Anastasia Pagnoni

Securing uniqueness of rights e-documents: a deontic process perspective

We typically think of documents as carrying information. However, certain kinds of documents do more than that: they are not only informative but also performative in that they represent rights. When these documents are in paper form or some other physical medium, holding the document indicates holding the right. Since the document represents a right, a hazard is that by duplicating the document, one may fraudulently claim a new right. For this reason, physical documents that represent rights are both tamper resistant and copy resistant. However, problems arise when such performative documents are converted to electronic form: duplicates are bit for bit perfect and undetectable. Thus, the normal heuristic of uniqueness of the document token as representing the uniqueness of the right no longer holds for performative electronic documents. This is especially challenging when the rights are transferable, as with various financial instruments such as stocks and bonds. This paper presents an analysis, based on deontic logic, about the necessary requirements for electronic documents and their corresponding electronic procedures in order to guarantee the uniqueness of rights and prevention of fraud. A design is sketched, based on a notion we call digital parchment, which offers improved flexibility.

Secure electronic bills of lading: blind counts and digital signatures

Electronic documents used in the framework of the goods delivery industry—i.e. electronic bills of lading (e-BOLs)—are the enablers of any payment, and therefore exposed to frauds. As of today, e-BOLs are handled by special private companies, which provide paperless trading services through their trade chains. This paper contributes a zero-knowledge open solution to the problem of designing secure electronic bills of lading, in the framework of a shipper-carrier-buyer transmission model. The suggested solution is a cryptographic protocol based on digital signatures and blind merchandise counts—that is, counts that do not reveal any information about actually counted quantities. The model is designed to mitigate a number of security threats and assumes the existence of both a trusted third party and a bank in charge of payment procedures. The paper discusses the drawbacks of the existing proprietary solutions and shows how the suggested open protocol addresses them.

Stochastic Nets and Performance Evaluation

This paper is an introduction to the so-called stochastic Petri nets. It contains a critical overview of the most representative stochastic Petri net classes (Stochastic Petri Nets, both in Florin-Natkin and in Molloy form, Generalized Stochastic Petri Nets, Extended Stochastic Petri Nets). Their application to performance evaluation is discussed. A bibliograhy for furthering the subject is given in the appendix.

Error-correcting Petri nets

The paper introduces error-correcting Petri nets, an algebraic methodology for designing synthetic biologic systems with monitoring capabilities. Linear error-correcting codes are used to extend the net’s structure in a way that allows for the algebraic detection and correction of non-reachable net markings. The presented methodology is based on modulo-p Hamming codes—which are optimal for the modulo-p correction of single errors—but also works with any other linear error-correcting code.

Profiling network attacks via AIS

The paper extends the intrusion detection methodology proposed by Tarakanov et al. in [8] to k-dimensional shape spaces, for k greater or equal 2. k real vectors, representing antibodies, are used to recognize malicious (or, non-self) connection logs. We suggest a method for recognizing antigens (generating such antibodies) via Singular Value Decomposition of a real-valued matrix obtained by preprocessing a database of connection logs [9]. New incoming connection requests are recognized by the antibodies as either self (normal request), or non-self (potential attack), by (a) mapping them into a k-dimensional shape space, and (b) evaluating the minimum Hamming distance between their image and that of a known attack logs. It is easy to see that using a shape space of dimension greater than 2 significantly reduces false positives.