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Library: Artificial intelligence and evolution
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Anti anti-viruses, anti-debugging (22)
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Anti-virus programs (7)
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Analysis of the particular viruses (71)
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Artificial intelligence and evolution@
Anti-virus technology (24)
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Anti-virus general (76)
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Collecting and Trading (3)
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Cryptography and Cryptovirology (10)
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MS-DOS specific (42)
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Computer Epidemiology (10)
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Fiction (13)
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Good viruses and worms (8)
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Interviews with VXers and AVers (64)
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Information warfare (5)
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Computer Immunology (8)
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History (44)
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Laws (18)
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Macro and script viruses (69)
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Metamorphism (15)
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Different OS's - MacOS, MenuetOS, ... (3)
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Trojans, Hoaxes, Hypes, Spyware (4)
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Theory, models and definitions (36)
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Polymorphism (24)
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Predictions, Prognosis, Trends... (12)
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Scene, Psychological, Ethical, Cultural and Social aspects (105)
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Self-reproduction (3)
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UNIX and clones specific (30)
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Virus technology (55)
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Virus general (24)
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Computer worms (21)
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Windows specific (51)
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Rootkits (2)
Paul-Michael Agapow
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Computational Brittleness and Evolution in Machine Language» (
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26.07Kb 6612 hitsComplexity International (1996) 3 (1996)Traditionally, computer machine languages have been regarded as inappropriate for evolutionary activity. This is due largely to the perception that machine language is computationally brittle (that is, working programs are a small fraction of the total of all possible programs and therefore a random change to a functional program will almost certainly render it non-functional). This assumes, however, that legitimate program sequences are dissimilar to each other and that "brittleness" does not exist in biological evolutionary systems. The first assumption was tested by checking for homology between legitimite program sequences at the machine level. A surprising degree of similarity was discovered, vastly above what would be expected if legitimate code sequences were only randomly related. The second assumption was examined via available data on protein mutations and composition. Although robust in some aspects, terrestrial biology also demonstrates significant brittleness. The difference in brittleness between computational and terrestrial systems therefore ceases to be a qualitative gap and becomes quantitative, albeit perhaps a large one. In light of the findings, some intriguing possibilities are examined. The evolution "in the wild" of computer viruses is considered and it is concluded that while evolution de novo is still unlikely, viable mutation of one virus strain to new species is possible. This explains a number of mutant viruses that have been discovered. Also considered is evolutionary computation using machine language as a possible optimisation tool, as is the significance of brittleness in evolutionary systems.
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Computer Viruses: the Inevitability of Evolution?»
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29.11Kb 4377 hitsFirst National Complexity Conference, Australian National University, Canberra, December 1992 (1992)In recent years computer viruses have received much attention although their theoretical aspects have been neglected. One such aspect is the possibility of viruses as life, with the attendant characteristics of terrestrial life forms including evolution. Where this particular idea has been previously considered, it has been judged highly improbable. The author disagrees and argues that viral evolution may not only be possible but inevitable. After an introduction to the biology of computer viruses evidence of viral evolution will be presented as well as examples of how current and future trends in computing could lead to the emergence of sophisticated and novel entities. Finally the author speculates on the consequences of this.
BlueOwl
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Implementing genetic algorithms in virusses»
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12.7Kb 3866 hitsReady Rangers Liberation Front [5] (2004)I have personally always been fascinated by evolution and am a strong believer that it is the truth about how organisms evolve. I have also spend many thoughts and codes and readings trying to figure out if it could also be implemented in computer virusses, of course something completely different.Normally computer virusses either don't change them selves (static), they encrypt themselves with one or multiple decryptors or they completely change their body (hard to do). With the second and the third way virusses try to completely change their layout / code use / register use etc. This theory will try to prove that another way could be better.In this theory I mainly describe how a fileinfecting virus could use genetics. This can however be applied to any spreading program including worms, as long as you can be creative.
John Croall
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Computer viruses (BMJ 302-66e)» (
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2.23Kb 3902 hitsBritish Medical Journal, vol. 297, p.488 (1988)Dr John Asbury points out that "a computer virus is a small piece of computer code which has been maliciously inserted on computer storage media" (23 July, p 246). Although this is true in most cases, there remains the possibility that some of these viruses have "evolved" out of random mutations ofcomputer programs.
John Croall, Ian McKay
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Computer viruses (BMJ 299-66a)»
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2.41Kb 3662 hitsBritish Medical Journal, vol. 297, pp.981-982 (1988)Dr Patrick J R Harkin (10 September, p 688) doubts the hypothesis described by one of us (JC) (13 August, p 488) that computer viruses may evolve (and may already have evolved) by random substitution and cumulative selection from preexisting pieces of software.
