Computer viruses generally require a host program. The virus writes its own code into the host program. When the program runs, the written virus program is executed first, causing infection and damage. A computer worm does not need a host program, as it is an independent program or code chunk. Therefore, it is not restricted by the host program, but can run independently and actively carry out attacks.
The first academic work on the theory of self-replicating computer programs was done in 1949 by John von Neumann who gave lectures at the University of Illinois about the "Theory and Organization of Complicated Automata". The work of von Neumann was later published as the "Theory of self-reproducing automata". In his essay von Neumann described how a computer program could be designed to reproduce itself. Von Neumann's design for a self-reproducing computer program is considered the world's first computer virus, and he is considered to be the theoretical "father" of computer virology. In 1972, Veith Risak directly building on von Neumann's work on self-replication, published his article "Selbstreproduzierende Automaten mit minimaler Informationsübertragung" (Self-reproducing automata with minimal information exchange). The article describes a fully functional virus written in assembler programming language for a SIEMENS 4004/35 computer system. In 1980 Jürgen Kraus wrote his diplom thesis "Selbstreproduktion bei Programmen" (Self-reproduction of programs) at the University of Dortmund. In his work Kraus postulated that computer programs can behave in a way similar to biological viruses.
A computer virus generally contains three parts: the infection mechanism, which finds and infects new files, the trigger, which determines when to activate the payload, and the payload, which is the malicious code to execute.
Most modern antivirus programs try to find virus-patterns inside ordinary programs by scanning them for so-called virus signatures. Different antivirus programs will employ different search methods when identifying viruses. If a virus scanner finds such a pattern in a file, it will perform other checks to make sure that it has found the virus, and not merely a coincidental sequence in an innocent file, before it notifies the user that the file is infected. The user can then delete, or (in some cases) "clean" or "heal" the infected file. Some viruses employ techniques that make detection by means of signatures difficult but probably not impossible. These viruses modify their code on each infection. That is, each infected file contains a different variant of the virus.
One method of evading signature detection is to use simple encryption to encipher (encode) the body of the virus, leaving only the encryption module and a static cryptographic key in cleartext which does not change from one infection to the next. In this case, the virus consists of a small decrypting module and an encrypted copy of the virus code. If the virus is encrypted with a different key for each infected file, the only part of the virus that remains constant is the decrypting module, which would (for example) be appended to the end. In this case, a virus scanner cannot directly detect the virus using signatures, but it can still detect the decrypting module, which still makes indirect detection of the virus possible. Since these would be symmetric keys, stored on the infected host, it is entirely possible to decrypt the final virus, but this is probably not required, since self-modifying code is such a rarity that finding some may be reason enough for virus scanners to at least "flag" the file as suspicious. An old but compact way will be the use of arithmetic operation like addition or subtraction and the use of logical conditions such as XORing, where each byte in a virus is with a constant so that the exclusive-or operation had only to be repeated for decryption. It is suspicious for a code to modify itself, so the code to do the encryption/decryption may be part of the signature in many virus definitions. A simpler older approach did not use a key, where the encryption consisted only of operations with no parameters, like incrementing and decrementing, bitwise rotation, arithmetic negation, and logical NOT. Some viruses, called polymorphic viruses, will employ a means of encryption inside an executable in which the virus is encrypted under certain events, such as the virus scanner being disabled for updates or the computer being rebooted. This is called cryptovirology.
Within a few days, cybersecurity experts had mostly contained the spread of the virus and restored the functionality of their networks, although it took some time to remove the infections entirely. Along with its investigative role, the FBI sent out warnings about the virus and its effects, helping to alert the public and reduce the destructive impacts of the attack. Still, the collective damage was enormous: an estimated $80 million for the cleanup and repair of affected computer systems.
The deadly coronavirus continues to spread across the globe, and mathematical models can be used to show suspected, recovered, and deceased coronavirus patients, as well as how many people have been tested. Researchers still do not know definitively whether surviving a COVID-19 infection means you gain long-lasting immunity and, if so, for how long? In order to understand, we think that this study may lead to better guessing the spread of this pandemic in future. We develop a mathematical model to present the dynamical behavior of COVID-19 infection by incorporating isolation class. First, the formulation of model is proposed; then, positivity of the model is discussed. The local stability and global stability of proposed model are presented, which depended on the basic reproductive. For the numerical solution of the proposed model, the nonstandard finite difference (NSFD) scheme and Runge-Kutta fourth order method are used. Finally, some graphical results are presented. Our findings show that human to human contact is the potential cause of outbreaks of COVID-19. Therefore, isolation of the infected human overall can reduce the risk of future COVID-19 spread.
Mathematical models are useful to understand the behavior of an infection when it enters a community and investigate under which conditions it will be wiped out or continued. Currently, COVID-19 is of great concern to researches, governments, and all people because of the high rate of the infection spread and the significant number of deaths that occurred. In December 2019, coronavirus first reported in Wuhan, China, is an infectious disease caused by a newly discovered coronavirus. The virus that causes COVID-19 is mainly transmitted through droplets generated when an infected person coughs, sneezes, or exhales. These droplets are too heavy to hang in the air and quickly fall on floors or surfaces. Coronavirus-confirmed cases reached nearly four million in 187 countries, and approximately 295,000 people have lost their lives due to this virus.
A computer virus is malicious code that replicates by copying itself to another program, computer boot sector or document and changes how a computer works. A virus spreads between systems after some type of human intervention. Viruses replicate by creating their own files on an infected system, attaching themselves to a legitimate program, infecting a computer's boot process or infecting user documents. The virus requires someone to knowingly or unknowingly spread the infection. In contrast, a computer worm is standalone programming that does not require human interaction to spread. Viruses and worms are two examples of malware, a broad category that includes any type of malicious code.
There are several best practices users can follow to protect their computers from worms. Following these steps will not only decrease the risk of infection, but also provide for easier detection and computer worm removal.
Users should be familiar with the symptoms of a computer worm so that they can quickly recognize infections and begin the process of computer worm removal. Here are some of the typical symptoms of a computer worm: 2b1af7f3a8