Cyber intelligence and analytics specialist, Snode, recently used its tools to analyse the #FeesMustFall protest and delve deeper within Twitter, offering enriched insight beyond 140 characters.
Social media platforms such as Twitter may be divisive, but its significance cannot be overlooked. Cyber intelligence and analytics specialist, Snode, believes the potential applications for social media are yet to be fully realised. “As a source of intelligence, Twitter is a valuable source of intelligence and it should be utilised by business and law enforcement. It is an open-source data-rich platform and needs to be leveraged in the best way possible,” notes CIO and co-founder of Snode, Nithen Naidoo.
Using the recent #FeesMustFall protests as a case study to showcase the enriched capabilities of cyber intelligence, Snode was able to apply its analytical tools to delve deeper into the anatomy of the Tweets, and even discover that outside influencers were making an impact.
The university fee protests are a hot topic of conversation in South Africa. The dialogue is been most prevalent on Twitter, where numerous messages have been exchanged under the guise of creating a discourse around the cost of tertiary education. Interestingly though, Snode’s analysts have unearthed some other key insights not obvious to most people.
To gain a deeper understanding of the underlying forces driving the #FeesMustFall protests, Snode analysts have fused various social media conversations to identify emerging trends associated with, and patterns of behaviour fuelling, this massive campaign.
The most telling finding is that many of the tweets did not originate from the same location that the message was referencing. In particular, the majority of tweets mentioning the University of Witwatersrand were found to have been sent from Pretoria, nearly 65 kilometres away.
In fact, Snode detected an anomaly in which tweets from South Africa’s capital with the #FeesMustFall hashtag referenced Wits 14 times more than they did in their own city’s university protest. Accompanying this anomaly was the fact that only 3% of #FeesMustFall tweets came from users linked to the @WitsUniversity handle, as opposed to a staggering total of 94% from politically affiliated Twitter accounts.
According to Naidoo, it can be inferred that there was another agenda being played out, and the #FeesMustFall protests are being abused by some social media users to draw attention to other topics, ultimately misrepresenting the true aim of students.
While the potential for social media to be misused by a small percentage of users, Snode says that victims of crime and law enforcement have the ability to fight back. The company’s real time processing for example, can dissect a myriad of information contained within a Tweet, including a Twitter user’s (real) name, origin of the Tweet (longitude and latitude), device type (iPhone or Android), and place of residence (e.g. city or hometown).
“If users share an image on Twitter for example, the metadata contained within that photo can offer us a wide ranging array of insights,” says Naidoo. “There are a host of AI applications available, such as Russia’s FindFace, which allows users to scan a digital image of someone and then discover their online profile. There are therefore a number of tools on hand to benefit law enforcement as much as they do criminals,” he continued.
In the right hands, this kind of machine assisted analytics can empower social media platforms such as Twitter to help make data-driven decisions, notes Naidoo. In the US, a number of American agencies are already using deep analysis within Twitter to track down dissidents, according to Saudi scientist Hala Al-Dosari in a recent interview with Bloomberg Businessweek.
“South Africa needs to use available technology correctly, especially when it comes to tackling issues like crime within the country. With regard to socially relevant topics such as the student protests, having cyber intelligence at work can assist in gleaning vital insight. At Snode, we believe having such knowledge can not only help us understand the climate better, but also assist law enforcement and government services to predict and respond to critical events more efficiently,” says Naidoo.
