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See detailAggregating large-scale measurements for Application Layer Traffic Optimization (ALTO) Protocol
Goergen, David UL; State, Radu UL; Gurbani, Vijay

Scientific Conference (2013, July)

Analyzing and aggregating large-scale broadband measurements is essential to study trends and derive network analytics. These trends and analyses could be made available through well defined protocols ... [more ▼]

Analyzing and aggregating large-scale broadband measurements is essential to study trends and derive network analytics. These trends and analyses could be made available through well defined protocols such as the Application Layer Traffic Optimization (ALTO) protocol. However, ALTO requires network information to be distilled and abstracted in form of a network map and a cost map. We describe our methodology for analyzing the United States Federal Communication Commission’s (FCC) Measuring Broadband America (MBA) dataset to derive required topology and cost maps suitable for consumption by an ALTO server. [less ▲]

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See detailASMATRA: Ranking ASs Providing Transit Service to Malware Hosters
Wagner, Cynthia UL; François, Jérôme UL; State, Radu UL et al

in IFIP/IEEE International Symposium on Integrated Network Management IM2013 (2013)

The Internet has grown into an enormous network offering a variety of services, which are spread over a multitude of domains. BGP-routing and Autonomous Systems (AS) are the key components for maintaining ... [more ▼]

The Internet has grown into an enormous network offering a variety of services, which are spread over a multitude of domains. BGP-routing and Autonomous Systems (AS) are the key components for maintaining high connectivity in the Internet. Unfortunately, Internet Service Providers (ISPs) operating ASs do not only host normal users and content, but also malicious content used by attackers for spreading malware, hosting phishing web-sites or performing any kind of fraudulent activity. Practical analysis shows that such malware-providing ASs prevent themselves from being de-peered by hiding behind other ASs, which do not host the malware themselves but simply provide transit service for malware. This paper presents a new method for detecting ASs that provide transit service for malware hosters, without being malicious themselves. A formal definition of the problem and the metrics are determined by using the AS graph. The PageRank algorithm is applied to improve the scalability and the completeness of the approach. The method is assessed on real and publicly available datasets, showing promising results. [less ▲]

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See detailSemantic based DNS Forensics
Marchal, Samuel UL; François, Jérôme UL; State, Radu UL et al

in Proceedings of the IEEE International Workshop on Information Forensics and Security (2012, December)

In network level forensics, Domain Name Service (DNS) is a rich source of information. This paper describes a new approach to mine DNS data for forensic purposes. We propose a new technique that leverages ... [more ▼]

In network level forensics, Domain Name Service (DNS) is a rich source of information. This paper describes a new approach to mine DNS data for forensic purposes. We propose a new technique that leverages semantic and natural language processing tools in order to analyze large volumes of DNS data. The main research novelty consists in detecting malicious and dangerous domain names by evaluating the semantic similarity with already known names. This process can provide valuable information for reconstructing network and user activities. We show the efficiency of the method on experimental real datasets gathered from a national passive DNS system. [less ▲]

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See detailProactive Discovery of Phishing Related Domain Names
Marchal, Samuel UL; François, Jérôme UL; State, Radu UL et al

in Proceedings of the 15th International Symposium on Research in Attacks, Intrusions and Defenses, Amsterdam 12-14 September 2012 (2012, September)

Phishing is an important security issue to the Internet, which has a significant economic impact. The main solution to counteract this threat is currently reactive blacklisting; however, as phishing ... [more ▼]

Phishing is an important security issue to the Internet, which has a significant economic impact. The main solution to counteract this threat is currently reactive blacklisting; however, as phishing attacks are mainly performed over short periods of time, reactive methods are too slow. As a result, new approaches to early identify malicious websites are needed. In this paper a new proactive discovery of phishing related domain names is introduced. We mainly focus on the automated detec- tion of possible domain registrations for malicious activities. We leverage techniques coming from natural language modelling in order to build pro- active blacklists. The entries in this list are built using language models and vocabularies encountered in phishing related activities - “secure”, “banking”, brand names, etc. Once a pro-active blacklist is created, ongoing and daily monitoring of only these domains can lead to the efficient detection of phishing web sites. [less ▲]

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See detailDNSSM: A large-scale Passive DNS Security Monitoring Framework
Marchal, Samuel UL; François, Jérôme UL; Wagner, Cynthia UL et al

in IEEE/IFIP Network Operations and Management Symposium (2012, April)

