On Traffic Analysis Attacks to Encrypted VOIP Calls

The increasing popularity of VoIP telephony has brought a lot of attention and concern over security and privacy issues of VoIP communication. This thesis proposes a new class of traffic analysis attacks to encrypted VoIP calls. The goal of these attacks is to detect speaker or speech of encrypted VoIP calls. The proposed traffic analysis attacks exploit silent suppression, an essential feature of VoIP telephony. These attacks are based on application-level features so that the attacks can detect the same speech or the same speaker of different VoIP calls made with different VoIP codecs. We evaluate the proposed attacks by extensive experiments over different type of networks including commercialized anonymity networks and campus networks. The experiments show that the proposed traffic analysis attacks can detect speaker and speech of encrypted VoIP calls with a high detection rate which is a great improvement comparing with random guess. With the help of intersection attacks, the detection rate for speaker detection can be increased. In order to shield the detrimental effect of this proposed attacks, a countermeasure is proposed to mitigate the proposed traffic analysis attack

On Traffic Analysis Attacks to Encrypted VOIP Calls

The increasing popularity of VoIP telephony has brought a lot of attention and concern over security and privacy issues of VoIP communication. This thesis proposes a new class of traffic analysis attacks to encrypted VoIP calls. The goal of these attacks is to detect speaker or speech of encrypted VoIP calls. The proposed traffic analysis attacks exploit silent suppression, an essential feature of VoIP telephony. These attacks are based on application-level features so that the attacks can detect the same speech or the same speaker of different VoIP calls made with different VoIP codecs. We evaluate the proposed attacks by extensive experiments over different type of networks including commercialized anonymity networks and campus networks. The experiments show that the proposed traffic analysis attacks can detect speaker and speech of encrypted VoIP calls with a high detection rate which is a great improvement comparing with random guess. With the help of intersection attacks, the detection rate for speaker detection can be increased. In order to shield the detrimental effect of this proposed attacks, a countermeasure is proposed to mitigate the proposed traffic analysis attack

Blindspot: Indistinguishable Anonymous Communications

Communication anonymity is a key requirement for individuals under targeted surveillance. Practical anonymous communications also require indistinguishability - an adversary should be unable to distinguish between anonymised and non-anonymised traffic for a given user. We propose Blindspot, a design for high-latency anonymous communications that offers indistinguishability and unobservability under a (qualified) global active adversary. Blindspot creates anonymous routes between sender-receiver pairs by subliminally encoding messages within the pre-existing communication behaviour of users within a social network. Specifically, the organic image sharing behaviour of users. Thus channel bandwidth depends on the intensity of image sharing behaviour of users along a route. A major challenge we successfully overcome is that routing must be accomplished in the face of significant restrictions - channel bandwidth is stochastic. We show that conventional social network routing strategies do not work. To solve this problem, we propose a novel routing algorithm. We evaluate Blindspot using a real-world dataset. We find that it delivers reasonable results for applications requiring low-volume unobservable communication.Comment: 13 Page

Traffic Analysis Attacks on Skype VoIP Calls

Skype is one of the most popular voice-over-IP (VoIP) service providers. One of the main reasons for the popularity of Skype VoIP services is its unique set of features to protect privacy of VoIP calls such as strong encryption, proprietary protocols, unknown codecs, dynamic path selection, and the constant packet rate. In this paper, we propose a class of passive traffic analysis attacks to compromise privacy of Skype VoIP calls. The proposed attacks are based on application-level features extracted from VoIP call traces. The proposed attacks are evaluated by extensive experiments over different types of networks including commercialized anonymity networks and our campus network. The experiment results show that the proposed traffic analysis attacks can greatly compromise the privacy of Skype calls. Possible countermeasure to mitigate the proposed traffic analysis attacks are analyzed in this paper

Traffic Analysis Attacks on Skype VoIP Calls

Skype is one of the most popular voice-over-IP (VoIP) service providers. One of the main reasons for the popularity of Skype VoIP services is its unique set of features to protect privacy of VoIP calls such as strong encryption, proprietary protocols, unknown codecs, dynamic path selection, and the constant packet rate. In this paper, we propose a class of passive traffic analysis attacks to compromise privacy of Skype VoIP calls. The proposed attacks are based on application-level features extracted from VoIP call traces. The proposed attacks are evaluated by extensive experiments over different types of networks including commercialized anonymity networks and our campus network. The experiment results show that the proposed traffic analysis attacks can greatly compromise the privacy of Skype calls. Possible countermeasure to mitigate the proposed traffic analysis attacks are analyzed in this paper

A Comprehensive Survey of Voice over IP Security Research

We present a comprehensive survey of Voice over IP security academic research, using a set of 245 publications forming a closed cross-citation set. We classify these papers according to an extended version of the VoIP Security Alliance (VoIPSA) Threat Taxonomy. Our goal is to provide a roadmap for researchers seeking to understand existing capabilities and to identify gaps in addressing the numerous threats and vulnerabilities present in VoIP systems. We discuss the implications of our findings with respect to vulnerabilities reported in a variety of VoIP products. We identify two specific problem areas (denial of service, and service abuse) as requiring significant more attention from the research community. We also find that the overwhelming majority of the surveyed work takes a black box view of VoIP systems that avoids examining their internal structure and implementation. Such an approach may miss the mark in terms of addressing the main sources of vulnerabilities, i.e., implementation bugs and misconfigurations. Finally, we argue for further work on understanding cross-protocol and cross-mechanism vulnerabilities (emergent properties), which are the byproduct of a highly complex system-of-systems and an indication of the issues in future large-scale systems

On Privacy of Encrypted Speech Communications

Silence suppression, an essential feature of speech communications over the Internet, saves bandwidth by disabling voice packet transmissions when silence is detected. However, silence suppression enables an adversary to recover talk patterns from packet timing. In this paper, we investigate privacy leakage through the silence suppression feature. More specifically, we propose a new class of traffic analysis attacks to encrypted speech communications with the goal of detecting speakers of encrypted speech communications. These attacks are based on packet timing information only and the attacks can detect speakers of speech communications made with different codecs. We evaluate the proposed attacks with extensive experiments over different type of networks including commercial anonymity networks and campus networks. The experiments show that the proposed traffic analysis attacks can detect speakers of encrypted speech communications with high accuracy based on traces of 15 minutes long on average