SoK: The Evolution of Sybil Defense via Social Networks

Alvisi, Lorenzo; Clement, Allen; Epasto, Alessandro; Lattanzi, Silvio; Panconesi, Alessandro

doi:10.1109/sp.2013.33

Cited by 120 publications

(110 citation statements)

References 40 publications

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“…As shown before, defenses built according to these properties are very sensitive to changes in the graph structure. Alvisi et al suggest to force Sybils into the required structure [18] by monitoring the link request acceptance rates of different nodes. If a node has to be accepted by a certain number of other nodes to be classified as benign, Sybils might be forced into creating many links among themselves (which are guaranteed to be accepted).…”

Section: Prospects Of Future Sybil Defense Solutionsmentioning

confidence: 99%

See 1 more Smart Citation

On the state of OSN-based Sybil defenses

Koll¹,

Stein

et al. 2014

2014 IFIP Networking Conference

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Abstract-A Sybil attack can inject many forged identities (called Sybils) to subvert a target system. Because of the severe damage that Sybil attacks can cause to a wide range of networking applications, there has been a proliferation of Sybil defense schemes. Of particular attention are those that explore the online social networks (OSNs) of users in a victim system in different ways. Unfortunately, while effective Sybil defense solutions are urgently needed, it is unclear how effective these OSN-based solutions are under different contexts. For example, all current approaches have focused on a common, classical scenario where it is difficult for an attacker to link Sybils with honest users and create attack edges; however, researchers have found recently that a modern scenario also becomes typical where an attacker can employ simple strategies to obtain many attack edges.In this work we analyze the state of OSN-based Sybil defenses. Our objective is not to design yet another solution, but rather to thoroughly analyze, measure, and compare how well or inadequate the well-known existing OSN-based approaches perform under both the classical scenario and the modern scenario. Although these approaches mostly perform well under the classical scenario, we find that under the modern scenario they are vulnerable to Sybil attacks. As shown in our quantitative analysis, very often a Sybil only needs a handful of attack edges to disguise itself as a benign node, and there is only a limited success in tolerating Sybils. Our study further points to capabilities a new solution must possess; in particular, in defense against Sybils under the modern scenario, we anticipate a new approach that enriches the structure of a social graph with more information about the relations between its users can work more effectively.

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Section: Prospects Of Future Sybil Defense Solutionsmentioning

confidence: 99%

“…Alvisi et al [18] pointed out that Sybil defense schemes tend to assume a minimal cut between Sybils and honest users, which however may not hold. The authors also analyzed SybilLimit [3] and show the sensitivity of the scheme to the existence of this cut.…”

Section: Introductionmentioning

confidence: 99%

On the state of OSN-based Sybil defenses

Koll¹,

Stein

et al. 2014

2014 IFIP Networking Conference

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“…In some scenarios, researchers develop de-anonymization techniques and then develop possible defense strategies against those types of techniques. Alvisi et al (2013) point out the Maginot syndrome for OSNs. In other words, while building strong defenses against sybil attacks, sophisticated attacks can be designed that exploit the weaknesses of these defenses.…”

Section: Defense Methods For De-anonymizationmentioning

confidence: 99%

“…Their main contribution is to be able to rank nodes where lower values indicate the likelihood of being a sybil node. Alvisi et al (2013) list four commonly used properties of structural graphs: popularity (degree of a node), small distance property (the maximum distance between any nodes in a social graph), clustering coefficient (related to the number of friendships of a user to the number of friendships among friends), and conductance (the ratio of the number of outgoing edges from the graph to the number of edges in the graph). The conductance property makes harder than other properties to act as undetected while not being fully fool-proof.…”

Section: Defense Methods For De-anonymizationmentioning

confidence: 99%

A Survey of Social Network Forensics

Karabiyik¹,

Canbaz²,

Aksoy³

et al. 2016

JDFSL

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Social networks in any form, specifically online social networks (OSNs), are becoming a part of our everyday life in this new millennium especially with the advanced and simple communication technologies through easily accessible devices such as smartphones and tablets. The data generated through the use of these technologies need to be analyzed for forensic purposes when criminal and terrorist activities are involved. In order to deal with the forensic implications of social networks, current research on both digital forensics and social networks need to be incorporated and understood. This will help digital forensics investigators to predict, detect and even prevent any criminal activities in different forms. It will also help researchers to develop new models/techniques in the future. This paper provides literature review of the social network forensics methods, models, and techniques in order to provide an overview to the researchers for their future works as well as the law enforcement investigators for their investigations when crimes are committed in the cyber space. It also provides awareness and defense methods for OSN users in order to protect them against to social attacks.

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“…In social media platforms have been plagued "Sybil" attacks (where a reputation system is subverted by creating multiple fake identifies in a P2P network e.g. Social Network Site), Alvisi et al [2013] document and evaluate the evolution of defences that have been developed to mitigate this growing threat. The study shows trends in defence mechanisms, that are quickly becoming mathematically complex in nature and sometimes proven to be ineffectual in practice e.g.…”

Section: Technicalmentioning

confidence: 99%

A Taxonomy of Attacks and a Survey of Defence Mechanisms for Semantic Social Engineering Attacks

2015

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Social engineering is used as an umbrella term for a broad spectrum of computer exploitations that employ a variety of attack vectors and strategies to psychologically manipulate a user. Semantic attacks are the specific type of social engineering attacks that bypass technical defences by actively manipulating object characteristics, such as platform or system applications, to deceive rather than directly attack the user. Commonly observed examples include obfuscated URLs, phishing emails, drive-by downloads, spoofed websites and scareware to name a few. This paper presents a taxonomy of semantic attacks, as well as a survey of applicable defences. By contrasting the threat landscape and the associated mitigation techniques in a single comparative matrix, we identify the areas where further research can be particularly beneficial.

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SoK: The Evolution of Sybil Defense via Social Networks

Cited by 120 publications

References 40 publications

On the state of OSN-based Sybil defenses

On the state of OSN-based Sybil defenses

A Survey of Social Network Forensics

A Taxonomy of Attacks and a Survey of Defence Mechanisms for Semantic Social Engineering Attacks

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