Sybil Attack

Existing on-line social networks (OSN) such as Facebook suffer from several weaknesses regarding privacy and security due to their inherent handling of personal data. As pointed out in [4], a preliminary analysis of existing OSNs shows that they are subject to a number of vulnerabilities, ranging from cloning legitimate users to sybil attacks through privacy violations. Starting from these OSN vulnerabilities as the first step of a broader research activity, we came up with a new approach that is very promising in re-visiting security and privacy problems in distributed systems and networks. We suggest a solution that both aims at avoiding any centralized control and leverages on the real life trust between users, that is part of the social network application itself. An anonymization technique based on multi-hop routing among trusted nodes guarantees privacy in data access and, generally speaking, in all the OSN operations.

Wireless sensor networks constitute of sensor nodes which are small in size, running on battery, limited computation power, memory and communication capability. Operational environment of sensor nodes is generally unfavorable and unattended which may result in failure of sensor nodes and they are prone to various malicious attacks. One of these attacks is Sybil attack. Sybil attack is harmful enough to get attention of researchers. In Sybil attack a malicious node illegally forges an unbounded number of identities to present an illusion to the network as if it were different legitimate nodes. We propose here a key management protocol that will prevent any such attacks.

The foreseen dream of Vehicular Ad Hoc NETwork (VANET) deployment is obstructed by long-chased security and privacy nightmares. Despite of the increasing demand for perfect privacy, it conflicts with rather more serious security threat called ‘Sybil Attack’ which refers to, impersonation of one physical entity for many, namely Sybil nodes. In such circumstances, data received from malicious Sybil attacker may seem as if it was received from many distinct physical nodes. Sybil nodes may deliberately mislead other neighbors, resulting in catastrophic situations like traffic jams or even deadly accidents. Preventing such attacks in a privacy-enabled environment is not a trivial task. In this paper, we aim at two conflicting goals, i.e. privacy and Sybil attack in VANET. We leverage pseudonymless beaconing in order to preserve privacy. To cope with Sybil attack, we put forth a twofold strategy. In order to avoid Sybil attack through scheduled beacons, we employ tamper resistant module (TRM) to carry out a pre-assembly data analysis on data that is used to assemble beacons whereas for event reporting message (ERM), we employ road side units (RSUs) to localize Sybil nodes in VANET and report them to the revocation authority(s). RSUs distribute authorized tokens among the benign vehicular nodes which in turn are consumed to report ERMs. RSUs collect ERMs for certain event and figures out if more than one ERM for the same event includes identical token or, if an ERM is sent more than once by the same source. Our proposed scheme preserves privacy in both beacons and ERMs, and provides conditional anonymity where in case of a dispute; malicious attackers are subject to revocation. We also show that our proposed scheme outperforms the previously proposed scheme from security and computational complexity standpoint.

Existing on-line social networks (OSN) such as Facebook suffer from several weaknesses regarding privacy and security due to their inherent handling of personal data. As pointed out in [4], a preliminary analysis of existing OSNs shows that they are subject to a number of vulnerabilities, ranging from cloning legitimate users to sybil attacks through privacy violations. Starting from these OSN vulnerabilities as the first step of a broader research activity, we came up with a new approach that is very promising in re-visiting security and privacy problems in distributed systems and networks. We suggest a solution that both aims at avoiding any centralized control and leverages on the real life trust between users, that is part of the social network application itself. An anonymization technique based on multi-hop routing among trusted nodes guarantees privacy in data access and, generally speaking, in all the OSN operations.

New Media usage has expanded in unexpected directions. This qualitative study pulls together two new media phenomena that demonstrate widespread engineered influence through Twitter dispersion. The first aspect is the practice of sock-puppetry deception that occurs when social media identities are used without proof of identity. The relative ease in creating a single invented online identity is overshadowed by the more recent practise of harnessing thousands of created identities to accentuate the standing of a single identity. The second aspect is the use of metadata to fetch and find increased nodes of commonality. This promulgates the perception of connectivity and homogeneity in terms of information transfer. Identity masking in Twitter, and the use of homophily to manipulate authority, public sway, and social media deception are a formidable combination. This study considers the increasing use of sock-puppetry in conjunction with techniques that exploit homophily to sway the perceptions of others. The ethical and socio-political issues of identity deception and their subsequent impact are discussed. Using the publicly available Twitter accounts of six high profile political figures, the study compares retweets that retain metadata from original tweets. Using both real and fake accounts, the paper tests the hypothesis that non-genuine Sybil Twitter accounts are deployed in the followings of popular figures by using metadata in retweets to establish credibility amongst fake entities. New Media experiences augmented manipulation in multiple ways. The use of metatagging to expose greater commonality increases both the frequency and the amplitude of information diffusion when delivered through social networking and microblogging. A comparison of the associated tweets, followers, and retweets of high profile leaders indicate pervasive sock-puppetry and Sybil deception. With homophily embedded into Tweets and Retweets, sock puppetry in social media presents a challenge. Where homophily fits traditional notions of " similarity between two nodes " , increasing the likelihood of likeness to occur is problematic. If homophily and false identity coalesce, then the use of twitter as a reliable social medium is contingent on discrete user identity in social media.

