The Use of Deception Techniques : Honeypots and Decoys

Honeypots and similar sorts of decoys represent only the most rudimentary uses of deception in protection of information systems. But because of their relative popularity and cultural interest, they have gained substantial attention in the research and commercial communities. In this paper we will introduce honeypots and similar sorts of decoys, discuss their historical use in defense of information systems, and describe some of their uses today. We will then go into a bit of the theory behind deceptions, discuss their limitations, and put them in the greater context of information protection. 1. Background and History Honeypots and other sorts of decoys are systems or components intended to cause malicious actors to attack the wrong targets. Along the way, they produce potentially useful information for defenders. 1.1 Deception fundamentals According to the American Heritage Dictionary of the English Language (1981): "deception" is defined as "the act of deceit" "deceit" is defined as "deception". Fundamentally, deception is about exploiting errors in cognitive systems for advantage. History shows that deception is achieved by systematically inducing and suppressing signals entering the target cognitive system. There have been many approaches to the identification of cognitive errors and methods for their exploitation, and some of these will be explored here. For more thorough coverage, see [68]. Honeypots and decoys achieve this by presenting targets that appear to be useful targets for attackers. To quote Jesus Torres, who worked on honeypots as part of his graduate degree at the Naval Postgradua te School: “For a honeypot to work, it needs to have some honey” Honeypots work by providing something that appears to be desirable to the attacker. The attacker, in searching for the honey of interest, comes across the honeypot, and starts to taste of its wares. If they are appealing enough, the attacker spends significant time and effort getting at the honey provided. If the attacker has finite resources, the time spent going after the honeypot is time not spent going after other things the honeypot is intended to protect. If the attacker uses tools and techniques in attacking the honeypot, some aspects of those tools and techniques are revealed to the defender in the attack on the honeypot. Decoys, like the chaff used to cause information systems used in missiles to go after the wrong objective, induce some signals into the cognitive system of their target (the missile) that, if successful, causes the missile to go after the chaff instead of their real objective. While some readers might be confused for a moment about the relevance of military operations to normal civilian use of deceptions, this example is particularly useful because it shows how information systems are used to deceive other information systems and it is an example in which only the induction of signals is applied. Of course in tactical situations, the real object of the missile attack may also take other actions to suppress its own signals, and this makes the analogy even better suited for this use. Honeypots and decoys only induce signals, they do not suppress them. While other deceptions that suppress signals may be used in concert with honeypots and decoys, the remainder of this paper will focus on signal induction as a deceptive technique and shy away from signal suppression and combinations of signal suppression and induction. 1.2 Historical Deceptions Since long before 800 B.C. when Sun Tzu wrote "The Art of War"  deception has been key to success in warfare. Similarly, information protection as a field of study has been around for at least 4,000 years [41]. And long before humans documented the use of deceptions, even before humans existed, deception was common in nature. Just as baboons beat their chests, so did early humans, and of course who has not seen the films of Khrushchev at the United Nations beating his shoe on the table and stating “We will bury you!”. While this article is about deceptions involving computer systems, understanding cognitive issues in deception is fundamental to understanding any deception.  Many authors have examined facets of deception from both an experiential and cognitive perspective. Chuck Whitlock has built a large part of his career on identifying and demonst rating these sorts of deceptions.  His book includes detailed descriptions and examples of scores of common street deceptions. Fay Faron points out that most such confidence efforts are carried as as specific 'plays' and details the anatomy of a 'con' [30]. Bob Fellows [13] takes a detailed approach to how 'magic' and similar techniques exploit human fallibility and cognitive limits to deceive people. Thomas Gilovich  provides indepth analysis of human reasoning fallibility by presenting evidence from psychological studies that demonst rate a number of human reasoning mechanisms resulting in erroneous conclusions.  West [32] describes the steps in psychological and social distortion of information and provides detailed support for cognitive limits leading to deception. Al Seckel [15] provides about 100 excellent examples of various optical illusions, many of which work regardless of the knowledge of the observer, and some of which are defeated after the observer sees them only once. Donald D. Hoffman [36] expands this into a detailed examination of visual intelligence and how the brain processes visual information. It is particularly noteworthy that the visual cortex consumes a great deal of the total human brain space and that it has a great deal of effect on cognition. Deutsch [47] provides a series of demons trations of interpreta tion and misinterpretation of audio information. First Karrass  then Cialdini [34] have provided excellent summaries of negotiation strategies and the use of influence to gain advantage. Both also explain how to defend against influence tactics. Cialdini [34] provides a simple structure for influence and asserts that much of the effect of influence techniques is built in and occurs below the conscious level for most people. Robertson and Powers  have worked out a more detailed lowlevel theoretical model of cognition based on "Perceptual Control Theory" (PCT), but extensions to higher levels of cognition have been highly speculative to date. They define a set of levels of cognition in terms of their order in the control system, but beyond the lowest few levels they have inadequate basis for asserting that these are orders of complexity in the classic control theoretical sense. Their higher level analysis results have also not been shown to be realistic representations of human behaviors. David Lambert  provides an extensive collection of examples of deceptions and deceptive techniques mapped into a cognitive model intended for modeling deception in military situations. These are categorized into cognitive levels in Lambert's cognitive model. Charles Handy [37] discusses organizational structures and behaviors and the roles of power and influence within organizations. The National Research Council (NRC) [38] discusses models of human and organizational behavior and how automation has been applied in this area. The NRC report includes scores of examples of modeling techniques and details of simulation implementa tions based on those models and their applicability to current and future needs. Greene [46] describes the 48 laws of power and, along the way, demonst rates 48 methods that exert compliance forces in an organization. These can be traced to cognitive influences and mapped out using models like Lambert 's, Cialdini's, and the one we describe later in this paper. Closely related to the subject of deception is the work done by the CIA on the MKULTRA project.  A good summary of some of the pre1990 results on psychological aspects of self deception is provided in Heuer's CIA book on the psychology of intelligence analysis.  Heuer goes one step further in trying to start assessing ways to counter deception, and concludes that intelligence analysts can make improvements in their presentation and analysis process. Several other papers on deception detection have been written and substantially summarized in Vrij's book on the subject.[50] All of these books and papers are summarized in more detail in “A Framework for Deception”  which provides much of the basis for the historical issues in this paper as well as other related issues in deception not limited to honeypots, decoys, and signal induction deceptions. In addition, most of the computer deception background presented next is derived from this paper.  The most common example of a computer security mechanism based on deception is the response to attempted logins on most modern computer systems. When a user first attempts to access a system, they are asked for a user identification (UID) and password. Regardless of whether the cause of a failed access attempt was the result of a nonexistent UID or an invalid password for that UID, a failed attempt is met with the same message. In text based access methods, the UID is typically requested first and, even if no such UID exists in the system, a password is requested. Clearly, in such systems, the computer can identify that no such UID exists without asking for a password. And yet these systems intentionally suppress the information that no such UID exist and induce a message designed to indicate that the UID does exist. In earlier systems where this was not done, attackers exploited the result so as to gain additional information about which UIDs were on the system and this dramatically reduced their difficulty in attack. This is a very widely accepted practice, and when presented as a deception, many people who otherwise object to deceptions in computer systems indicate that this somehow doesn’t count as a d