Analysis of a Reputation System for Mobile Ad-Hoc Networks with Liars

The application of decentralized reputation systems is a promising approach to ensure cooperation and fairness, as well as to address random failures and malicious attacks in Mobile Ad-Hoc Networks. However, they are potentially vulnerable to liars. With our work, we provide a first step to analyzing robustness of a reputation system based on a deviation test. Using a mean-field approach to our stochastic process model, we show that liars have no impact unless their number exceeds a certain threshold (phase transition). We give precise formulae for the critical values and thus provide guidelines for an optimal choice of parameters.Comment: 17 pages, 6 figure

A Practical Approach to Protect IoT Devices against Attacks and Compile Security Incident Datasets

open access articleThe Internet of Things (IoT) introduced the opportunity of remotely manipulating home appliances (such as heating systems, ovens, blinds, etc.) using computers and mobile devices. This idea fascinated people and originated a boom of IoT devices together with an increasing demand that was difficult to support. Many manufacturers quickly created hundreds of devices implementing functionalities but neglected some critical issues pertaining to device security. This oversight gave rise to the current situation where thousands of devices remain unpatched having many security issues that manufacturers cannot address after the devices have been produced and deployed. This article presents our novel research protecting IOT devices using Berkeley Packet Filters (BPFs) and evaluates our findings with the aid of our Filter.tlk tool, which is able to facilitate the development of BPF expressions that can be executed by GNU/Linux systems with a low impact on network packet throughput

Heuristics for Cultural Algorithm Knowledge Driven Search in Dynamic Social Systems

Population evolution algorithms such as Cultural Algorithms (CA) enable a global repository known as the belief space consisting of common cultural traits to influence the population space. Two important aspects of CA are the knowledge and its propagation. The population use social networks for communication. Knowledge representation is generally dependent on the application at hand. In this thesis the role of CA belief space knowledge in application neutral simulation is explored. A standard benchmark function is used to study the performance of evolutionary algorithms. The function captures the characteristics of a neutral world in dynamic settings. A multi-agent simulation was designed where autonomous agents are able to communicate, acquire and exploit various knowledge types including topographic, domain, historical and situational. While all these strategies showed improvements when searching for the global maximum, we found that domain based topographic exploitation strategies of the landscape were the more efficient