we evaluate the effectiveness of limiting an adversary to a fixed amount of messages.

In recent years, Wireless Sensor Networks (WSNs) have become valuable assets to both the commercial and military communities with applications ranging from industrial automation and product tracking to intrusion detection at a hostile border. A typical WSN topology allows sensors to act as data sources that forward their measurements to a central sink or base station (BS). The unique role of the BS makes it a natural target for an adversary that desires to achieve the most impactful attack possible against a WSN. An adversary may employ traffic analysis techniques to identify the BS based on network traffic flow even when the WSN implements conventional security mechanisms. This motivates a need for WSN operators to achieve improved BS anonymity to protect the identity, role, and location of the BS. Although a variety of countermeasures have been proposed to improve BS anonymity, those techniques are typically evaluated based on a WSN that does not employ acknowledgements. In this paper we propose an enhanced evidence theory metric called Acknowledgement-Aware Evidence Theory (AAET) that more accurately characterizes BS anonymity in WSNs employing acknowledgements. We demonstrate AAET's improved robustness to a variety of configurations through simulation.

Aside from massive advantages in safety and convenience on the road, Vehicular Ad Hoc Networks (VANETs) introduce security risks to the users. Proposals of new security concepts to counter these risks are challenging to verify because of missing real world implementations of VANETs. To fill this gap, we introduce VANETsim, an event-driven simulation platform, specifically designed to investigate application-level privacy and security implications in vehicular communications. VANETsim focuses on realistic vehicular movement on real road networks and communication between the moving nodes. A powerful graphical user interface and an experimentation environment supports the user when setting up or carrying out experiments.

Wireless Sensor Network has a wide range of applications including environmental monitoring and data gathering in hostile environments. This kind of network is easily leaned to different external and internal attacks because of its open nature. Sink node is a receiving and collection point that gathers data from the sensor nodes present in the network. Thus, it forms bridge between sensors and the user. A complete sensor network can be made useless if this sink node is attacked. To ensure continuous usage, it is very important to preserve the location privacy of sink nodes. A very good approach for securing location privacy of sink node is proposed in this paper. The proposed scheme tries to modify the traditional Blast technique by adding shortest path algorithm and an efficient clustering mechanism in the network and tries to minimize the energy consumption and packet delay.

Sensor networks mainly deployed to monitor and report real events, and thus it is very difficult and expensive to achieve event source anonymity for it, as sensor networks are very limited in resources. Data obscurity i.e. the source anonymity problem implies that an unauthorized observer must be unable to detect the origin of events by analyzing the network traffic; this problem has emerged as an important topic in the security of wireless sensor networks. This work inspects the different approaches carried for attaining the source anonymity in wireless sensor network, with variety of techniques based on different adversarial assumptions. The approach meeting the best result in source anonymity is proposed for further improvement in the source location privacy. The paper suggests the implementation of most prominent and effective LSB Steganography technique for the improvement.

The wireless network is become larger than past. So in the recent years the wireless with multiple sinks is more useful. The anonymity and privacy in this network is a challenge now. In this paper, we propose a new method for anonymity in multi sink wireless sensor network. In this method we use layer encryption to provide source and event privacy and we use a label switching routing method to provide sink anonymity in each cluster. A master sink that is a powerful base station is used to connect sinks to each other.

Anonymous communications networks, such as Tor, help to solve the real and important problem of enabling users to communicate privately over the Internet. However, in doing so, anonymous communications networks introduce an entirely new problem for the service providers - such as websites, IRC networks or mail servers - with which these users interact, in particular, since all anonymous users look alike, there is no way for the service providers to hold individual misbehaving anonymous users accountable for their actions. Recent research efforts have focused on using anonymous blacklisting systems (which are sometimes called anonymous revocation systems) to empower service providers with the ability to revoke access from abusive anonymous users. In contrast to revocable anonymity systems, which enable some trusted third party to deanonymize users, anonymous blacklisting systems provide users with a way to authenticate anonymously with a service provider, while enabling the service provider to revoke access from any users that misbehave, without revealing their identities. In this paper, we introduce the anonymous blacklisting problem and survey the literature on anonymous blacklisting systems, comparing and contrasting the architecture of various existing schemes, and discussing the tradeoffs inherent with each design. The literature on anonymous blacklisting systems lacks a unified set of definitions, each scheme operates under different trust assumptions and provides different security and privacy guarantees. Therefore, before we discuss the existing approaches in detail, we first propose a formal definition for anonymous blacklisting systems, and a set of security and privacy properties that these systems should possess. We also outline a set of new performance requirements that anonymous blacklisting systems should satisfy to maximize their potential for real-world adoption, and give formal definitions for several optional features already supported by some sche- - mes in the literature.

Low-latency anonymity systems such as Tor rely on intermediate relays to forward user traffic; these relays, however, are often unreliable, resulting in a degraded user experience. Worse yet, malicious relays may introduce deliberate failures in a strategic manner in order to increase their chance of compromising anonymity. In this paper we propose using a reputation metric that can profile the reliability of relays in an anonymity system based on users' past experience. The two main challenges in building a reputation-based system for an anonymity system are: first, malicious participants can strategically oscillate between good and malicious nature to evade detection, and second, an observed failure in an anonymous communication cannot be uniquely attributed to a single relay. Our proposed framework addresses the former challenge by using a proportional-integral-derivative (PID) controller-based reputation metric that ensures malicious relays adopting time-varying strategic behavior obtain low reputation scores over time, and the latter by introducing a filtering scheme based on the evaluated reputation score to effectively discard relays mounting attacks. We collect data from the live Tor network and perform simulations to validate the proposed reputation-based filtering scheme. We show that an attacker does not gain any significant benefit by performing deliberate failures in the presence of the proposed reputation framework.