Data In The Internet of Things era: the propertization of data in light of contemporary business practices

Data is at the heart of the digital age or, as some put it, “the new oil”, “the next natural resource” and the “currency of the 21st century” that everything depends on to function and operate. The Internet of Things (IoT), which aims to connect things to the Internet and interconnect them with each other, could have a huge impact on data generation and dissemination as there will be data streams from countless sources. The centrality of data and its countless value in today’s world do not, however, end contention and controversial views about its nature. Every stakeholder looks at data from his own perspective. Merchants and the business community view data as a valuable asset and commodity that could generate huge profits. In the existing legal systems, courts traditionally excluded information (data) from the ambit of property and current statutes seem to be silent about the issue of dealing with data as property. This paper attempts to study the propertization of data in light of contemporary business practices and the existing laws through consulting some relevant statutory laws and court cases. The aim of the discussion is to pay attention to the gap between business practices and current legal protection available for data or information. This paper is believed to be useful and timely as data propertization is an ongoing contentious issue that surfaces with every new wave of data-generated technology such as the IoT

Data protection challenges in the internet of things era: an assessment of protection offered by PDPA 2010

The Internet of Things (IoT) is an emerging technology of the 21st century. It is described as the first real evolution of the Internet that could positively or negatively affect all aspects of life. The basic idea of the IoT revolves around connecting things and objects (persons, animals, cars, trees, etc.) to the Internet and enabling them to communicate and then process (generate, receive, send, etc.) data about themselves and the environment surrounding them. Without a doubt, the IoT will bring countless benefits and provide timely data and information about places and objects. However, the IoT, like other technologies, has disadvantages especially in terms of privacy and security of data. Particularly, the IoT might challenge personal data protection law and misgive its ability to effectively stand in the rapid successive technology waves. As the most important law relating to the protection of personal data in Malaysia, the Personal Data Protection Act (PDPA) 2010 could be used as a benchmark for assessing the adequacy of data protection law in the country. Thus, this paper attempts to shed light on data protection challenges in the IoT era and then assess the adequacy of this Act in dealing with those challenges. The paper employs a legal doctrinal method to analyze the legal frameworks relevant to personal data protection. It may also use a comparative method to compare the PDPA with its counterparts in other countries. A study such as this is arguably useful and timely as Malaysia is already embarked in the IoT caravan with the vision of being “the Premier Regional IoT Development Hub.

Problème de k-Séparateur

Let G be a vertex-weighted undirected graph. We aim to compute a minimum weight subset of vertices whose removal leads to a graph where the size of each connected component is less than or equal to a given positive number k. If k = 1 we get the classical vertex cover problem. Many formulations are proposed for the problem. The linear relaxations of these formulations are theoretically compared. A polyhedral study is proposed (valid inequalities, facets, separation algorithms). It is shown that the problem can be solved in polynomial time for many special cases including the path, the cycle and the tree cases and also for graphs not containing some special induced sub-graphs. Some (k + 1)-approximation algorithms are also exhibited. Most of the algorithms are implemented and compared. The k-separator problem has many applications. If vertex weights are equal to 1, the size of a minimum k-separator can be used to evaluate the robustness of a graph or a network. Another application consists in partitioning a graph/network into different sub-graphs with respect to different criteria. For example, in the context of social networks, many approaches are proposed to detect communities. By solving a minimum k-separator problem, we get different connected components that may represent communities. The k-separator vertices represent persons making connections between communities. The k-separator problem can then be seen as a special partitioning/clustering graph problemConsidérons un graphe G = (V,E,w) non orienté dont les sommets sont pondérés et un entier k. Le problème à étudier consiste à la construction des algorithmes afin de déterminer le nombre minimum de nœuds qu’il faut enlever au graphe G pour que toutes les composantes connexes restantes contiennent chacune au plus k-sommets. Ce problème nous l’appelons problème de k-Séparateur et on désigne par k-séparateur le sous-ensemble recherché. Il est une généralisation du Vertex Cover qui correspond au cas k = 1 (nombre minimum de sommets intersectant toutes les arêtes du graphe

Robustness Against Transactional Causal Consistency

Distributed storage systems and databases are widely used by various types of applications. Transactional access to these storage systems is an important abstraction allowing application programmers to consider blocks of actions (i.e., transactions) as executing atomically. For performance reasons, the consistency models implemented by modern databases are weaker than the standard serializability model, which corresponds to the atomicity abstraction of transactions executing over a sequentially consistent memory. Causal consistency for instance is one such model that is widely used in practice. In this paper, we investigate application-specific relationships between several variations of causal consistency and we address the issue of verifying automatically if a given transactional program is robust against causal consistency, i.e., all its behaviors when executed over an arbitrary causally consistent database are serializable. We show that programs without write-write races have the same set of behaviors under all these variations, and we show that checking robustness is polynomial time reducible to a state reachability problem in transactional programs over a sequentially consistent shared memory. A surprising corollary of the latter result is that causal consistency variations which admit incomparable sets of behaviors admit comparable sets of robust programs. This reduction also opens the door to leveraging existing methods and tools for the verification of concurrent programs (assuming sequential consistency) for reasoning about programs running over causally consistent databases. Furthermore, it allows to establish that the problem of checking robustness is decidable when the programs executed at different sites are finite-state