Artificial immune system based security algorithm for mobile ad hoc networks

Securing Mobile Ad hoc Networks (MANET) that are a collection of mobile, decentralized, and self-organized nodes is a challenging task. The most fundamental aspect of a MANET is its lack of infrastructure, and most design issues and challenges stem from this characteristic. The lack of a centralized control mechanism brings added difficulty in fault detection and correction. The dynamically changing nature of mobile nodes causes the formation of an unpredictable topology. This varying topology causes frequent traffic routing changes, network partitioning and packet losses. The various attacks that can be carried out on MANETs challenge the security capabilities of the mobile wireless network in which nodes can join, leave and move dynamically. The Human Immune System (HIS) provides a foundation upon which Artificial Immune algorithms are based. The algorithms can be used to secure both host-based and network-based systems. However, it is not only important to utilize the HIS during the development of Artificial Immune System (AIS) based algorithms as much as it is important to introduce an algorithm with high performance. Therefore, creating a balance between utilizing HIS and AIS-based intrusion detection algorithms is a crucial issue that is important to investigate. The immune system is a key to the defence of a host against foreign objects or pathogens. Proper functioning of the immune system is necessary to maintain host homeostasis. The cells that play a fundamental role in this defence process are known as Dendritic Cells (DC). The AIS based Dendritic Cell Algorithm is widely known for its large number of applications and well established in the literature. The dynamic, distributed topology of a MANET provides many challenges, including decentralized infrastructure wherein each node can act as a host, router and relay for traffic. MANETs are a suitable solution for distributed regional, military and emergency networks. MANETs do not utilize fixed infrastructure except where a connection to a carrier network is required, and MANET nodes provide the transmission capability to receive, transmit and route traffic from a sender node to the destination node. In the HIS, cells can distinguish between a range of issues including foreign body attacks as well as cellular senescence. The primary purpose of this research is to improve the security of MANET using the AIS framework. This research presents a new defence approach using AIS which mimics the strategy of the HIS combined with Danger Theory. The proposed framework is known as the Artificial Immune System based Security Algorithm (AISBA). This research also modelled participating nodes as a DC and proposed various signals to indicate the MANET communications state. Two trust models were introduced based on AIS signals and effective communication. The trust models proposed in this research helped to distinguish between a “good node” as well as a “selfish node”. A new MANET security attack was identified titled the Packet Storage Time attack wherein the attacker node modifies its queue time to make the packets stay longer than necessary and then circulates stale packets in the network. This attack is detected using the proposed AISBA. This research, performed extensive simulations with results to support the effectiveness of the proposed framework, and statistical analysis was done which showed the false positive and false negative probability falls below 5%. Finally, two variations of the AISBA were proposed and investigated, including the Grudger based Artificial Immune System Algorithm - to stimulate selfish nodes to cooperate for the benefit of the MANET and Pain reduction based Artificial Immune System Algorithm - to model Pain analogous to HIS

Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks

This book presents collective works published in the recent Special Issue (SI) entitled "Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks”. These works expose the readership to the latest solutions and techniques for MANETs and VANETs. They cover interesting topics such as power-aware optimization solutions for MANETs, data dissemination in VANETs, adaptive multi-hop broadcast schemes for VANETs, multi-metric routing protocols for VANETs, and incentive mechanisms to encourage the distribution of information in VANETs. The book demonstrates pioneering work in these fields, investigates novel solutions and methods, and discusses future trends in these field

The Spell of Capital

This book explores the tradition, impact, and contemporary relevance of two key ideas from Western Marxism: Georg Lukács's concept of reification, in which social aspects of humanity are viewed in objectified terms, and Guy Debord's concept of the spectacle, where the world is packaged and presented to consumers in uniquely mediated ways. Bringing the original, yet now often forgotten, theoretical contexts for these terms back to the fore, Johan Hartle and Samir Gandesha offer a new look at the importance of Western Marxism from its early days to the present moment-and reveal why Marxist cultural critique must continue to play a vital role in any serious sociological analysis of contemporary society

Monte Carlo Method with Heuristic Adjustment for Irregularly Shaped Food Product Volume Measurement

Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method

Predicting breast cancer risk, recurrence and survivability

This thesis focuses on predicting breast cancer at early stages by using machine learning algorithms based on biological datasets. The accuracy of those algorithms has been improved to enable the physicians to enhance the success of treatment, thus saving lives and avoiding several further medical tests

Clinical pharmacokinetic monitoring and resistance testing for the optimisation of antiviral therapy targeting human cytomegalovirus

Cytomegalovirus (CMV) breakthrough despite therapy with ganciclovir remains a problem, particularly for solid organ transplant (SOT) patients. This could be owing to inadequate ganciclovir blood concentrations, and it is unclear whether monitoring of this is of clinical use. The first study aim was to verify the validity of ganciclovir blood concentration monitoring with daily area-under-curve (AUC24) as a predictive marker for breakthrough CMV. Systematic review of 610 SOT recipients across 11 studies evaluated the association between ganciclovir AUC24 and CMV incidence. Despite dose adjustments for creatinine clearance (CrCL), AUC24 for patients varied from 28-53.7 µg·h/mL. The incidence of CMV infection ranged from 0-50%, while disease ranged from 0-3.1%. One study showed a reduced risk of viraemia when AUC24 was 40-50 µg·h/mL. This formed the basis for a prospective 2-year study on 50 kidney transplant recipients monitored for ganciclovir AUC24 and CMV infection and genotypic resistance markers. Doses given to patients with CrCL<40 mL/min were higher than the guidelines, and lower when CrCL≥40 mL/min. Mean AUC24 was 33±13 µg·h/mL and 82% of subjects did not attain therapeutic target. Monte Carlo simulations with data from the study cohort were conducted to determine whether the manufacturer’s dosing would be predicted to result in higher target attainment than the study cohort. Simulations showed guidelines also could not attain therapeutic target in 80% of individuals. Breakthrough CMV occurred in 6% of recipients, while 12% developed late-onset infection. Mean AUC24 between recipients with and without infection was not significantly different (p=0.528). One recipient with AUC24 20 µg·h/mL acquired GCV-resistant mutations. The second aim was to uncover novel GCV-resistance mutations. Two UL97 mutations of unknown antiviral susceptibility, A594S and G598D, were selected from the diagnostics laboratory for examination. Investigations found A5946S-mutated CMV showed GCV-resistance on plaque reduction, while virus replication was similar to wildtype. Enzyme activity was assessed using ganciclovir as substrate, or auto-phosphorylation, showed ectopically-expressed UL97 mutants retained some enzyme activity in vitro. In conclusion, ganciclovir AUC24 predicted CMV breakthrough of resistant variants in kidney transplant recipients. CMV genotypes of unknown antiviral susceptibility were evaluated, where marker-transfer provided evidence for a new GCV-resistant CMV UL97 mutation