SiLK Tools is a suite of network ?ow tools that network analysts use to detect intru- sions, viruses, worms, and botnets, and to analyze network performance. One tool in SiLK is tuple ?ltering, where ?ows are ?ltered based on inclusion in a “multi-key” set (MKset) whose unique members are composite keys whose values are from multiple ?elds in a SiLK ?ow record. We propose and evaluate a more e?cient method of im- plementing MKset ?ltering that uses cuckoo hashes, which underlie McHugh et al.’s cuckoo bag (cubag) suite of MKset SiLK tools. Our solution improves execution time for ?ltering with an MKset of size k by a factor of O(logk), and decreases memory footprints for MKset ?ltering by 50%. The solution also saves 90% of disk space for MKset ?le storage, and adds functionality for transformations such as subnet masking on ?ow records during MKset ?ltering.

The internet data traffic is tripling every two years due to the exponential growth in the number of routers. Routers implement the packet classification methodology by determining the flow of the packet, based on various rule checking mechanisms that are performed on the packet headers. However, the memory components like TCAMs used by these various rules are very expensive and power hungry. Henceforth, the current IP Lookup algorithms implemented in hardware are even though able to achieve multi-gigabit speeds, yet suffer with great memory overhead. To overcome this limitation, we propose a packet classification methodology that comprises of MicroCuckoo-hash technique, to route packets. This approach alleviates the memory requirements significantly, by completely eliminating the need for TCAM cells. Cuckoo hash is used to achieve very high speed, hardware accelerated table lookups and also are economical compared to TCAMs. The proposed IP Lookup algorithm is implemented as a simulation-based hardware/software model. This model is developed, tested and synthesized using Vivado HLS tool. / Master of Science

This Master’s thesis describes reverse engineering with focus on malware analysis. Reader will be informed about theoretical description of static and dynamic analysis. These techniques are later used on analysis of 5 malware families with focus on detection of used anti-sandbox techniques. After that new theoretical improvements are proposed with detection of anti-sandbox techniques or fully avoiding such anti-sandbox evasion techniques. Finally these changes are implemented on main sandbox of Avast Software from which reader can see how effective these improvements are.

This thesis aims to produce a novel multi-objective algorithm that is based on Cuckoo Search by Dr. Xin-She Yang. Cuckoo Search is a promising nature-inspired meta-heuristic optimization algorithm, which currently is only able to solve single-objective optimization problems. After an introduction, a number of theoretical points are presented as a basis for the decision of which algorithms to hybridize Cuckoo Search with. These are then reviewed in detail and verified against current benchmark algorithms to evaluate their efficiency. To test the proposed algorithm in a new setting, a real-world combinatorial problem is used. The proposed algorithm is then used as an optimization engine for a simulation-based system and compared against a current implementation.

The main goal of a scheduling process is to decide when and how to execute each of the project’s activities. Despite large variety of researched scheduling problems, the majority of them can be described as generalisations of the resource-constrained project scheduling problem (RCPSP). Because of wide applicability and challenging difficulty, RCPSP has attracted vast amount of attention in the research community and great variety of heuristics have been adapted for solving it. Even though these heuristics are structurally different and operate according to diverse principles, they are designed to obtain only one solution at a time. In the recent researches on RCPSPs, it was proven that these kind of problems have complex multimodal fitness landscapes, which are characterised by a wide solution search spaces and presence of multiple local and global optima. The main goal of this thesis is twofold. Firstly, it presents a variation of the RCPSP that considers optimisation of projects in an uncertain environment where resources are modelled to adapt to their environment and, as the result of this, improve their efficiency. Secondly, modification of a novel evolutionary computation method Cuckoo Search (CS) is proposed, which has been adapted for solving combinatorial optimisation problems and modified to obtain multiple solutions. To test the proposed methodology, two sets of experiments are carried out. First, the developed algorithm is applied to a real-life software development project. Second, performance of the algorithm is tested on universal benchmark instances for scheduling problems which were modified to take into account specifics of the proposed optimisation model. The results of both experiments demonstrate that the proposed methodology achieves competitive level of performance and is capable of finding multiple global solutions, as well as prove its applicability in real-life projects.

