Feature Engineering for Detection of Wormhole Attacking in Mobile Ad Hoc Networks with Machine Learning Methods

Due to the self-configuring nature of a Mobile Ad Hoc Network (MANET), each node must participate in the routing process, in addition to its other activities. Therefore, routing in a MANET is especially vulnerable to malicious node activity leading to potentially severe disruption in network communications. The wormhole attack is a particularly severe MANET routing threat since it is easy to launch, can be launched in several modes, difficult to detect, and can cause significant communication disruption. In this paper we establish a practice for feature engineering of network data for wormhole attack prevention and detection with intrusion detection methods based on machine learning

Some Implementation Issues for Security Services based on IBE

Identity Based Encryption (IBE) is a public key cryptosystem where a unique identity string, such as an e-mail address, can be used as a public key. IBE is simpler than the traditional PKI since certificates are not needed. An IBE scheme is usually based on pairing of discrete points on elliptic curves. An IBE scheme can also be based on quadratic residuosity. This paper presents an overview of these IBE schemes and surveys present IBE based security services. Private key management is described in detail with protocols to authenticate users of Private Key Generation Authorities (PKG), to protect submission of generated private keys, and to avoid the key escrow problem. In the security service survey IBE implementations for smartcards, for smart phones, for security services in mobile networking, for security services in health care information systems, for secure web services, and for grid network security are presented. Also the performance of IBE schemes is estimated

Research Findings on Wormhole Attack Detection in Mobile Ad Hoc Networks

The Internet is moving from the traditional desktop network paradigm to a ubiquitous paradigm where a multitude of small computing devices such as computer chips and smart sensors are involved in daily activities and routines. This means that a rapidly growing amount of devices are connected to the Internet. At the same time, infrastructure-less and self-configuring systems like Mobile Ad hoc Networks (MANET) are gaining popularity since they provide a possibility for mobile devices to share information with each other without being dependent on a core infrastructure. Routing security in MANETs is, however, a significant challenge to wide scale adoption. One of the most severe security threats to MANET routing is the wormhole attack due to its ability to disrupt a significant proportion of network traffic, while simultaneously being difficult to detect. This paper provides an overview of recent research findings on wormhole attack detection in MANETs collected from a joint research project with Arcada University of Applied Sciences in Finland and The Open University, UK

A New MANET Wormhole Detection Algorithm Based on Traversal Time and Hop Count Analysis

As demand increases for ubiquitous network facilities, infrastructure-less and self-configuring systems like Mobile Ad hoc Networks (MANET) are gaining popularity. MANET routing security however, is one of the most significant challenges to wide scale adoption, with wormhole attacks being an especially severe MANET routing threat. This is because wormholes are able to disrupt a major component of network traffic, while concomitantly being extremely difficult to detect. This paper introduces a new wormhole detection paradigm based upon Traversal Time and Hop Count Analysis (TTHCA), which in comparison to existing algorithms, consistently affords superior detection performance, allied with low false positive rates for all wormhole variants. Simulation results confirm that the TTHCA model exhibits robust wormhole route detection in various network scenarios, while incurring only a small network overhead. This feature makes TTHCA an attractive choice for MANET environments which generally comprise devices, such as wireless sensors, which possess a limited processing capability

Identifying time measurement tampering in the traversal time and hop count analysis (TTHCA) wormhole detection algorithm

Traversal time and hop count analysis (TTHCA) is a recent wormhole detection algorithm for mobile ad hoc networks (MANET) which provides enhanced detection performance against all wormhole attack variants and network types. TTHCA involves each node measuring the processing time of routing packets during the route discovery process and then delivering the measurements to the source node. In a participation mode (PM) wormhole where malicious nodes appear in the routing tables as legitimate nodes, the time measurements can potentially be altered so preventing TTHCA from successfully detecting the wormhole. This paper analyses the prevailing conditions for time tampering attacks to succeed for PM wormholes, before introducing an extension to the TTHCA detection algorithm called ∆T Vector which is designed to identify time tampering, while preserving low false positive rates. Simulation results confirm that the ∆T Vector extension is able to effectively detect time tampered MANET attacks, thereby providing an important security enhancement to the TTHCA algorithm

Working Papers Presented in Arcada Workshop on Analytics in June 8, 2016

The Department of Business Management and Analytics in Arcada University of Applied Sciences arranged a Workshop on Analytics in June 8, 2016. Five Working Papers presented in this workshop are published in this report

Working Papers Presented in Arcada Workshop on Analytics in May 25, 2015

The Department of Business Management and Analytics in Arcada University of Applied Sciences arranged a Workshop on Analytics in May 25, 2015. Four Working Papers presented in this workshop are published in this report