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Malicious activities conducted by disgruntled employees via an email platform can cause profound damage to an organization such as financial and reputational losses. This threat is known as an “Insider IT Sabotage” threat. This involves employees misusing their access rights to harm the organization. Events leading up to the attack are not technical but rather behavioural. The problem is that owing to the high volume and complexity of emails, the risk of insider IT sabotage cannot be diminished with rule-based approaches.

Malicious human behaviours that insiders within the insider IT sabotage category would possess are studied and mapped to phrases that would appear in email communications. A large email data set is classified according to behavioural characteristics of these employees. Machine learning algorithms are used to identify occurrences of this insider threat type. The accuracy of these approaches is measured.

It is shown in this paper that suspicious behaviour of disgruntled employees can be discovered, by means of machine intelligence techniques. The output of the machine learning classifier depends mainly on the depth and quality of the phrases and behaviour analysis, cleansing and number of email attributes examined. This process of labelling content in isolation could be improved if other attributes of the email data are included, such that a confidence score can be computed for each user.

This research presents a novel approach to show that the creation of a prototype that can automate the detection of insider IT sabotage within email systems to mitigate the risk within organizations.

… Strange but true facts, number 7: Wandsworth is famous for more than its blue halo.

Describes the history and activities of the Crime Writers′ Association, highlighting various awards, and recent winners. Details the CWA Spare Copy Catalogue Scheme, whereby authors′ spare copies of their own books are made available for purchase by libraries when those books are out of print.

Contemporary organizations with multinational business activities must strive to achieve strategic responsiveness to thrive and survive as they operate across a highly dynamic and complex global business environment. Here we emphasize the importance of combining the slow analytical strategy processes at headquarters with the fast autonomous responses taken by frontline agents in the subsidiaries in view of the changing conditions. New business developments are observed first in the fast activities around the multinational periphery where updated experiences from ongoing responses create useful insights that can be used strategically if management at headquarters is cognizant about its existence and able to collect this information. We introduce the notion of democratizing the strategic engagement of managers and employees at all levels and locations of the multinational corporation (MNC) as an essential leadership paradigm. The implied interaction between slow central analytical reasoning at headquarters and updated insights from fast decentralized initiatives in local subsidiaries constitutes an effective dynamic responsive mechanism. This dynamic interaction implies that critical strategic decisions made in the MNC must be informed by the diverse updated insights of managers and employees operating on the corporate frontlines tapping into the crowd wisdom readily available in and around the organization.