Abstract Not Provided / Thesis / Master of Science (MSc)

In 1996 and 1997, I studied the nest site selection of the yellow-billed cuckoo (Coccyzus americanus) in the George Washington National Forest, southwestern Virginia. Data were collected from nine 30 ha plots. I compared the habitat features of nest sites with two types of nonnest sites (nonuse and systematically random). Habitat features were measured at 3 spatial scales: nest tree, nest tree area (0.0049 ha centered on the nest), and nest stand (forest stand surrounding the nest). Yellow-billed cuckoo nests were oriented in a nonrandom direction (mean angle = 114°, r = 0.43, P = 0.05) with respect to the bole and were concealed more from above than from below (n = 14, M = 5, p = 0.01) or from the side (n = 14, M = 4, p = 0.04). Slope aspect was nonrandom at yellow-billed cuckoo nest sites (mean angle = 143°, r = 0.52, P < 0.05). Small stem density in the nest tree area was greater (P = 0.029) at nest sites than nonuse sites but species composition was similar. The density of grape (Vitus spp.) and dogwood (Cornus spp.) snags was greater at nest sites than random sites (P < 0.001). Total basal area at yellow-billed cuckoo nest stands was lower than nonuse or random sites with (P = 0.033, and 0.016, respectively) or without (P = 0.014, and 0.004, respectively) snags. Nest sites also occurred in areas with less (P = 0.008) canopy cover but more (P = 0.038) ground cover than random sites. Yellow-billed cuckoos appeared to select nest sites based on the structure and composition of the understory vegetation. Periodic disturbance that promotes the growth of shade intolerant species, but maintains the general structure of the stand may be beneficial for this species that appears to select disturbed areas in mature forests. / Department of Biology

The design of public transportation networks includes the problem of finding efficient transit routes. This problem is called the Urban Transit Routing Problem (UTRP) and it is a highly complex combinatorial optimization problem. Solving the UTRP and finding more efficient transit routes may lead to large cost savings as well as shorter average travel times for the passengers. The most common approach to solving it, in the literature, is with the usage of a metaheuristic algorithm. The purpose of this thesis is to solve the UTRP with such an algorithm, and to make the algorithm efficient. To this end, the multi-objective Discrete Cuckoo Search (MODCS) algorithm is introduced and it solves the UTRP with respect to both passenger and operator objectives. Two network instances are solved for: the common benchmark network of Mandl's network, and the Södertälje bus network. For Mandl's network, the results were compared to other algorithms in the literature. The results showed great performance of the MODCS algorithm with respect to the passenger objective, and not as good with respect to the operator objective. The computation times of the MODCS were higher than those of the other algorithms. For the Södertälje bus network, the MODCS algorithm found route sets with significantly better objective values than those of a previous master thesis algorithm. Furthermore, the average computation times of the MODCS algorithm were much less than those of the previous master thesis algorithm. / Att designa kollektivtrafiknät inkluderar problemet av att hitta effektiva kollektivtrafiklinjer. Detta problem kallas för Urban Transit Routing Problem (UTRP) och det är ett mycket komplext kombinatoriskt optimeringsproblem. Att lösa UTRP och hitta effektivare kollektivtrafiklinjer kan leda till stora besparingar samt lägre genomsnittliga restider för passagerare. Den vanligaste metoden för att lösa problemet, inom litteraturen, är med en metaheuristisk algoritm. Syftet med detta examensarbete är att lösa UTRP med en sådan algoritm samt att göra algoritmen effektiv. Den multiobjektiva diskreta Cuckoo Search (MODCS) algoritmen blev introducerad för att uppnå syftet, och den löste UTRP med avseende på både passagerar- och operatörintressen. Två olika nätverk har lösts: Mandls nätverk som är det vanligaste att jämföra med, och Södertäljes bussnätverk. Resultaten för Mandls nätverk blev jämförda med resultaten av andra algoritmer i litteraturen. MODCS algoritmen hittade linjenät med mycket bra värden för passagerarintresset, men inte lika bra för operatörintresset. Beräkningstiden för MODCS var högre än för de andra algoritmerna. För Södertäljes bussnätverk så hittade MODCS algoritmen linjenät som hade mycket bättre objektiva värden än en algoritm från ett tidigare examensarbete. De genomsnittliga beräkningstiderna var dessutom mycket lägre för MODCS än för algoritmen från det tidigare examensarbetet.

