Metaverse Security and Privacy Threats

We must be aware of metaverse security and privacy threats as our lives become further integrated into the metaverse and take safety precautions just as we would in the physical world. Furthermore, from a development perspective, privacy invasions and security breaches threaten further expansion and implementation of the metaverse. Knowing these metaverse security and privacy issues helps keep both end users and developers secure in this new frontier.

Metaverse security and privacy threats and issues

Metaverse Security and Privacy Threats and Issues

Common metaverse security and privacy threats are categorized below as follows: identity, data, privacy, network, economy, governance, and physical/social effects.

Identity-related threats

  1. Identity theft
    When a user’s identity is stolen, their digital assets, avatars, social relationships, and digital life can be leaked in a more destructive fashion than we see in traditional identity theft. Hackers can seize personal information through phishing e-mails, hacked devices, and customer data to then commit fraud within the metaverse itself with the user’s own avatar.
  2. Impersonation attack
    This tactic occurs when the attacker pretends to be an authorized user so they may gain entry to the metaverse’s services. Attackers may impersonate endpoints to insert rogue devices into Bluetooth pairings. Hackers can also invade helmets and other wearable devices and use them as entry points to impersonate the user and their credentials.
  3. Identity linkability in Ternary Worlds
    Ternary (three) worlds represent the physical, digital, and human worlds. All three are integrated into the metaverse, allowing an attacker to track users and determine their positions in the real world. Hackers may also track users through compromised headsets and other wearable devices.
  4. Trusted and Interoperable Authentication
    Fast and safe cross-platform and cross-domain authentication built on platforms such as Blockchain is crucial defense against identity-related threats.

Data-related threats

Data collected or created by users, IoT devices, or avatars is at risk for exploits including availability, confidentiality, false data injection, integrity, and UGC ownership/provenance tracing.

  1. Data Tampering Attack
    Integrity features monitor any modification during data communication across the ternary worlds and sub-metaverses. Attackers can forge, modify, remove and replace that data to interfere with physical entities, users, and their avatars. These attackers can remain undetected by falsifying log files or message-digest results.
  2. False Data Injection Attack
    False data injection involves the injection of falsified information such as messages and instructions to mislead metaverse systems. For example, attackers can generate biased AI models by injecting adversary training samples (centralized) or poisoned gradients (decentralized) during training.
  3. Threats to Data Quality of UGC and Physical Input
    User generated content (UGC) utility such as data quality can be compromised by users generating low quality content to save costs. They can share unaligned non-IID data during the content recommendation model’s training process. Uncalibrated wearable sensors can also create inaccurate data to mislead digital twin creation.
  4. Threats to UGC Ownership and Provenance
    The metaverse is an open and autonomous space with no centralized authority. Therefore, it is difficult to trace ownership and provenance of UGCs produced by many avatars across all sub-metaverses and turn them into protected assets.

Privacy Threats

A user’s location, habit, lifestyle, and more can be offended during the data service’s lifecycle. This includes data perception, transmission, processing, governance, or storage.

  1. Pervasive Data Collection
    Facial expressions, eye/hand movement, speech, biometric features, and brain wave patterns are all profiled in a user’s avatar creation. Motion sensors and four built-in cameras in the Oculus headset, for example, can track our environment and can be exploited by attackers.
  2. Privacy Leakage in Data Transmission
    Sensitive user data collected by XR data such as headsets are transferred through wired and wireless communication. Although this sensitive data is encrypted, attackers can still access the raw data through eavesdropping through different channels. Differential attacks and advanced inference attacks are used to track a user’s location.
  3. Privacy Leakage in Data Processing
    The aggregation and processing of data from users and their environments is necessary for avatar creation and rendering and this data can be leaked. Private data belonging to different users may violate regulations such as the General Data Protection Regulation (GDPR). Attackers can also infer a user’s privacy and preferences from published processing results (avatars).
  4. Privacy Leakage in Cloud/Edge Storage
    Storage of sensitive information from users in cloud servers or edge devices raise privacy disclosure issues. Hackers can determine users’ privacy information by frequent queries by differential attacks, or compromise cloud storage as a whole through DDoS attacks.
  5. Unauthorized Data Access
    Different service providers across the sub-metaverses need to access real time user activity in order to deliver seamless personalized services such as avatar creation. Malicious service providers can illegally elevate their data access rights using buffer overflow and tampering access across control lists.
  6. Misuse of User/Avatar Data
    During the data-service lifecycle, user data can be intentionally revealed by hackers or unintentionally revealed by service providers to assist user profiling and precision marketing activities.
  7. Threats to Digital Footprints
    Digital footprints consist of preferences, habits, and activities of avatars that can reflect the end user in the real world. Attackers can use these footprints to exploit real world users. Users can also be stalked without their knowledge thanks to the wide third-person view typically used in the metaverse, and their user preferences can later be used in social engineering attacks.
  8. Threats to Accountability
    Since XR devices gather much more data than traditional smart devices, the metaverse must be accountable for meeting privacy compliance. However, the audit process of the compliance of privacy regulations (such as the GDPR) is inefficient under the centralized service offering architecture. They also cannot ensure transparency of regulation compliance during the data management life-cycle.

