#neurosecurity

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The Neural Forensic Siphon (Brain-to-Bit): Unmasking the 2026 Cognitive Hijack

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The Neural Forensic Siphon (Brain-to-Bit): Unmasking the 2026 Cognitive Hijack

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App Stores for the Brain: Privacy & Security in Brain-Computer Interfaces

Abstract — An increasing number of Brain-Computer Interfaces (BCIs) are being developed in medical and nonmedical fields, including marketing, gaming and entertainment industries. BCI enabled technology carries a great potential to improve and enhance the quality of human lives. It provides people suffering from severe neuromuscular disorders with a way to interact with the external environment. It also enables a more personalized user experience in gaming and entertainment.

These BCI applications are, however, not without risk. Established engineering practices set guarantees on performance, reliability and physical safety of BCIs. But no guarantees or standards are currently in place regarding user privacy and security. In this paper, we identify privacy and security issues arising from possible misuse or inappropriate use of BCIs. In particular, we explore how current and emerging non-invasive BCI platforms can be used to extract private information, and we suggest an interdisciplinary approach to mitigating this problem. We then propose a tool to prevent this side-channel extraction of users’ private information. This is a first step towards making BCI-enabled technologies secure and privacy preserving.

Excerpts

IV. PRIVACY AND SECURITY ISSUES IN NEURAL ENGINEERING

B. Neurosecurity

In 2009, Denning et al. [21] recognized that “the use of standard engineering practices, medical trials, and neuroethical evaluations during the design process can create systems that are safe and that follow ethical guidelines; unfortunately, none of these disciplines currently ensure that neural devices are robust against adversarial entities trying to exploit these devices to alter, block, or eavesdrop on neural signals”. Potential security threats that can be mounted against implanted neural devices were identified, and the term “neurosecurity” was introduced as “the protection of the confidentiality, integrity, and availability of neural devices from malicious parties with the goal of preserving the safety of a person’s neural mechanisms, neural computation, and free will” [21].

C. Brain Spyware - BCI-enabled Malicious Application

At the 2012 USENIX Security Symposium, Martinovic et al. [31] presented the first malicious software designed to detect a user’s private information using a BCI. They referred to is as the “brain spyware”. The authors used a commercially available BCI to present users with visual stimuli and record their EEG neural signals. They focused on the P300 response, and analyzed the recorded signals in order to detect users’: (a) 4-digit PINs, (b) bank information, (c) months of birth, (d) locations of residence, and (e) if they recognized the presented set of faces.

While the authors of [31] have focused only on the P300 response, it is not hard to imagine brain spyware applications being developed to extract private information about users’ memories, prejudices and beliefs, but also about their possible neurophysiological disorders. Currently, there does not seem to exist a way to resist these attacks. Moreover, recent results [28] show that attempts at willful deception can themselves be detected from an individual’s neural signals. Going a step further, the same authors [28] show that non-invasive brain stimulators, emitting imperceptible DC electrical currents, can be used to make a user’s responses noticeably slower when attempting to lie.

Thus, there is a growing need to address the potential privacy and security risks arising from the use of BCIs, in both medical and non-medical applications. As a first step, we are exploring which components of the EEG signal can be used to infer private information about a user, and quantifying the amount of exposed information.

V. THREAT MODEL

Consider an example model of an attacker who uses BCIs to extract private information about users. We assume this will involve non-invasive BCI devices, mostly intended for consumer use. Manufacturers of non-invasive EEG-based BCIs generally distribute software development kits and guides with their products, as well as technical support. Their intention is to promote application development, but such “open-development” platforms may compromise user privacy and security, since there is currently no review process, standards and guidelines in place to protect users, nor technical protection to restrict inappropriate or malicious BCI use.

As depicted in Figure 1, a typical BCI system consists of three main components: (R1) an acquisition system, (R2) an application, and (R34) a signal processing system, where the signal processing system consists of (R3) feature extraction and (R4) decoding (translation) algorithm components. The existing BCI open-development platforms typically grant every application developer full control over all four of these components. For the discussion of this paper, we will assume an attacker has an access to all of these resources (R1)–(R4). We next consider how an attacker uses these resources to develop malicious applications.

A. Types of Attackers 

In Figure 2, two types of attackers are shown (as described in the caption). We distinguish between these types based on the way an attacker analyzes recorded neural signals. The first type of an attacker extracts users’ private information by hijacking the legitimate components of a BCI system. Such an attacker exploits for malicious purposes those feature extraction and decoding algorithms that are intended for the legitimate BCI applications. The second type of an attacker extracts users’ private information by adding or replacing the legitimate BCI components. Such an attacker implements additional feature extraction and decoding algorithms, and either replaces or supplements the existing BCI components with the additional malicious code. As can be observed from the Figure, the difference between the two attacker types is only in the structure of the “brain malware” component.