The main goal of a scheduling process is to decide when and how to execute each of the project's activities. Despite large variety of researched scheduling problems, the majority of them can be described as generalisations of the resource-constrained project scheduling problem (RCPSP). Because of wide applicability and challenging difficulty, RCPSP has attracted vast amount of attention in the research community and great variety of heuristics have been adapted for solving it. Even though these heuristics are structurally different and operate according to diverse principles, they are designed to obtain only one solution at a time. In the recent researches on RCPSPs, it was proven that these kind of problems have complex multimodal fitness landscapes, which are characterised by a wide solution search spaces and presence of multiple local and global optima. The main goal of this thesis is twofold. Firstly, it presents a variation of the RCPSP that considers optimisation of projects in an uncertain environment where resources are modelled to adapt to their environment and, as the result of this, improve their efficiency. Secondly, modification of a novel evolutionary computation method Cuckoo Search (CS) is proposed, which has been adapted for solving combinatorial optimisation problems and modified to obtain multiple solutions. To test the proposed methodology, two sets of experiments are carried out. Firstly, the developed algorithm is applied to a real-life software development project. Secondly, the performance of the algorithm is tested on universal benchmark instances for scheduling problems which were modified to take into account specifics of the proposed optimisation model. The results of both experiments demonstrate that the proposed methodology achieves competitive level of performance and is capable of finding multiple global solutions, as well as prove its applicability in real-life projects.

Obligate brood parasites rely solely on other species, the hosts, to incubate their eggs and raise their offspring, which often reduces the host’s reproductive output. This reproductive cost has led to the evolution of anti-parasite adaptations among hosts, which in turn, has led to better trickery by parasites, a process termed an evolutionary arms race. The objective of this thesis was to investigate host-parasite coevolutionary arms races to address questions of host-use diversity. Host diversity varies dramatically among brood-parasitic species, but reasons for variations in host-use among brood parasites are not well understood. In Chapter 2, I address questions on host diversity specifically, whereas I address questions about coevolutionary interaction between hosts and parasites in Chapters 3, 4 and 5 using two host-parasite systems, one in New Zealand and one in North America. Chapter 2 investigates if host diversity is constrained by aggressive nest defence behaviour. I compared the nest defence behaviour of the exclusive host of the shining cuckoo Chrysococcyx lucidus lucidus on the main islands of New Zealand, the grey warbler Gerygone igata, to two other potentially suitable hosts that are not currently parasitised, the fantail Rhipidura fuliginosa and the silvereye Zosterops lateralis. The results suggest that grey warblers are as aggressive as fantails and silvereyes towards shining cuckoos at the nest and thus, host specialisation in shining cuckoos in New Zealand, at least, does not appear to be the result of nest-defence constraints imposed by potential but unused host species. Chapter 3 investigates if red-winged blackbirds Agelaius phoeniceus, a species that typically accepts the eggs of parasites, recognises, as indicated by changes in incubation behaviour, when they have been parasitised by brown-headed cowbirds Molothrus ater. Recognition without rejection suggests that rejection may be context-dependent but the results suggest that red-winged blackbirds do not recognise when their nests have been parasitised by brown-headed cowbirds, at least at the egg stage. This study was the first to investigate if hosts that almost invariably accept the eggs of parasites recognise when they have been parasitised. Chapter 4 investigated the possibility of coevolutionary arms races occurring through olfactory channels in contrast to earlier work that focussed only on visual and auditory cues. Recent research has revealed that olfactory abilities in birds are more common than previously thought. Uropygial gland secretions are posited to be a key source of avian body odour and its composition has been found to vary among species and individuals as well as between the sexes. I compared gas-chromatography (GC-FID) traces of shining cuckoo preen wax to the GC-FID traces of the grey warbler, the only host of the shining cuckoo in mainland New Zealand, as well as the preen wax of seven other species for evidence of mimicry. Preliminary results suggest there is evidence for mimicry and the potential for odour-based nestling discrimination in grey warblers. Further tests recording the response of grey warblers to odour-manipulated nestlings are necessary. Finally, in Chapter 5, I investigated the response of the song thrush Turdus philomelos, a species that rejects the eggs of the common cuckoo Cuculus canorus and conspecifics at intermediate and low frequencies, respectively, to nest-odour manipulations using the preen wax of conspecifics and heterospecifics. The results suggest song thrush do not use odour to assess the risk of parasitism at least as indicated in terms of changes in incubation behaviour. Investigations of the role of olfaction in avian brood parasite systems can provide a better understanding of brood-parasite coevolution. Only by considering all channels of communication can we be sure to completely understand the coevolutionary dynamics between brood parasites and their hosts.