Patrick Harkin
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Computer viruses (BMJ 307-59e)»
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2.75Kb 3895 hitsBritish Medical Journal, vol. 297, p.688 (1988)Computer viruses have recently become a popular topic for discussion (23 July, p 246; 6 August, p 432; 13 August, p 488), but I have not yet seen a full description in a medical journal of the many forms ofdestructive computer software, other than viruses, which also exist.
Dimitris Iliopoulos, Christoph Adami, Péter Ször
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Darwin inside the machines: Malware evolution and the consequences for computer security»
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41.7Kb 4695 hitsVB2008, pp.187-194 (2008)Recent advances in anti-malware technologies have steered the security industry away from maintaining vast signature databases and into newer defence technologies such as behaviour blocking, application whitelisting and others. Most would agree that the reasoning behind this is to keep up with the arms race established between malware writers and the security community almost three decades ago. Still, malware writers have not as yet created new paradigms. Indeed, malicious code development is still largely limited to code pattern changes utilizing polymorphic and metamorphic engines, as well as executable packer and wrapper technologies. Each new malware instance retains the exact same core functionality as its ancestor and only alters the way it looks. What if, instead, malware were able to change its function or behaviour autonomously? What if, in the absence of human intervention, computer viruses resembled biological viruses in their ability to adapt to new defence technologies as soon as they came into effect? In this paper, we will provide the theoretical proof behind malware implementation that closely models Darwinian evolution.Biological viruses are under constant attack by immune systems and artificial drugs. Yet they systematically manage to evolve new functionalities that circumvent such countermeasures, leading to recurrent epidemics. According to the biological analogy, evolvable malware will be able to alter its functionality by autonomously incorporating behaviours freely available to it by the numerous discoverable APIs. The new behaviour profiles would constantly be screened by security software in the same way natural selection acts on biological organisms. In the end, the malware instances that are better equipped to survive counlermeasures will be able to proliferate more efficiently. Such malware poses a real threat to the current methods of detection due to the vast numbers of functions it can adopt, and that cannot possibly be screened for. Furthermore, it is likely that clean-program functionality will be favoured amongst such behaviours since it shields malware that is mimicking clean programs from behaviour blocking. As a consequence, we predict that behaviour-based virus detection would quickly become ineffective if malware can evolve based on the Darwinian paradigm.
J. S. Bach
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Artificial intelligence and viruses» (
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18.27Kb 5803 hitsCodeBreakers [4] (1998)Many people think that virus writers are lamers who have nothing better to do then waste their time writing useless and dangerous software that does not benefit the software society. There are some people who think of computer viruses as completely useless and some that think of them as just a nuisance. My objective here is to rebut the ones who think computer viruses are useless, drawing some analogues from biology. Granted, the analogies will be very crude, but i will try to make my point clear. Naturally, there is no comparison in importance between real biological viruses and computer viruses, and i am not a "proponent" of the spreading of any kind, particularly in view of the tremendous damage and suffering that some biological viruses have caused to humans (see HIV, etc). However some interesting analogies can be drawn, which when put in proper perspective, can help one understand the very process of life itself.
Mark Ludwig
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Computer Viruses, Artificial Life and Evolution»
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573.34Kb 24040 hitsAmerican Eagle Publications, Inc. (1993)Eric Olson
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Computer-Generated Life» (
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31.12Kb 5846 hitsArtificial Life 3: 29-39, 1997 (1997)Dr. Frankenstein, in Mary Shelley's novel, created a living human being in his laboratory. Impressive though this accomplishment may have been, though, Frankenstein's monster was made from materials that were already living, or nearly so, before they came into his hands. His "creation" of life was little more than an elaborate bit of surgery and resuscitation. It would be of greater philosophical interest if someone could create a living organism out of non-biological materials - out of simple organic molecules of the sort that were present on the young earth, for example, or out of wholly inorganic chemicals, or even out of nuts and bolts and wires. This would truly be a case of artificial life
saec
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Evolutionary Virus Propogation Technique» (
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9.86Kb 5408 hitsElectrical Ordered Freedom EOF-DR-RRLF (2008)Hey! First article, kind of a mix between a tutorial + idea, it shows the implementation of a propagation technique. These techniques are used in biology and also Artificial Intelligence. The virus evolves, you can say the species learns because generally only fit entities will survive.I want to apologise for any mistakes I have made, and any short sighted errors. Also, sorry for the language, I'm writing many reports for school and the "I'm so smart I can excrete through my mouth" attitude they like to see in reports sometimes leaks, I should look for a plumber but I don't wish to find a cock ;)
Eugene Spafford
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Computer Viruses as Artificial Life» (
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55.29Kb 10900 hits (1994)There has been considerable interest in computer viruses since they first appeared in 1981, and especially in the past few years as they have reached epidemic numbers in many per-sonal computer environments. Viruses have been written about as a security problem, as asocial problem, and as a possible means of performing useful tasks in a distributed computing environment.However, only recently have some scientists begun to ask if computer viruses are not a form of artificial life - a self-replicating organism. Simply because computer viruses do not existas organic molecules may not be sufficient reason to dismiss the classification of this form of "vandalware" as a form of life.This paper begins with a description of how computer viruses operate and their history, and of the various ways computer viruses are structured. It then examines how viruses meetproperties associated with life as defined by some researchers in the area of artificial life and self-organizing systems. The paper concludes with some comments directed towards the definitionof artificially "alive" systems and experimentation.
