SMS-Based ICT Tool for Knowledge Sharing in Agriculture

Agriculture is the world’s major industry with 60% of the global population depending on it.  Being the major source of livelihood, agriculture is challenged by issues such as food shortage, food security problems, climate change affecting crop yield, land degradation, decrease of crop varieties and others. There is a huge amount of knowledge products generated by the government agencies, local universities, private civic groups, local government units and non-government organizations (NGOs) to address these issues however the information has difficulty reaching the intended farm practitioners as end-user. With this aforesaid challenge, a technology based information sharing and access among stakeholders such as agricultural knowledge experts (academe) and knowledge end-users (farmers) is a dire need.  Information and Communications Technology (ICT) has always been an indispensable tool that can provide an environment where knowledge generators and knowledge users can use to exchange information any time and place.  Retooling and scaling up the process how information and knowledge products is being accessed and shared is indeed a critical consideration. Using descriptive research and qualitative approach, this study determined an ICT tool, a managed SMS-based system to be highly acceptable to the identified stakeholders as an information sharing medium and model and is therefore recommended for use.  The result of this research shall serve as an implementation guide for government, non-government organizations(NGOs), extension service providers, system integrators, researchers, and other related groups offering or planning to engage in similar service

On the Automated Management of Security Incidents in Smart Space

The proliferation of smart spaces, such as smart buildings, is increasing opportunities for offenders to exploit the interplay between cyber and physical components, in order to trigger security incidents. Organizations are obliged to report security incidents to comply with recent data protection regulations. Organizations can also use incident reports to improve security of the smart spaces where they operate. Incident reporting is often documented in structured natural language. However, reports often do not capture relevant information about cyber and physical vulnerabilities present in a smart space that are exploited during an incident. Moreover, sharing information about security incidents can be difficult, or even impossible, since a report may contain sensitive information about an organization. In previous work, we provided a meta-model to represent security incidents in smart spaces. We also developed an automated approach to share incident knowledge across different organizations. In this paper we focus on incident reporting. We provide a System Editor to represent smart buildings where incidents can occur. Our editor allows us to represent cyber and physical components within a smart building and their interplay. We also propose an Incident Editor to represent the activities of an incident, including —for each activity— the target and the resources exploited, the location where the activity occurred, and the activity initiator. Building on our previous work, incidents represented using our editor can be shared across various organizations, and instantiated in different smart spaces to assess how they can re-occur. We also propose an Incident Filter component that allows viewing and prioritizing the most relevant incident instantiations, for example, involving a minimum number of activities. We assess the feasibility of our approach in assisting incident reporting using an example of a security incident that occurred in a research center

Collaborative Security Mechanism in Detecting Intrusion Activity

The rapidly increasing array of Internet-scale threats is a pressing problem for every organization that utilizes the network. Organizations often have limited knowledge as well as capability to detect and respond to these threats. The sharing of information related to probes and attacks is a facet of an emerging trend toward ‘’collaborative security’’. Collaborative security mechanism provide network administrator with a valuable tool in this increasingly hostile environment. This research paper proposed a new Collaborative Security Model which incorporated existing mechanism such as prevention by using firewall or any network devices, detection by using Intrusion Detection System (IDS), response by correlating any log files gathered from multiple devices and forensic which tracing the activity of the intrusion. The model integrates and compensates the advantages and disadvantages of each mechanism in order to create a strong defensive model for the network infrastructure

Information and knowledge leakage in supply chain

The current world of post industrial value generation sees companies increasingly analyzing their internal operations against their external organizations to identify supply/demand fluctuations along the supply chain. Within these integrated relationships between internal and external parties in the supply chain, knowledge and information have become very important production resources. The existence and success of an increasing number of organizations strongly depend on their capabilities to utilize knowledge and information for profit generation. By managing more efficient information sharing, the volume of company confidential information passing through the supply chain increases, and this brings about more incidences of knowledge leakage and information leakage. A survey by PricewaterhouseCoopers in 2014 shows information security spending over the next 12 months would increase 60.27 % in Asia and 48.98 % in all regions. This emphasizes the importance of information privacy and therefore the necessity to study the information and knowledge leakage in integrated supply chain. The objectives of this study are to investigate the factors triggering information and knowledge leakage and create a mitigation framework to soften the impact of leakages on performance. The above objectives will be met by formulating and examining several hypotheses of a conceptualized information leakage (IL) and knowledge leakage (KL) framework. A case study derived from a structured interview is adopted as a methodology in this research. As a result, this paper contributes a novel theoretical model that characterizes information and knowledge leakage in an integrated supply chain. Therefore, it also adds new knowledge of managing information and knowledge leakage to supply chain management

Interoperability, Trust Based Information Sharing Protocol and Security: Digital Government Key Issues

Improved interoperability between public and private organizations is of key significance to make digital government newest triumphant. Digital Government interoperability, information sharing protocol and security are measured the key issue for achieving a refined stage of digital government. Flawless interoperability is essential to share the information between diverse and merely dispersed organisations in several network environments by using computer based tools. Digital government must ensure security for its information systems, including computers and networks for providing better service to the citizens. Governments around the world are increasingly revolving to information sharing and integration for solving problems in programs and policy areas. Evils of global worry such as syndrome discovery and manage, terror campaign, immigration and border control, prohibited drug trafficking, and more demand information sharing, harmonization and cooperation amid government agencies within a country and across national borders. A number of daunting challenges survive to the progress of an efficient information sharing protocol. A secure and trusted information-sharing protocol is required to enable users to interact and share information easily and perfectly across many diverse networks and databases globally.Comment: 20 page

Privacy-Friendly Collaboration for Cyber Threat Mitigation

Sharing of security data across organizational boundaries has often been advocated as a promising way to enhance cyber threat mitigation. However, collaborative security faces a number of important challenges, including privacy, trust, and liability concerns with the potential disclosure of sensitive data. In this paper, we focus on data sharing for predictive blacklisting, i.e., forecasting attack sources based on past attack information. We propose a novel privacy-enhanced data sharing approach in which organizations estimate collaboration benefits without disclosing their datasets, organize into coalitions of allied organizations, and securely share data within these coalitions. We study how different partner selection strategies affect prediction accuracy by experimenting on a real-world dataset of 2 billion IP addresses and observe up to a 105% prediction improvement.Comment: This paper has been withdrawn as it has been superseded by arXiv:1502.0533

Controlled Data Sharing for Collaborative Predictive Blacklisting

Although sharing data across organizations is often advocated as a promising way to enhance cybersecurity, collaborative initiatives are rarely put into practice owing to confidentiality, trust, and liability challenges. In this paper, we investigate whether collaborative threat mitigation can be realized via a controlled data sharing approach, whereby organizations make informed decisions as to whether or not, and how much, to share. Using appropriate cryptographic tools, entities can estimate the benefits of collaboration and agree on what to share in a privacy-preserving way, without having to disclose their datasets. We focus on collaborative predictive blacklisting, i.e., forecasting attack sources based on one's logs and those contributed by other organizations. We study the impact of different sharing strategies by experimenting on a real-world dataset of two billion suspicious IP addresses collected from Dshield over two months. We find that controlled data sharing yields up to 105% accuracy improvement on average, while also reducing the false positive rate.Comment: A preliminary version of this paper appears in DIMVA 2015. This is the full version. arXiv admin note: substantial text overlap with arXiv:1403.212