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Security in Industrial Communications
Published in Richard Zurawski, Industrial Communication Technology Handbook, 2017
Since the whole protocol stack of LonWorks is implemented in hard- and firmware within a dedicated microprocessor, security measures have to be implemented above layer 7. In this case, the system still fully complies with the LonWorks standard although interoperability is confined to secured nodes by defining special user-defined structures. If an attacker has appropriate tools and physical access, nodes are not well protected. Properties of a node from simple configuration properties to the whole application and data storage can be read and often changed with common administration tools. Some kind of security token must, therefore, be introduced that securely stores the secret keys and can execute cryptographic operations in a secure manner.
A hierarchical structure model of success factors for (blockchain-based) crowdfunding
Published in Massimo Ragnedda, Giuseppe Destefanis, Blockchain and Web 3.0, 2019
Felix Hartmann, Xiaofeng Wang, Maria Ilaria Lunesu
Share of retained equity/tokens: The study by Ahlers et al. (2015) finds that retaining equity can be an effective signal to increase the likelihood of funding success. In other studies on equity retention and social network theory in equity crowdfunding, Vismara et al. (2016) and Ralcheva and Roosenboom (2016) come to the same result. This effect could be linked to the cost of retained equity if the business collapses and the potential increase in value if the project is successful. Founders who are convinced that the business will be successful will be more likely to retain as much equity as possible. Interestingly, in the blockchain-based crowdfunding space, the studies by Lee et al. (2018) and Amsden and Schweizer (2018) find that the same pattern is also true for ICOs. Projects that retain more tokens seem to be more successful. Lee et al. (2018) argue that “retaining more tokens could be an important governance indicator, the percent of tokens to be sold to investors measures management’s skin in the firm” and that the result could be linked to former studies on the positive effects of signalling equity retention. It seems that investors are attracted by projects with a higher retention rate. Retaining a higher fraction of tokens could be seen as a signal of the founder’s confidence in the project. Selling only a fraction of the tokens gives projects the possibility to sell unsold tokens in future financing rounds; this is comparable to seasoned equity offerings (SEOs) that are used by publicly traded companies. Nevertheless, in the case of most token sales, the tokens are not connected to any shareholder rights such as governance. The managers normally remain in full control over the company. In fact, this could change with the new trend of security token offerings such as ETOs which are bound by more prompt investor protection.
Towards a role-based authentication system based on SSVEP-P300 hybrid brain–computer interfacing
Published in Behaviour & Information Technology, 2022
Nikhil Rathi, Rajesh Singla, Sheela Tiwari
Conventional methods of user authentication have been around for many decades that can be categorised into three main groups: knowledge-based (e.g. passwords and PIN), object-based (e.g. smart cards and tokens) and biometric-based (e.g. fingerprint, iris, voice, etc.) (Al-Assam, Sellahewa, and Jassim 2011). The knowledge-based authentication technique is based on the verification of information known to the person seeking permission, such as a PIN or password. Further, users often use simple passwords (such as mobile numbers or names, etc.) that are easy to remember. Therefore, they are vulnerable to several types of attacks, such as off-line dictionary attacks, brute force attacks, and shoulder surfing (Pham et al. 2014). Security tokens and smart cards are the physical devices that the registered individual must have to gain authorised access to electronically restricted resources or network services. The tokens require special readers and can suffer from duplicity, stealing hacking, or damaging issues (Rathi, Singla, and Tiwari 2020). The biometric-based system relies on the uniqueness of an individual’s physical/behavioural attributes, such as fingerprint, facial features, retina scans and voice (Lozoya-Santos et al. 2019). The biometric system acquires a biometric key (e.g. fingerprints, faces, irises, palm prints, etc.) from an individual, extracts a feature set, stores it and compares it with the stored database for accessing the system. If the two feature sets are matching, the system could recognise the individual; otherwise, the system will reject the individual (Jain, Ross, and Prabhakar 2004). But each authentication method has its limitations. Users often create a short password that is easy to remember but these passwords are very predictable and easy to guess, a token can be stolen or duplicate, and an impostor can gain unauthorised access while biometrics such as fingerprints can be mimicked or a biometric template can be replaced by an impostor’s template in a database. Hence, these methods could be useful in lower-level security but for a higher-level; a more secure system is required. Recently, the research communities successfully explore the potential of using brain signals measured with an electroencephalogram (EEG) as a new type of biometrics in user authentication. The key benefit of using brain signals as an authentication identifier is that it is fraud-resistant because it is impossible to replicate the brain activity of any subject without his/her consent (Bassett and Gazzaniga 2011). Hence, it can be used as a suitable solution for high-level security. Also, EEG-based authentication system verifies the user’s identity from physical or behavioural characteristics. Therefore, researchers have focused on exploring how brains function, discovering biomarkers and developing brain signal-based applications commonly known as a brain–computer interface (BCIs) (Chan et al. 2018).