SPTH
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Code Evolution: Follow nature's example»
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17.58Kb 7890 hitsReady Rangers Liberation Front [6] (2005)This article describes an idea about how the evolution of computer code could look like. First I have to say that I got this idea while I was on a real strange party with some punks. I was pretty drunken by wiskey and really stoned (no shit). I could not really think, so I took out a paper and noted my idea. The next day I read the paper and thought that this could really work. Well, I still think that this idea could work, so go on reading about the idea!
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Imitation of Life: Advanced system for native Artificial Evolution»
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42.06Kb 1226 hitsValhalla #1 (2011)A model for artificial evolution in native x86 Windows systems has been developed at the end of 2010. In this text, further improvements and additional analogies to natural microbiologic processes are presented. Several experiments indicate the capability of the system - and raise the question of possible countermeasures.
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Taking the redpill: Artificial Evolution in native x86 systems»
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41.93Kb 15532 hits (2010)First, three successful environments for artificial evolution in computer systems are analysed briefly. The organism in these enviroment are in a virtual machine with special chemistries. Two key-features are found to be very robust under mutations: Non-direct addressing and separation of instruction and argument.In contrast, the x86 instruction set is very brittle under mutations, thus not able to achieve evolution directly. However, by making use of a special meta-language, these two key-features can be realized in a x86 system. This meta-language and its implementation is presented in chapter 2.First experiments show very promising behaviour of the population. A statistically analyse of these population is done in chapter 3. One key-result has been found by comparison of the robustness of x86 instruction set and the meta-language: A statistical analyse of mutation densities shows that the meta-language is much more robust under mutations than the x86 instruction set.In the end, some Open Questions are stated which should be addressed in further researches. An detailed explanation of how to run the experiment is given in the Appendix.
Harold Thimbleby, Ian Witten, David Pullinger
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Concepts of cooperation in artificial life»
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41.9Kb 5184 hits (1998)We have built some simple, but useful, cooperative Artificial Life agents. Based on this experience and by contrasting our work with computer viruses, we argue that Artificial Life (the simulation of life including evolution) can only remain reliably and indefinitely cooperative if it adheres to explicitly-specified social conventions. Breaking or neglecting these conventions results in systems that are worse than useless; in fact, malicious with respect to human social values.
ValleZ
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Genetic programming in virus» (
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15.67Kb 4107 hits29a [7] (2004)I wanna comment here some ideas i have had. They are only ideas...these ideas seems very beautiful however this seems fiction more than reality.
Tom Van Braeckel
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Introduction to Randomly Evolving Machinecode»
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28.49Kb 4017 hits (2001)REM stands for Randomly Evolving Machinecode. REM is a program which replicates by copying itself, randomly changing one or more bytes in every offspring. After replicating, REM runs the offsprings, which should start replicating too. When an offspring is not able to replicate, it extincts.
Claus Wilke, Christoph Adami
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The biology of digital organisms» (
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37.34Kb 5512 hitsTrends in Ecology & Evolution, Vol.17, No.11, pp. 528-532 (2002)Digital organisms are self-replicating computer programs that mutate and evolve. They can be thought of as a domesticated form of computer virus that lives in, and adapts to,a controlled environment.Digital organisms provide a unique opportunity with which to study evolutionary biology in a form of life that shares no ancestry with carbon-based life forms,and hence to distinguish general principles of evolution from historical accidents that are particular to biochemical life.In terms of the complexity of their evolutionary dynamics,digital organisms can be compared with biochemical viruses and bacteria.Recent studies of digital organisms have addressed long-term evolutionary adaptation and the growth of complexity in evolving systems,patterns of epistatic interactions in various genetic backgrounds,and quasi-species dynamics.
16 authors, 19 titles