We present a monitoring approach and the supporting software architecture for passive DNS traffic. Monitoring DNS traffic can reveal essential network and system level activity profiles. Worm infected and ... [more ▼]

We present a monitoring approach and the supporting software architecture for passive DNS traffic. Monitoring DNS traffic can reveal essential network and system level activity profiles. Worm infected and botnet participating hosts can be identified and malicious backdoor communications can be detected. Any passive DNS monitoring solution needs to address several challenges that range from architectural approaches for dealing with large volumes of data up to specific Data Mining approaches for this purpose. We describe a framework that leverages state of the art distributed processing facilities with clustering techniques in order to detect anomalies in both online and offline DNS traffic. This framework entitled DSNSM is implemented and operational on several networks. We validate the framework against two large trace sets. [less ▲]

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See detailA Distance-Based Method to Detect Anomalous Attributes in Log Files
Hommes, Stefan UL; State, Radu UL; Engel, Thomas UL

in Proceedings of IEEE/IFIP NOMS 2012 (2012, April)

Dealing with large volumes of logs is like the prover- bial needle in the haystack problem. Finding relevant events that might be associated with an incident, or real time analysis of operational logs is ... [more ▼]

Dealing with large volumes of logs is like the prover- bial needle in the haystack problem. Finding relevant events that might be associated with an incident, or real time analysis of operational logs is extremely difficult when the underlying data volume is huge and when no explicit misuse model exists. While domain-specific knowledge and human expertise may be useful in analysing log data, automated approaches for detecting anomalies and track incidents are the only viable solutions when confronted with large volumes of data. In this paper we address the issue of automated log analysis and consider more specifically the case of ISP-provided firewall logs. We leverage approaches derived from statistical process control and information theory in order to track potential incidents and detect suspicious network activity. [less ▲]

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See detailDetecting Stealthy Backdoors with Association Rule Mining
Hommes, Stefan UL; State, Radu UL; Engel, Thomas UL

in IFIP Networking 2012 (2012)

In this paper we describe a practical approach for detecting a class of backdoor communication channel that relies on port knocking in order to activate a backdoor on a remote compromised system ... [more ▼]

In this paper we describe a practical approach for detecting a class of backdoor communication channel that relies on port knocking in order to activate a backdoor on a remote compromised system. Detecting such activation sequences is extremely challenging because of varying port sequences and easily modifiable port values. Simple signature-based ap- proaches are not appropriate, whilst more advanced statistics-based test- ing will not work because of missing and incomplete data. We leverage techniques derived from the data mining community designed to detect se- quences of rare events. Simply stated, a sequence of rare events is the joint occurrence of several events, each of which is rare. We show that search- ing for port knocking sequences can be reduced to a problem of finding rare associations. We have implemented a prototype and show some ex- perimental results on its performance and underlying functioning. [less ▲]

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See detailInstant Degradation of Anonymity in Low-Latency Anonymisation Systems
Ries, Thorsten UL; State, Radu UL; Engel, Thomas UL

in Sadre, Ramin; Novotny, Jiri; Celeda, Pavel (Eds.) et al Dependable Networks and Services, LNCS 7279 (2012)

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See detailMeasuring anonymity using network coordinate systems
Ries, Thorsten UL; State, Radu UL; Engel, Thomas UL

in International Symposium on Communications and Information Technologies (ISCIT), 2011 (2011)

Popularity and awareness of anonymisation systems increased tremendously over the past years, however only a very few systems made it from research to production. These systems usually add intermediate ... [more ▼]

Popularity and awareness of anonymisation systems increased tremendously over the past years, however only a very few systems made it from research to production. These systems usually add intermediate nodes in the communication path aiming to hide user identities. Several attacks against these systems exist, like timing attacks or exploitation of latency information. In this paper, we propose an alternative approach to disclose users of current popular anonymisation systems in practice by the means of virtual network coordinate systems, a widely accepted method for latency prediction and network optimisation. Mapping physical nodes to a n-dimensional space can reveal a geographical proximity that is used to disclose users, who expect to stay anonymous. We define a model that leverages network coordinates in order to measure quantitatively the anonymity services and evaluate it on the Planet-Lab research network. The basic idea is to analyse the relative distance between nodes and to calculate the probability of nodes being hosted in the same location. Evaluation proves that our proposed model can be used as a measure of anonymity. [less ▲]

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See detailComparison of Low-Latency Anonymous Communication Systems - Practical Usage and Performance
Ries, Thorsten UL; Panchenko, Andriy UL; State, Radu UL et al

in Ninth Australasian Information Security Conference (2011)