Signal Strength based position verification is more promising as compared to other Sybil attack detection techniques because it is lightweight and does not require centralisation. Nodes can locally determine their locations through received signal strength variations and inform neighbours about location updates accordingly. In position verification, network nodes verify the position of each node and further ensure that each physical location is bounded by only one identity at any particular time. In this paper we will survey Sybil attack detection techniques and their related issues. Finally we will present our ideas about the Sybil attack detection via one-time localization (only at the entrance into the network) which significantly reduces the communication overhead unlike other schemes where per packet location tracking or periodic dissemination of location information is used to detect Sybil attacks.

Wireless sensor networks constitute of sensor nodes which are running on battery, small in size, limited memory, computation power and communication capability. Operational environment of sensor nodes is generally unfavorable and unattended which may result in failure of sensor nodes and they are prone to various malicious attacks. One of these attacks is Sybil attack. In this paper Sybil attack is prevented using cryptography. This paper shows the effect of Sybil attack in wireless sensor network and also shows the effect of proposed algorithm on network performance in presence of Sybil nodes.

One of the most important problems of WMNs, that is even preventing them from being used in many sensitive applications, is the lack of security. To ensure security of WMNs, two strategies need to be adopted: embedding security mechanisms into the network protocols, and developing efficient intrusion detection and reaction systems. To date, many secure protocols have been proposed, but their role of defending attacks is very limited.We present a framework for intrusion detection in WMNs that is orthogonal to the network protocols. It is based on a reputation system, that allows to isolate ill-behaved nodes by rating their reputation as low, and distributed agents based on unsupervised learning algorithms (self-organizing maps), that are able to detect deviations from the normal behavior. An additional advantage of this approach is that it is quite independent of the attacks, and therefore it can detect and confine new, previously unknown, attacks. Unlike previous approaches, and due to the inherent insecurity of WMN nodes, we assume that confidentiality and integrity cannot be preserved for any single node.

Our main contribution is a novel approach to enhancing po- sition security in VANET. We achieve local and global posi- tion security by using the on-board radar to detect neighbor- ing vehicles and to confirm their announced coordinates. We compute cosine similarity among data collected by radar and neighbors' reports to filter the forged data from the truthful data. Based

The Sybil Attack is a serious threat to the secure and dependable operation of wireless ad hoc networks. This paper proposes an algorithm to provide each correct node in an one-hop wireless network with a quorum of non-Sybil identities from the neighbourhood. The quorums provided to different correct nodes may differ, but their intersection is composed by a majority of correct identities, with an arbitrarily close to 1 probability. Therefore, the quorums may be used for different purposes, such as voting. The algorithm ...

The Sybil attack is one of the most aggressive and evasive attacks in sensor networks that can affect on many aspects of network functioning. Thus, its efficient detection is of highest importance. In order to resolve this issue, in this work we propose to couple reputation systems with agents based on self-organizing map algorithm trained for detecting outliers in data. The response of the system consists in assigning low reputation values to the compromised node rendering them isolated from the rest of the network. The main improvement of this work consists in the way of calculating reputation, which is more flexible and discriminative in distinguishing attacks from normal behavior. Self-organizing map algorithm deploys feature space based on sequences of sensor outputs. Our solution offers many benefits: scalable solution, fast response to adversarial activities, ability to detect unknown attacks, high adaptability and low consumption. The testing results demonstrate its high ability in detecting and confining Sybil attack.

The Sybil attack is one of the most aggressive and evasive attacks in sensor networks that can affect on many aspects of network functioning. Thus, its efficient detection is of highest importance. In order to resolve this issue, in this work we propose to couple reputation systems with agents based on self-organizing map algorithm trained for detecting outliers in data. The response of the system consists in assigning low reputation values to the compromised node rendering them isolated from the rest of the network. The main improvement of this work consists in the way of calculating reputation, which is more flexible and discriminative in distinguishing attacks from normal behavior. Self-organizing map algorithm deploys feature space based on sequences of sensor outputs. Our solution offers many benefits: scalable solution, fast response to adversarial activities, ability to detect unknown attacks, high adaptability and low consumption. The testing results demonstrate its high ability in detecting and confining Sybil attack.