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Constructing secure service compositions with patterns
In service based applications, it is often necessary to construct compositions of services in order to provide required functionality in cases where this is not possible through the use of a single service. Whilst creating service compositions, it is necessary to ensure not only that the functionality required of the composition is achieved but also that certain security properties are preserved. In this paper, we describe an approach to constructing secure service compositions. Our approach is based on the use of composition patterns and rules that determine the security properties that should be preserved by the individual services that constitute a composition in order to ensure that security properties of the overall composition are also satisfied. Our approach extends a framework developed to support the runtime service discovery
Link Before You Share: Managing Privacy Policies through Blockchain
With the advent of numerous online content providers, utilities and
applications, each with their own specific version of privacy policies and its
associated overhead, it is becoming increasingly difficult for concerned users
to manage and track the confidential information that they share with the
providers. Users consent to providers to gather and share their Personally
Identifiable Information (PII). We have developed a novel framework to
automatically track details about how a users' PII data is stored, used and
shared by the provider. We have integrated our Data Privacy ontology with the
properties of blockchain, to develop an automated access control and audit
mechanism that enforces users' data privacy policies when sharing their data
across third parties. We have also validated this framework by implementing a
working system LinkShare. In this paper, we describe our framework on detail
along with the LinkShare system. Our approach can be adopted by Big Data users
to automatically apply their privacy policy on data operations and track the
flow of that data across various stakeholders.Comment: 10 pages, 6 figures, Published in: 4th International Workshop on
Privacy and Security of Big Data (PSBD 2017) in conjunction with 2017 IEEE
International Conference on Big Data (IEEE BigData 2017) December 14, 2017,
Boston, MA, US
Model the System from Adversary Viewpoint: Threats Identification and Modeling
Security attacks are hard to understand, often expressed with unfriendly and
limited details, making it difficult for security experts and for security
analysts to create intelligible security specifications. For instance, to
explain Why (attack objective), What (i.e., system assets, goals, etc.), and
How (attack method), adversary achieved his attack goals. We introduce in this
paper a security attack meta-model for our SysML-Sec framework, developed to
improve the threat identification and modeling through the explicit
representation of security concerns with knowledge representation techniques.
Our proposed meta-model enables the specification of these concerns through
ontological concepts which define the semantics of the security artifacts and
introduced using SysML-Sec diagrams. This meta-model also enables representing
the relationships that tie several such concepts together. This representation
is then used for reasoning about the knowledge introduced by system designers
as well as security experts through the graphical environment of the SysML-Sec
framework.Comment: In Proceedings AIDP 2014, arXiv:1410.322
An active, ontology-driven network service for Internet collaboration
Web portals have emerged as an important means of collaboration on the WWW, and the integration of ontologies promises to make them more accurate in how they serve users’ collaboration and information location requirements. However, web portals are essentially a centralised architecture resulting in difficulties supporting seamless roaming between portals and collaboration between groups supported on different portals. This paper proposes an alternative approach to collaboration over the web using ontologies that is de-centralised and exploits content-based networking. We argue that this approach promises a user-centric, timely, secure and location-independent mechanism, which is potentially more scaleable and universal than existing centralised portals
Mining Threat Intelligence about Open-Source Projects and Libraries from Code Repository Issues and Bug Reports
Open-Source Projects and Libraries are being used in software development
while also bearing multiple security vulnerabilities. This use of third party
ecosystem creates a new kind of attack surface for a product in development. An
intelligent attacker can attack a product by exploiting one of the
vulnerabilities present in linked projects and libraries.
In this paper, we mine threat intelligence about open source projects and
libraries from bugs and issues reported on public code repositories. We also
track library and project dependencies for installed software on a client
machine. We represent and store this threat intelligence, along with the
software dependencies in a security knowledge graph. Security analysts and
developers can then query and receive alerts from the knowledge graph if any
threat intelligence is found about linked libraries and projects, utilized in
their products
Enabling Machine Understandable Exchange of Energy Consumption Information in Intelligent Domotic Environments
In the 21st century, all the major countries around the world are coming together to reduce the impact of energy generation and consumption on the global environment. Energy conservation and its efficient usage has become a top agenda on the desks of many governments. In the last decade, the drive to make homes automated and to deliver a better assisted living picked pace and the research into home automation systems accelerated, usually based on a centralized residential gateway. However most devised solutions fail to provide users with information about power consumption of different house appliances. The ability to collect power consumption information can lead us to have a more energy efficient society. The goal addressed in this paper is to enable residential gateways to provide the energy consumption information, in a machine understandable format, to support third party applications and services. To reach this goal, we propose a Semantic Energy Information Publishing Framework. The proposed framework publishes, for different appliances in the house, their power consumption information and other properties, in a machine understandable format. Appliance properties are exposed according to the existing semantic modeling supported by residential gateways, while instantaneous power consumption is modeled through a new modular Energy Profile ontolog
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