Secure and efficient transmission of data based on Caesar Cipher Algorithm for Sybil attack in IoT

The Internet of Things (IoT) is an emerging concept in the field of information technology. IoT can integrate any real-time entity with another, using sensing, computing and communication capabilities to offer enhanced services in everyday life. In this article, IoT-based patient health monitoring is considered for use in IoT sensors deployed in devices. These devices are attached to the body of the patient for timely tracking of his or her health condition. During data transfers from devices connected to the patient’s body to the doctor, the data may be susceptible to security threats. IoT devices are subjected to many routing attacks, like blackhole, greyhole, Sybil, sinkhole and wormhole attacks. Sybil attacks are the most dangerous routing attacks. This type of attack involves stealing the identities of legitimate nodes; this, in turn, leads to information loss, misinterpretation in the network and an increase in routing disturbances. Hence, in this paper, we propose the use of the traditional Caesar Cipher Algorithm (CCA) along with the lightweight encryption algorithm (LEA) and the Received Signal Strength Indicator (RSSI) to detect and prevent Sybil attacks in an IoT environment. The proposed algorithm detects the false node in a particular path by announcing the attack to another node. It also prevents the attack by choosing an alternative path by which to forward data packets to the desired users. To ensure authentication, privacy and data integrity, the lightweight encryption algorithm with a 64-bit key is used with AODV as the routing protocol.

Detection of Localization Error in a WSN under Sybil Attack using Advanced DV-Hop Methodology

Localization is one of the most important aspects of Wireless Sensor Networks that make it applicable in a number of fields and areas. WSN advances in the technological aspects the number of attacks on the nodes of the WSN have also increased proficiently resulting in a number of security issues. One such attack is the Sybil attack which uses multiple pseudonymous identities to disrupt the reputation of the system. This paper is used to analyse the Sybil attacks using a detection and defence algorithm based on distance vector hop. Simulation of the results using the algorithm will be useful in effectively enhancing security of WSN nodes. In this proposed work based on the experimental analysis we have found out that with 50 beacon nodes, we have been able to decrease the average localisation error buy a solid 4% when compared with previous methodologies.

Innovative survey of defense machinery against Sybil attacks over wireless ad hoc network on IoT

Integrating IoT with Wireless Ad hoc Network (WANET) capabilities can solve several problems. However, because they both rely on identity nodes to communicate with each other, they are both vulnerable to Sybil attacks. Sybil attackers illegally change into several different identities (attackers) to carry out various malicious activities such as damaging data aggregation, voting, and disrupting routing. Several defense machineries have been proposed for Sybil attacks on WANET, which are mostly based on cryptography, location or position, network behavior, resource testing, and trust. However, the drawbacks are that not all machinery are suitable for use in networks with limited resources. This paper presents a survey, classification, and comparison of various defense machineries that have been proposed for non-IoT WANETs. The author emphasizes the issue of the advantages and disadvantages of this defense mechanism when applied to the IoT infrastructure and how each method can effectively recognize properties of Sybil attacks.

Utilizing Web Trackers for Sybil Defense

User tracking has become ubiquitous practice on the Web, allowing services to recommend behaviorally targeted content to users. In this article, we design Alibi, a system that utilizes such readily available personalized content, generated by recommendation engines in real time, as a means to tame Sybil attacks. In particular, by using ads and other tracker-generated recommendations as implicit user “certificates,” Alibi is capable of creating meta-profiles that allow for rapid and inexpensive validation of users’ uniqueness, thereby enabling an Internet-wide Sybil defense service. We demonstrate the feasibility of such a system, exploring the aggregate behavior of recommendation engines on the Web and demonstrating the richness of the meta-profile space defined by such inputs. We further explore the fundamental properties of such meta-profiles, i.e., their construction, uniqueness, persistence, and resilience to attacks. By conducting a user study, we show that the user meta-profiles are robust and show important scaling effects. We demonstrate that utilizing even a moderate number of popular Web sites empowers Alibi to tame large-scale Sybil attacks.

A Privacy-Preserving Key Management Scheme with Support for Sybil Attack Detection in VANETs

Vehicular ad hoc networks (VANETs) face two important and conflicting challenges with regards to security: preserve the privacy of vehicles in order to prevent malicious entities from tracking users and detect and remove bad actors that attempt to game the system for their own advantage. In particular, detecting Sybil attacks, in which one node attempts to appear as many, seemingly conflicts with the goal of privacy preservation, and existing schemes fail on either one or both accounts. To fill this gap, we present a hierarchical key management system which uses short group signatures to preserve member privacy at lower levels while allowing mid-level nodes to detect Sybil attacks and highly trusted nodes at the top of the hierarchy to completely reveal the real identities of malicious nodes in order to prevent them from rejoining the system and for use by legal authorities. In addition, we present an argument for relaxing the requirement of backward secrecy in VANET groups in the case when no malicious activity has been detected.