ELECTRONIC COMMERCE SECURITY IN THE CONTEXT OF THE MEANS OF PAYMENT DEMATERIALIZATION

Some items regarding electronic commerce, electronic vulnerabilities, electronic means of payment, digital money and electronic micropayments are presented below. Then is presented a method of assessing the quality of applications and e-commerce Web sites. This method is then adapted from the operational point of view, developed and implemented in the study of the electronic micropayment systems’ security, in the purpose of analyzing and evaluating their security in the context of the means of payment dematerialization.e-commerce, micropayment, security, encryption, digital economy, EWAM

Roadmap on optical security

Postprint (author's final draft

Conditionals in Homomorphic Encryption and Machine Learning Applications

Homomorphic encryption aims at allowing computations on encrypted data without decryption other than that of the final result. This could provide an elegant solution to the issue of privacy preservation in data-based applications, such as those using machine learning, but several open issues hamper this plan. In this work we assess the possibility for homomorphic encryption to fully implement its program without relying on other techniques, such as multiparty computation (SMPC), which may be impossible in many use cases (for instance due to the high level of communication required). We proceed in two steps: i) on the basis of the structured program theorem (Bohm-Jacopini theorem) we identify the relevant minimal set of operations homomorphic encryption must be able to perform to implement any algorithm; and ii) we analyse the possibility to solve -- and propose an implementation for -- the most fundamentally relevant issue as it emerges from our analysis, that is, the implementation of conditionals (requiring comparison and selection/jump operations). We show how this issue clashes with the fundamental requirements of homomorphic encryption and could represent a drawback for its use as a complete solution for privacy preservation in data-based applications, in particular machine learning ones. Our approach for comparisons is novel and entirely embedded in homomorphic encryption, while previous studies relied on other techniques, such as SMPC, demanding high level of communication among parties, and decryption of intermediate results from data-owners. Our protocol is also provably safe (sharing the same safety as the homomorphic encryption schemes), differently from other techniques such as Order-Preserving/Revealing-Encryption (OPE/ORE).Comment: 14 pages, 1 figure, corrected typos, added introductory pedagogical section on polynomial approximatio

The Birth of a New Industry: Entry by Start-ups and the Drivers of Firm Growth. The Case of Encryption Software

The paper analyses the birth of the Encryption Software Industry (ESI), a new niche in the software industry. Using a Chandlerian perspective, this work reports the main facts about firm entry and growth, with a particular focus on start-up strategies and actions. Since scale economies do not play a major role in ESI, the paper investigates the different sources of firm competitive advantages. This work shows that innovation and product differentiation, along with investments in co-specialised assets, are variables strongly correlated to young firm probability to survive and grow. In so doing, we have collected highly detailed information on product introduction, US patents granted, worldwide alliances and biographical data of firm founders.Entry, Entrepreneurship, Innovation, Software.