31,967 research outputs found
Applications of Machine Learning to Threat Intelligence, Intrusion Detection and Malware
Artificial Intelligence (AI) and Machine Learning (ML) are emerging technologies with applications to many fields. This paper is a survey of use cases of ML for threat intelligence, intrusion detection, and malware analysis and detection. Threat intelligence, especially attack attribution, can benefit from the use of ML classification. False positives from rule-based intrusion detection systems can be reduced with the use of ML models. Malware analysis and classification can be made easier by developing ML frameworks to distill similarities between the malicious programs. Adversarial machine learning will also be discussed, because while ML can be used to solve problems or reduce analyst workload, it also introduces new attack surfaces
Climate Services for Resilient Development (CSRD) Partnership’s work in Latin America
The Climate Services for Resilient Development (CSRD)
Partnership is a private-public collaboration led by USAID,
which aims to increase resilience to climate change in
developing countries through the development and
dissemination of climate services. The partnership
began with initial projects in three countries: Colombia,
Ethiopia, and Bangladesh. The International Center for
Tropical Agriculture (CIAT) was the lead organization for
the Colombian CSRD efforts – which then expanded to
encompass work in the whole Latin American region
Cognitive system to achieve human-level accuracy in automated assignment of helpdesk email tickets
Ticket assignment/dispatch is a crucial part of service delivery business
with lot of scope for automation and optimization. In this paper, we present an
end-to-end automated helpdesk email ticket assignment system, which is also
offered as a service. The objective of the system is to determine the nature of
the problem mentioned in an incoming email ticket and then automatically
dispatch it to an appropriate resolver group (or team) for resolution.
The proposed system uses an ensemble classifier augmented with a configurable
rule engine. While design of classifier that is accurate is one of the main
challenges, we also need to address the need of designing a system that is
robust and adaptive to changing business needs. We discuss some of the main
design challenges associated with email ticket assignment automation and how we
solve them. The design decisions for our system are driven by high accuracy,
coverage, business continuity, scalability and optimal usage of computational
resources.
Our system has been deployed in production of three major service providers
and currently assigning over 40,000 emails per month, on an average, with an
accuracy close to 90% and covering at least 90% of email tickets. This
translates to achieving human-level accuracy and results in a net saving of
about 23000 man-hours of effort per annum
Scoping study brief – State of climate information services in East Africa
This brief presents the findings of a scoping study on climate information services in East Africa, conducted as a requirement for the Climate Resilient Agribusiness for Tomorrow (CRAFT) Project, under Work Stream 4 on Enabling Environment for Climate-Smart Agriculture (CSA). The purpose was to ascertain the status of climate information services under the ambit of CSA in each of the three East African countries
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