The most popular system for providing practical low-latency anonymity on the Internet is Tor. However, many other tools besides Tor exist as both free and commercial solutions. In this paper, we consider ... [more ▼]

The most popular system for providing practical low-latency anonymity on the Internet is Tor. However, many other tools besides Tor exist as both free and commercial solutions. In this paper, we consider five most popular low-latency anonymisation services that represent the current state of the art: single-hop proxies (Perfect Privacy and free proxies) and Onion Routing based solutions (Tor, I2P, and Jon-Donym). We assess their usability and rank them in regard to their anonymity. We also assess their efficiency and reliability. To this end, we define a set of metrics and present extensive measurements based on round-trip time, inter-packet delay variation and throughput. Apart from the technical realization, economic aspects are also crucial for anonymous communication systems. In order to attract more users, which is mandatory in order to improve anonymity per se, systems need to exhibit a certain payoff. We therefore define an economic model that takes all relevant aspects into consideration. In this paper, we describe the results obtained, lessons learned, and provide guidance for selecting the most appropriate system with respect to a set of requirements. [less ▲]

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See detailDetection of Abnormal Behaviour in a Surveillance Environment Using Control Charts
Hommes, Stefan UL; State, Radu UL; Zinnen, Andreas UL et al

in 8th IEEE International Conference on Advanced Video and Signal-Based Surveillance, 2011 (2011)

This paper introduces a new approach to unsupervised detection of abnormal sequences of images in video surveillance data. We leverage an online object detection method and statistical process control ... [more ▼]

This paper introduces a new approach to unsupervised detection of abnormal sequences of images in video surveillance data. We leverage an online object detection method and statistical process control techniques in order to identify suspicious sequences of events. Our method assumes a training phase in which the spatial distribution of objects is learned, followed by a chart-based tracking process. We evaluate the performance of our method on a standard dataset and have implemented a publicly available opensource prototype. [less ▲]

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See detailAn Autonomic Testing Framework for IPv6 Configuration Protocols
Becker, Sheila UL; Abdelnur, Humberto J.; State, Radu UL et al

in Lecture Notes in Computer Science 6155 (2010)

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See detailMachine Learning Techniques for Passive Network Inventory
François, Jérôme UL; Abdelnur, Humberto J.; State, Radu UL et al

in IEEE Transactions on Network and Service Management (2010), 7(4), 244-257

Being able to fingerprint devices and services, i.e., remotely identify running code, is a powerful service for both security assessment and inventory management. This paper describes two novel ... [more ▼]

Being able to fingerprint devices and services, i.e., remotely identify running code, is a powerful service for both security assessment and inventory management. This paper describes two novel fingerprinting techniques supported by isomorphic based distances which are adapted for measuring the similarity between two syntactic trees. The first method leverages the support vector machines paradigm and requires a learning stage. The second method operates in an unsupervised manner thanks to a new classification algorithm derived from the ROCK and QROCK algorithms. It provides an efficient and accurate classification. We highlight the use of such classification techniques for identifying the remote running applications. The approaches are validated through extensive experimentations on SIP (Session Initiation Protocol) for evaluating the impact of the different parameters and identifying the best configuration before applying the techniques to network traces collected by a real operator. [less ▲]

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See detailAbusing SIP authentication
Abdelnur, Humberto J.; Avanesov, Tigran UL; Rusinowitch, Michael et al

in Journal of Information Assurance and Security (2009), 4

The recent and massive deployment of Voice over IP infrastructures had raised the importance of the VoIP security and more precisely of the underlying signalisation protocol SIP. In this paper, we will ... [more ▼]

The recent and massive deployment of Voice over IP infrastructures had raised the importance of the VoIP security and more precisely of the underlying signalisation protocol SIP. In this paper, we will present a new attack against the authentication mechanism of SIP. This attack allows to perform toll fraud and call hijacking. We will detail the formal specification method that allowed to detect this vulnerability, highlight a simple usage case and propose a mitigation technique. [less ▲]

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See detailDefensive configuration with game theory
Becker, Sheila UL; State, Radu UL; Engel, Thomas UL

in The 11th IFIP/IEEE International Symposium on Integrated Network Management (2009)

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See detailUsing Game Theory to configure P2P SIP
Becker, Sheila UL; State, Radu UL; Engel, Thomas UL

in Lecture Notes in Computer Science (2009)

Detailed reference viewed: 64 (4 UL)