B. Methods of Extracting Private Information

We consider scenarios where an attacker interacts with users by presenting them with specific sets of stimuli, and recording their responses to the presented stimuli. In the current literature, there are several well-established methods of presenting stimuli to users:

• Oddball paradigm - a technique where users are asked to react to specific stimuli, referred to as target stimuli, hidden as rare occurrences in a sequence of more common, non-target stimuli [23].

• Guilty knowledge test - a technique based on the hypothesis that a familiar stimulus evokes a different response when viewed in the context of similar, but unfamiliar items [44].

• Priming - a technique that uses an implicit memory effect where one stimulus may have an influence on a person’s response to a later stimulus [39].

We assume an attacker can use any of these methods to facilitate extraction of private information. In addition, an attacker can present malicious stimuli in an overt (conscious) fashion, as well as in a subliminal (unconscious) way, with subliminal stimulation defined as the process of affecting people by visual or audio stimuli of which they are completely unaware [15]. Ways of achieve unawareness typically include reducing a stimulus intensity or duration below the required level of conscious awareness.

C. Examples of “Brain Malware” Information Misuse

Private information about BCIs users, extracted using “brain malware”, may be of interest to multiple parties, those using it for greater good and potential improvement of the quality of humans lives, but also to those using it to increase their own (financial) gains, as well as those using it simply to harm others. One can easily imagine the following examples of concerning BCIs use:

Example 1: As exemplified in Farahaney’s work [22], an access to an individual’s memories and emotional responses might be used by police enforcement and government agencies during criminal investigation, as well as for crime and terrorism prevention.

Example 2: BCI-recorded neural signals may be used in a variety of entertainment and relaxation applications. A person’s emotional response and satisfaction/annoyment level may, for example, be used to provide better (more accurate) music and/or movie recommendations. Similarly, information about a person’s activity and anxiety levels may be used to tailor a more personalized training routine or a relaxation session.

Example 3: Personal information, extracted from neural signals, could also be used for targeted advertisement, where in addition to (or instead of) information about a person’s activities on the Internet, an advertiser/retailer would have a realtime access to a person’s level of interest, satisfaction, or frustration with the presented material.

Example 4: On the other end of the spectrum, however, the extracted information about a person’s memories, prejudices, beliefs or possible disorders could be used to manipulate a person or coerce her/him into doing something.

Example 5: Finally, the extracted neural information could also be used to cause physical or emotional harm to a person. Examples of such actions have already been observed in the literature. Denning et al. [21], presented the case of individuals who placed flashing animations on epilepsy support webpages, eliciting seizures in some patients with photosensitive epilepsy.

VI. THE NEED FOR A COORDINATED PREVENTION APPROACH

Issues arising from misuse or inappropriate use of BCI technology most likely do not pose a critical concern yet, considering their limited use outside of research communities. However, existing and emerging privacy and security threats may be viewed as an attack on human rights to privacy and dignity [13]. Thus, they deserve immediate attention and careful consideration. We suggest that methods to prevent and mitigate BCI-enabled privacy and security threats must be developed now, in the early design phase. Doing so will allows us to keep up with Privacy-by-Design [1] values, as well as with general values of privacy-enhancing technologies.

We view the development of prevention and mitigation tools as an interdisciplinary effort, involving neuroscientists, neural engineers, ethicists, as well as legal, security and privacy experts. The first step of this interdisciplinary approach should be an open discussion, aimed at answering the following questions: (i) Who all should be allowed an access to individuals’ neural signals? (ii) Which components of these neural signals should those entities have an access to? (iii) How noisy, distorted or distilled should these components be made before making them available? (iv) Which purposes are the entities allowed to use the neural signals for? and (v) What are the risks associated with the misuse of the provided components, i.e., what amount of private information can be extracted from the provided components?

We expect the answers to questions (i)–(v) will lead to a “triangle” approach towards enhancing privacy and security of BCI technology. On one vertex of the triangle, we expect to have legal experts and ethicists, defining a set of laws and policies to govern legal use of neural signals. As an example of possible legal intervention, the law could examine should the BCI platforms indeed be immunized for the apps they sell, or is some other balance between manufacturers and application developers more appropriate for BCI technologies.

On the second vertex, we expect to have a group of neuroscientists and engineers, in charge of developing and establishing a set of industry and research standards, methods, processes and practices for secure and privacy-preserving BCI systems. One such practice may, for example, require there to exist a centralized authority in charge of reviewing and validating every BCI application before allowing its use in general population. Finally, at the third vertex we expect BCI systems manufacturers and application developers, developing, implementing and using engineering practice, methods and tools, in order to prevent and mitigate specific classes of security and privacy attacks. Clearly the IEEE, and its standards process, could have a role here.

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BONACI, T., CALO, R., & CHIZECK, H. J. (2014). App stores for the brain: Privacy & Security in Brain-Computer Interfaces. 1-7. 

