We live in a world that demands more and more connectivity. Our everyday life is dominated by an overwhelming amount of information that needs to be controlled and maintained. Everyday transactions that few years ago required our physical existence, have been replaced by electronic applications. Users may now use friendly, fast and safe interfaces to perform easily numerous tasks, varying from money transfers using the web and remote health checks to e-learning and e-commerce. Being exposed in an unprecedented number of threats and frauds, safe connectivity for all network-based systems has now become a predicate necessity. The science of cryptography provides the necessary tools and means towards this direction. Cryptographic hardware and software play now a dominant role in e-commerce, mobile phone communications, military applications, private emails, digital signatures for e-commerce, ATM cards, web banking, maintenance of health records and so on. This doctoral thesis approaches the problem of designing versatile architectures for cryptographic hardware. By the term versatile we define hardware architectures capable of supporting a variety of arithmetic operations and algorithms useful in cryptography, with no need to reconfigure the internal interconnections of the integrated circuit. I owe my deepest gratitude to my supervisor, Professor Thanos Stouraitis, for his excellent guidance throughout the 8 years of my Ph.D. studies. I consider myself more than lucky to have collaborated with him in the development of this doctoral thesis. I would like to gratefully thank him not only as a supervisor, but also as a friend. Thanos stood for me as a real source of inspiration, an example of out-of-the-box thinking, a paradigm of devotion and faith to hard work. This thesis would not have been possible without his exemplary support and his continuous and close supervision. During all those years, I had the opportunity to collaborate with several remarkable people, who influenced my work and provided me with invaluable help in my research. I am grateful to my friends Dr. Athanasios Kakarountas, and Dr. Charalampos Michail for the collaboration and cooperation during the first years of my Ph.D. studies. The roots of this thesis share a lot of common thoughts and efforts. I would also like to thank Mrs. Fotopoulou Eleni and Mr. Ferentinos Aris for our collaboration and all the fun moments we had in the Digital Signal & Image Processing Lab. Furthermore, I owe my deepest gratitude to my co-supervisors Prof. Odysseas Koufopavlou and Prof. Christos Zaroliagis, for the valuable comments, guidance and support during the preparation of this dissertation. Last, but not least, my family and friends deserve my deepest gratitude for their support and belief in me throughout those 8 years. I sincerely believe that this work would not have been as successful without them.