In computer security applications, a honeypot is a trap set on a network to dete

Question

In computer security applications, a honeypot is a trap set on a network to detect and counteract computer hackers. Honeypot data are studied in Kimou et al. (2010) using Markov chains. The authors obtained honeypot data from a central database and observed attacks against four computer ports – 80, 135, 139, and 445 – over 1 year. The ports are the states of a Markov chain along with a state corresponding to no port is attacked.

Let (Xn) n=0 be a SDTMC where Xn represents the port attacked with S = {80, 135, 139, 445, No attack}.

Weekly data are monitored, and the port most often attacked during the week is recorded. The estimated Markov transition matrix for weekly attacks is:

with initial distribution = (0, 0, 0, 0, 1).

1) Write a Python 3 code, that will be estimating the probability each port is attacked after 100 weeks. Be sure to include the following in your code:

a) Simulate 100 weeks of attacks, and repeat the simulation 5,000 times. Compute the probability that each port is attacked after 100 weeks. Use the print function to print your answers.

b) Create a bar graph to show the probability of attacks at each port after 100 weeks. Be sure to title your graph and label the axes.

Explanation / Answer

Running a honeypot is not without its risks, however. That's because the overwhelming number of compromised systems are used for attacking other systems. If you ignore a vulnerable system, you may be liable if hackers use your system to break into others. It's called downstream liability, and it brings us to the topic of honeynets.

A honeynet is a honeypot with added technology that properly records the hacker's actions while simultaneously minimizing or eliminating the risks to others on the Internet. An example is a honeypot that's set up behind a backward firewall; instead of preventing incoming connections, the firewall prevents the honeypot from initiating outbound connections. Still, while that approach makes the honeypot incapable of damaging other systems, it also makes it pretty easy for bad guys to spot. Realizing they've broken into a presumably booby-trapped system, the typical hacker is likely to wipe the disk clean and never return (which is not tremendously informative for the honeypot watchers).

For the past four years, Lance Spitzer and the others at the Honeynet Project have been working to create, deploy, manage and analyze the results of honeynets. Their technology is clever, but their results incredibly disturbing. To solve the problem of downstream liability, Spitzer and his team developed a range of data control techniquesfor example, an adaptive firewall rule that allows five or 10 outgoing connections every hour: That's high enough to prevent an attacker from getting suspicious, but low enough to prevent serious damage to third-party systems. These rules can be implemented on commercial firewall systems like those from Check Point Software Technologies or on firewalls built from Linux and OpenBSD systems. Of course, no data control technique is perfect. "The more you allow a blackhat to do outbound, the more you can learn, but the greater the risk," according to the project's website.

Data capture is another technical challenge in running a honeypot. By recording every packet in and out of the system, the honeypot watchers can get a good idea of what the bad guys are doing. The log files on the honeypot itself are also a good data source. The log files are easily deleted by the attacker, so it's common to have the honeypot send a copy of its log to a remote syslog server that's on the same network but is better defended. (Be sure to watch the log server as well. If it is penetrated by your attacker using a novel attack, then your honeypot will certainly have shown its worth.)

The task of data capture has been considerably complicated in recent years by the increased use of encryption in the blackhat community. Back in the 1990s, most bad guys logged in to their compromised systems using clear text-protocols such as telnet and rsh. Today they've followed the advice of numerous computer security professionals and have turned to cryptographic protocols like ssh to make their communications immune to network monitoring. Honeynet's response to encryption is to modify the target computer's operating system so that all keystrokes, transferred files and other information are logged to yet another monitoring system. Because the attacker might discover such logs, the project uses steganographic techniqueshiding keystrokes inside NetBIOS broadcast packets, for example. It's a clever idea. (Unfortunately, it's only a matter of time before the bad guys adapt those techniques to their own nefarious ends.)

One of the nice things about honeypot systems is that they do a great job at data reduction. With a typical website or mail server, attacks are usually drowned out by the legitimate traffic. Adding an intrusion detection system rarely helps because of the tendency of these systems to generate false alarms. Honeypots, on the other hand, have little or no legitimate traffic. Most of the data in or out is, by definition, an attack. As a result, it is much easier to look at the data and find out what the attacker actually did.

Since its formation in 1999, the Honeynet Project has gathered a tremendous amount of information that you can find at www.honeynet.org or in Spitzer's 2002 book, Honeypots: Tracking Hackers. Some of the findings: The incidence of attack has doubled in the past year; attackers are increasingly using automated point-and-shoot tools with pluggable exploits (making tools easy to update as new vulnerabilities are discovered); and, despite their bravado, few hackers use novel attacks.

Honeypots are primarily a research tool, but they have genuine business applications as well. Put a honeypot on an IP address adjacent to your company's Web or mail server, and you'll get an idea of the attacks to which it is subject. But don't give the adjacent machine a name with your domain name serverafter all, most attacks are done by IP address. You'll get even better intelligence if the honeypot uses the same operating system, patch level and application suite as the machine you're trying to protect. In fact, make it an exact copy and then monitor all the traffic in and out of this honeypot machine. If it gets compromised, you'll know what to look for on your production machine.

To be sure, honeypots and honeynets are not "fire and forget" security appliances, a point that Spitzer repeatedly stresses. According to the Honeynet Project, it typically takes between 30 hours and 40 hours of analysis to really understand the damage that an attacker can do in just 30 minutes. The systems also require diligent maintenance and testing. With a honeypot, you constantly match your wits against the bad guys'. You get to choose the battlefield, but your opponent gets to choose the time of the battle.

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