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Consciousness Studies: The Emerging Military-Industrial-Spiritual-Scientific Complex

Abstract

Consciousness studies is not just an academic field, it is an industry as well with active research programs in medicine, business, and the military. As advancements in technology offer more access to the brain, attempts to instrumentalize the resulting knowledge will shift the very definitions of consciousness. Consciousness of this process is a necessary first condition toward keeping consciousness studies from becoming merely a form of social and individual control. Understanding consciousness studies and such important guiding metaphors as information, and dynamics such as power, is an essential part of this process.

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Many observers are arguing that there is now a convergence of human enhancement technologies and a little blizzard of acronyms has arisen to list them: GRIN (genetic, robotic, information, nano process), NBIC (nanotechnology, biological engineering, information technology, cognitive engineering, GRAIN (genetics, robotics, artificial intelligence, nanotechnology), and GNR (genetics, nanotechnology, robotics) (Garreau 2005:316). The exact mix isn’t important; it is the same technoscientific forces that are driving the Perpetual Revolution in Military Affairs that has been transforming war for the last half century (Gray 2005). What is clear is that these are potent technologies and as such are an integral part of this participatory hyper-co-evolution.

So then, at the end of the day, the question is about power: Who shapes this evolutionary process and why ? Already, in our intensely mediated culture, it often feels like there is a consciousness war going on, a war of many fronts — right and left, buyers and sellers, rich and poor, male and female, Coke and Pepsi, traditional and progressive. Images, ideas, and words bombard us from all sides as we make our way through our day. The examples early in this essay were meant to show this struggle over consciousness is about money and war and fame and values, it is about power. It is about the health of the planet and the health of democracies. David Barash argues this power of consciousness to model (understand and therefore predict and perhaps manipulate) the behavior of others could be related to how conscious you are, and so it is . . .

. . . . possible that the more conscious you are, the more accurate your theory of mind, since cognitive modelers should be more effective if they know, cognitively and self-consciously, not only what they are modeling but that they are doing so. [Barash 2006:B10]

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Jonathan Moreno argues that we should think in terms of Neurosecurity as a way of making public a discussion that is already happening within the military. As he points out, “it would be naive to suppose that national-security organizations are not monitoring developments in that field.” Although, as his own work shows, military agencies such as DARPA are actually funding developments in the field, not just monitoring them (Moreno 2006a:B7). He also recommends a set of questions for anyone doing “neuroscience” (by which he means instrumentalist consciousness studies) that are good for anyone doing consciousness studies to ask:

How do the sources of research funds affect the direction of science and social change? Which uses of brain research are acceptable, and which are not? And what limits should society, perhaps acting through scientific associations, place on the acceptable applications of neuroscience?” [Moreno 2006a:B7]

Good questions, but they really only represent a beginning. Perhaps the model used in the Human Genome Project, where 3.5% of all funds went to studying the social implications of the technoscientific work, should be expanded to cover other fields that are transforming society, including those enabling instrumentalist consciousness studies. When a perfectly accurate lie detector test is developed, as will happen soon, will we have any idea at all of the possible consequences? What does it mean that we are faced with a military-industrial- whatever? It is what we should expect; it is the start of an analysis, not any kind of ending.

GRAY, C. H. (2007). Consciousness Studies: The Emerging Military-Industrial-Spiritual-Scientific Complex. Anthropology of Consciousness. 18, 3-19.

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Researchers Find 'Mind-Control' Gaming Headsets Can Leak Users' Secrets

Friday August 17, @09:29AM - from the and-whatever-you-do,-don't-touch-the-reverse-button dept.

"At the Usenix security conference in Seattle last week, a group of researchers from the University of California at Berkeley, Oxford University and the University of Geneva presented a study that hints at the darker side of a future where we control computers with our minds rather than a mouse. In a study of 28 subjects wearing brain-machine interface headsets built by companies like Neurosky and Emotiv and marketed to consumers for gaming and attention exercises, the researchers found they were able to extract hints directly from the electrical signals of the test subjects' brains that partially revealed private information like the location of their homes, faces they recognized and even sequences of numbers they recognized. For the moment, the experimental theft of users' private information from brain signals is more science fiction than a real security vulnerability, since it requires tricking the victim into thinking about the target information at a certain time, and still doesn't work reliably. (Though much better than random chance.) But as BMI gets more sophisticated and mainstream, the researchers say their study should serve as a warning about privacy issues around the technology of such interfaces."

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Related :

Hacking the brain for fun and profit

Researchers Hack Brainwaves to Reveal PINs, Other Personal Data

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Neurosecurity has been defined as "a version of computer science security principles and methods applied to neural engineering," or more fully, as "the protection of the confidentiality, integrity, and availability of neural devices from malicious parties with the goal of preserving the safety of a person’s neural mechanisms, neural computation, and free will.

Wikipedia