Biblio

This project develops techniques to protect against sensor attacks on cyber-physical systems. Specifically, a resilient version of the Kalman filtering technique accompanied with a watermarking approach is proposed to detect cyber-attacks and estimate the correct state of the system. The defense techniques are used in conjunction and validated on two case studies: i) an unmanned ground vehicle (UGV) in which an attacker alters the reference angle and ii) a Cube Satellite (CubeSat) in which an attacker modifies the orientation of the satellite degrading its performance. Based on this work, we show that the proposed techniques in conjunction achieve better resiliency and defense capability than either technique alone against spoofing and replay attacks.

The nodes in Mobile Ad hoc Network (MANET) can self-assemble themselves, locomote unreservedly and can interact with one another without taking any help from a centralized authority or fixed infrastructure. Due to its continuously changing and self-organizing nature, MANET is vulnerable to a variety of attacks like spoofing attack, wormhole attack, black hole attack, etc. This paper compares and analyzes the repercussion of the wormhole attack on MANET's two common routing protocols of reactive category, specifically, Dynamic Source Routing (DSR) and Ad-hoc On-Demand Distance Vector (AODV) by increasing the number of wormhole tunnels in MANET. The results received by simulation will reveal that DSR is greatly affected by this attack. So, as a solution, a routing algorithm for DSR which is based on trust is proposed to prevent the routes from caching malicious nodes.

Dynamic Fuzzy Rule Interpolation (D-FRI) offers a dynamic rule base for fuzzy systems which is especially useful for systems with changing requirements and limited prior knowledge. This suggests a possible application of D-FRI in the area of network security due to the volatility of the traffic. A honeypot is a valuable tool in the field of network security for baiting attackers and collecting their information. However, typically designed with fewer resources they are not considered as a primary security tool for use in network security. Consequently, such honeypots can be vulnerable to many security attacks. One such attack is a spoofing attack which can cause severe damage to the honeypot, making it inefficient. This paper presents a vigilant dynamic honeypot based on the D-FRI approach for use in predicting and alerting of spoofing attacks on the honeypot. First, it proposes a technique for spoofing attack identification based on the analysis of simulated attack data. Then, the paper employs the identification technique to develop a D-FRI based vigilant dynamic honeypot, allowing the honeypot to predict and alert that a spoofing attack is taking place in the absence of matching rules. The resulting system is capable of learning and maintaining a dynamic rule base for more accurate identification of potential spoofing attacks with respect to the changing traffic conditions of the network.

ID/password-based authentication is commonly used in network services. Some users set different ID/password pairs for different services, but other users reuse a pair of ID/password to other services. Such recycling allows the list attack in which an adversary tries to spoof a target user by using a list of IDs and passwords obtained from other system by some means (an insider attack, malwares, or even a DB leakage). As a countermeasure agains the list attack, biometric authentication attracts much attention than before. In 2012, Hattori et al. proposed a cancelable biometrics authentication scheme (fundamental scheme) based on homomorphic encryption algorithms. In the scheme, registered biometric information (template) and biometric information to compare are encrypted, and the similarity between these biometric information is computed with keeping encrypted. Only the privileged entity (a decryption center), who has a corresponding decryption key, can obtain the similarity by decrypting the encrypted similarity and judge whether they are same or not. Then, Hirano et al. showed the replay attack against this scheme, and, proposed two enhanced authentication schemes. In this paper, we propose a spoofing attack against the fundamental scheme when the feature vector, which is obtained by digitalizing the analogue biometric information, is represented as a binary coding such as Iris Code and Competitive Code. The proposed attack uses an unexpected vector as input, whose distance to all possible binary vectors is constant. Since the proposed attack is independent from the replay attack, the attack is also applicable to two revised schemes by Hirano et al. as well. Moreover, this paper also discusses possible countermeasures to the proposed spoofing attack. In fact, this paper proposes a countermeasure by detecting such unexpected vector.