Network-Related Threats

Traditional threats still exist in the metaverse, as it is still utilizing the current internet and and existing wireless technologies. The most common threats include SPoF, DDoS, and Sybil attacks.

  1. SPoF
    Centralized architecture like the cloud-based system used in metaverse creation is convenient and cost saving. However, it can be vulnerable to Single Point of Failure (SPoF) by damage to physical root servers or DDoS attacks. It also makes free exchange of tokens or virtual currency difficult across different worlds.
  2. DDoS
    Hackers can exploit IoT botnets made up of many IoT devices to conduct distributed denial-of-service (DDoS) attacks. By overwhelming the centralized server with massive amounts of traffic, they can cause service unavailability and network outages.
  3. Sybil Attacks
    Sybil adversaries manipulate many stolen identities to gain disproportionately large influence on metaverse services such as reputation and voting-based services. These attacks compromise system effectiveness.

Economy-related Threats

Service trust, digital asset ownership, and economic fairness in the metaverse is at risk for various risks outlined below.

  1. Service Trust Issues in Virtual Object Trading
    Inherent fraud risks such as repudiation and refusal to pay during virtual object trading can result in inherent distrust within the metaverse marketplace. Through the creation of digital objects through digital twin, the metaverse must guarantee the authenticity and trustworthiness of the deployed digital copies.
  2. Threats to Digital Asset Ownership
    Lack of central authority in addition to complex circulation and ownership forms make the generation, pricing, trusted trading, and ownership traceability of digital assets in the trading economy difficult. This includes both collective ownership and shared ownership.
  3. Threats to Economic Fairness in Creator Economy
    Well-designed incentives promote efficiency and fairness in resource sharing and digital asset trading in the creator economy. Three factors put this fairness at risk:
    a. Strategic users/avatars can manipulate the digital market to break the supply and demand status to make enormous profits.
    b. Free-riding users/avatars unfairly gain revenue and utilize metaverse services without contributing anything themselves, subsequently risking the sustainability of the creator economy.
    c. Collusive users/avatars may collude with each other or a service provider to manipulate the market and make a profit.

Threats to Physical World and Human Society

The metaverse is an extension of the cyber-physical-social system (CPSS), where physical systems, human society, and cyber systems are interconnected. Therefore, metaverse security and privacy threats in the digital world cross over into personal safety, physical infrastructure, and human society.

  1. Threats to Personal Safety
    Hackers can attack wearable devices and indoor sensors such as cameras to observe the routine and physical position of users to orchestrate robberies. They can also display frightening content to the end user which may cause physical harm.
  2. Threats to Infrastructure Safety
    Hackers can sniff software or system vulnerabilities and then exploit compromised devices as entry points to invade national infrastructures such as the power grid or high-speed rail through Advanced Persistent Threat (APT) attacks.
  3. Social Effects
    User addiction, rumor prevention, biased outcomes, and simulated facts are all inherent threats in this emerging technology. Similar to the Matrix films, the metaverse is controlled by AI algorithms where the code is the ultimate law. Subsequently, ethical issues such as racial and gender bias may occur.

Governance-Related Threats

Just like social norms in the real world, content creation, data processing, and the virtual economy should reflect digital norms and regulations. However, the following metaverse security and privacy threats can threaten system efficiency and security.

  1. Misbehaving Regulators
    Rogue regulators can cause system paralysis, and their supervisors must also be observed. Dynamic punishment/reward mechanisms should be utilized to punish these regulators and reward their law-abiding counterparts. Punishment and reward standards should be maintained by a majority of avatars in a decentralized and democratic manner to maintain sustainability.
  2. Threats to Collaborative Governance
    Collaborative governance under a hierarchical or flat mode is best for large-scale metaverse maintenance in order to avoid the concentration of regulation rights. Rogue regulators can still undermine this system by, for example, partitioning a specific regulator from the network using wormhole attacks.
  3. Threats to Digital Forensics
    Digital forensics is defined as the virtual reconstruction of cyber crimes by identifying, extracting, fusing, and analyzing evidence from both the real and virtual worlds. However, the dynamics and interoperability issues across worlds makes efficient forensic investigation difficult. Additionally, the real and digital world can be frequently blurred such as through emerging innovations such as deepfake technology.

Metaverse Security Certification

If you are interested to learn more about metaverse security and privacy issues, consider joining the Metaverse Security Center community at Identity Management Institute and apply to become a Certified Metaverse Security Consultant (CMSC)™.