Low power predictable memory and processing architectures

Great demand in power optimized devices shows promising economic potential and draws lots of attention in industry and research area. Due to the continuously shrinking CMOS process, not only dynamic power but also static power has emerged as a big concern in power reduction. Other than power optimization, average-case power estimation is quite significant for power budget allocation but also challenging in terms of time and effort. In this thesis, we will introduce a methodology to support modular quantitative analysis in order to estimate average power of circuits, on the basis of two concepts named Random Bag Preserving and Linear Compositionality. It can shorten simulation time and sustain high accuracy, resulting in increasing the feasibility of power estimation of big systems. For power saving, firstly, we take advantages of the low power characteristic of adiabatic logic and asynchronous logic to achieve ultra-low dynamic and static power. We will propose two memory cells, which could run in adiabatic and non-adiabatic mode. About 90% dynamic power can be saved in adiabatic mode when compared to other up-to-date designs. About 90% leakage power is saved. Secondly, a novel logic, named Asynchronous Charge Sharing Logic (ACSL), will be introduced. The realization of completion detection is simplified considerably. Not just the power reduction improvement, ACSL brings another promising feature in average power estimation called data-independency where this characteristic would make power estimation effortless and be meaningful for modular quantitative average case analysis. Finally, a new asynchronous Arithmetic Logic Unit (ALU) with a ripple carry adder implemented using the logically reversible/bidirectional characteristic exhibiting ultra-low power dissipation with sub-threshold region operating point will be presented. The proposed adder is able to operate multi-functionally.

Profiling side-channel attacks on cryptographic algorithms

Traditionally, attacks on cryptographic algorithms looked for mathematical weaknesses in the underlying structure of a cipher. Side-channel attacks, however, look to extract secret key information based on the leakage from the device on which the cipher is implemented, be it smart-card, microprocessor, dedicated hardware or personal computer. Attacks based on the power consumption, electromagnetic emanations and execution time have all been practically demonstrated on a range of devices to reveal partial secret-key information from which the full key can be reconstructed. The focus of this thesis is power analysis, more specifically a class of attacks known as profiling attacks. These attacks assume a potential attacker has access to, or can control, an identical device to that which is under attack, which allows him to profile the power consumption of operations or data flow during encryption. This assumes a stronger adversary than traditional non-profiling attacks such as differential or correlation power analysis, however the ability to model a device allows templates to be used post-profiling to extract key information from many different target devices using the power consumption of very few encryptions. This allows an adversary to overcome protocols intended to prevent secret key recovery by restricting the number of available traces. In this thesis a detailed investigation of template attacks is conducted, along with how the selection of various attack parameters practically affect the efficiency of the secret key recovery, as well as examining the underlying assumption of profiling attacks in that the power consumption of one device can be used to extract secret keys from another. Trace only attacks, where the corresponding plaintext or ciphertext data is unavailable, are then investigated against both symmetric and asymmetric algorithms with the goal of key recovery from a single trace. This allows an adversary to bypass many of the currently proposed countermeasures, particularly in the asymmetric domain. An investigation into machine-learning methods for side-channel analysis as an alternative to template or stochastic methods is also conducted, with support vector machines, logistic regression and neural networks investigated from a side-channel viewpoint. Both binary and multi-class classification attack scenarios are examined in order to explore the relative strengths of each algorithm. Finally these machine-learning based alternatives are empirically compared with template attacks, with their respective merits examined with regards to attack efficiency.

A river of memory: landscape, narrative and identity in the Lee Valley, Co. Cork, Ireland

In moments of rapid social changes, as has been witnessed in Ireland in the last decade, the conditions through which people engage with their localities though memory, individually and collectively, remains an important cultural issue with key implications for questions of heritage, preservation and civic identity. In recent decades, cultural geographers have argued that landscape is more than just a view or a static text of something symbolic. The emphasis seems to be on landscape as a dynamic cultural process – an ever-evolving process being constructed and re-constructed. Hence, landscape seems to be a highly complex term that carries many different meanings. Material, form, relationships or actions have different meanings in different settings. Drawing upon recent and continuing scholarly debates in cultural landscapes and collective memory, this thesis sets out to examine the generation of collective memory and how it is employed as a cultural tool in the production of memory in the landscape. More specifically, the research considers the relationships between landscape and memory, investigating the ways in which places are produced, appropriated, experienced, sensed, acknowledged, imagined, yearned for, appropriated, re-appropriated, contested and identified with. A polyvocal-bricoleur approach aims to get below the surface of a cultural landscape, inject historical research and temporal depth into cultural landscape studies and instil a genuine sense of inclusivity of a wide variety of voices (role of monuments and rituals and voices of people) from the past and present. The polyvocal-bricoleur approach inspires a mixed method methodology approach to fieldsites through archival research, fieldwork and filmed interviews. Using a mixture of mini-vignettes of place narratives in the River Lee valley in the south of Ireland, the thesis explores a number of questions on the fluid nature of narrative in representing the story and role of the landscape in memory-making. The case studies in the Lee Valley are harnessed to investigate the role of the above questions/ themes/ debates in the act of memory making at sites ranging from an Irish War of Independence memorial to the River Lee’s hydroelectric scheme to the valley’s key religious pilgrimage site. The thesis investigates the idea that that the process of landscape extends not only across space but also across time – that the concept of historical continuity and the individual and collective human engagement and experience of this continuity are central to the processes of remembering on the landscape. In addition the thesis debates the idea that the production of landscape is conditioned by several social frames of memory – that individuals remember according to several social frames that give emphasis to different aspects of the reality of human experience. The thesis also reflects on how the process of landscape is represented by those who re-produce its narratives in various media.