The hackathon to be held at ITWeb Security Summit 2017 is extending to the Northern Cape.
Spearheaded by Geekulcha, and run in conjunction with ITWeb Events and Snode, it is the first hackathon to take place at ITWeb Security Summit, and is aimed at stimulating and growing skills capacity in information security.
Various organisations are collaborating on the hackathon, where participants will interact and get a chance to be guided by over 500 cyber security minds at the summit.
As a first edition, the hackathon will only accommodate 30 people at Vodacom World in Midrand. The Northern Cape Department of Economic Development and Tourism has commissioned a parallel Security Hackathon in Kimberley, on 16 and 17 May, in collaboration with Sol Plaatje University, Geekulcha Student Society (GKSS).
The Kimberley edition of the hackathon will be managed by the GKSS and local entrepreneurs from the Diamond Creative Vision Hub.
A team of 11 people from the department and GKSS attended the training Ideathon in Pretoria, to get a sense of how to run things. A team from Snode will help the Kimberley edition of the hackathon by providing mentorship to ensure the participants build the most secure solutions possible.
#SS17Hack Midrand and Kimberley will be broadcast live to each other, giving a sense of concurrency, although each hackathon will have its own judging process.
Source: ITWeb By deploying mathematical algorithms in the fight against cybercrime, organisations stand to gain the 'street fighters' of cyber defence in their arsenal. This is according to Snode chief technology officer and founder Nithen Naidoo, who told delegates at the ITWeb Security Summit 2017 that algorithms already in use in other sectors stood to significantly improve cyber defence. "Maths is fast, doesn't lie and makes no assumptions. By using advanced algorithms, we are able to introduce intelligence amplification - rather than artificial intelligence - to the fight against cyber crime." He says these algorithms will help organisations catch over 80% of attack attempts, whereas artificial intelligence (AI) catches only around 30 - 40%. "We took statistical analytics from other spheres and applied it to cyber security. I don't know why we haven't used it before, but now it's here." "Maths is fast, doesn't lie and makes no assumptions." Naidoo said machine learning and mathematical algorithms combined could be harnessed to constantly monitor user behaviour and seek anomalies across any data, as well as patterns that are precursors to events.
Author: Nithen Naidoo, Founder and CEO At Snode, we like to see things differently and naturally gravitate towards alternative analysis. We are often asked why we use the phrase “Cyber Intelligence” as opposed to “Cybersecurity” to describe our real-time analytics platform. Our view is a paradigm shift (by design) and therefore not strictly aligned to standard definition. That said, it’s an excellent way to describe Snode’s unique value proposition. We see Cybersecurity as a technology layer, consisting of automated, signature based systems (e.g. Intrusion Prevention Systems); searching for known, commonly indiscriminate and unsophisticated attacks. We believe these traditional security controls are essential to a good security posture and complement the Snode Cyber Intelligence solution. Cyber Intelligence, in a Snode (design) context, is viewed as an autonomous layer that lies above the traditional cybersecurity stack; assessing network behaviours, threat intelligence and leveraging machine assisted analytics. Such technologies are designed to protect against more sophisticated and targeted attacks that have never been seen before and therefore circumvent signature based controls. As an example, consider the following: an authenticated, authorised finance staff member accesses a financial system database. Such activity would not be considered malicious by a signature based control and generally goes unnoticed as this is role-based acceptable behaviour. However, a Cyber Intelligence platform may report this behaviour as anomalous since it deviates from the user’s normal pattern of behaviour. Therefore, such activity may be indicative of, and reported as, a potential disclosure of sensitive data. This scenario was an actual finding at a Snode mining client. A subsequent investigation found that the employee was colluding with an organised labour (union) member to supply sensitive financial information ahead of an upcoming wage negotiation. Hence, we describe Cyber Intelligence as the technology layer that goes to work; when all else fails.