Source: TechCentral One of the biggest problems with identifying cybersecurity breaches is knowing that they happened at all. Too often, attackers breach companies’ defences and remain undetected — until it’s too late. A new South African start-up, Snode, incubated by fast-growing South African fintech company Hello Group but now spun off as its own business, has developed a solution that it believes will help IT departments identify suspicious behaviour as it’s happening, even when traditional security measures like firewalls fail to stop intruders. Snode, which was founded by cybersecurity expert Nithen Naidoo, has developed technology that alerts companies to the tell-tale signs that a cyberattack might be about to take place. “If you are looking for fraud only at the point where it occurred, you will always be reactive,” Naidoo said. “But if you can predict the fraud by looking at precursor patterns, you can prevent it and become proactive in your response.” Hello Group CEO Nadir Khamissa said Naidoo became involved with the company about 10 years ago to help it root out cybersecurity breaches and shore up its cyber defences. He became even more involved as the company moved into mobile money transfer with Hello Paisa. Hello Group, which has provided venture capital funding to Snode, needed something beyond basic firewall and signature (username and password) security mechanisms. “We needed something to understand patterns of behaviour, which is something we could not buy.” Naidoo built technologies that passively “sniff” all of a company’s network data, differentiating between different types of traffic going through the network in real time using “deep-packet inspection”. "The technology is “aware” of the start and end point of every packet of data, both internal and external," Khamissa said. “This is imperative to be able to understand patterns of behaviour. This enormous volume of data gets put into machine-learning algorithms that understand the patterns and is then overlaid with the expected or traditional behaviour of a user to identify anomalies.” The problem with most security solutions is the analyst interface “turns into a Christmas tree” of alerts — most of them false alarms — defeating the purpose, he said. “We have invested in pattern-recognition technologies to avoid these false positives. Snode understands patterns of behaviour and eliminates those.” Snode, Khamissa said, doesn’t replace firewalls and username-and-password-based security mechanisms. Rather, it is a layer on top of those solutions to help companies understand and identify behaviour and vulnerabilities. “Snode at its core uses mathematics to detect anomalies and patterns in any type of data from any source and understand the behavioural patterns of normal behaviour from abnormal behaviour,” explained Naidoo. “Just your presence on the network leaves a trace and affects the network in a certain way. Snode understands your systems environment and it has a signature for it. It identifies any stray from what it deems normal behaviour.At some point in the early stage of a cyberattack, there would have to be some form of reconnaissance. Snode actively looks for this, whether it’s a hacker doing a port scan, or an employee accessing a system they don’t normally access,” he said. “It does this in real time, with in-flight analytics.” Although Snode can’t analyse encrypted network traffic, it can still pick up anomalies. “If my encrypted channel suddenly does 2GB of traffic at 2am, that’s an anomaly. Sure, you can mask your identity in various ways, but no matter you do, you are going to influence the system.” Khamissa said Snode uses machine-learning algorithms to augment human efforts to defend digital networks. “The good guys are completely outgunned in the cyberwar. Attackers are highly motivated and mechanised. In the defence, you typically have a junior guy in IT patching servers, looking at endless alerts. To notch up your defence capabilities, you need something like Snode to augment the defenders of your networks.” After developing the solution inside Hello Group for many years, it has now been “productised” to be sold to other companies. Snode has run the solution in various iterations with PricewaterhouseCoopers over the past three years. PwC will now take the product to market as the company’s first reseller partner. It also has customers in South Africa, Nigeria, the UK and Australia. “Our focus is really on South Africa for now, but we have been getting a lot of requests from abroad,” said Khamissa. The key industry it intends focusing on is financial services, he said.
Source: htxt.africa Cyber security firm Snode has taken a look at tweets sorrounding recent #FeesMustFall protests and found some incredibly interesting data. Earlier this year Snode launched a cyber security solution which uses machine learning and algorithms to detect patterns and anomalies in a network. We’ve learned that Snode is quite good at detecting patterns so the team decided to see what sort of patterns they could find while analysing tweets related to #FeesMustFall. This was done by looking at a few things namely; location of tweets and tweets using the #FeesMustFall hashtag. So what did they find? Looking at the locations of tweets Snode found that many tweets about Wits University originated from Pretoria. This Snode says contrasted against the subject of the tweets analysed. Snode also found that users in Pretoria referenced Wits University 14 times more than the University of Pretoria. Another interesting revelation was that of those users in the capital only 3% of #FeesMustFall tweets came from users linked to the Wits University account. The vast majority of tweets referencing the institution – 94% to be precise – were sent from accounts that have political ties. This, says Snode reveals that the #FeesMustFall protests may have been adopted by social media users to draw attention away from the goals of students. Data in pictures Snode says that by further analysing the meta-data in photos shared on Twitter there exists the potential to glean even more data such as the location the photo was taken (using GPS co-ordinates), the type of device the person was using and even a user’s real name. But it doesn’t end there according to Snode co-founder Nithen Naidoo. “There are a host of AI applications available, such as Russia’s FindFace, which allows users to scan a digital image of someone and then discover their online profile. There are therefore a number of tools on hand to benefit law enforcement as much as they do criminals,” said Naidoo. This analysis shows us that you can’t inherently trust everything you read on social media, and perhaps we should be more questioning of what we see rather than sharing something because we think it’s topical. Deep analysis of social media can also help those in positions of power make more informed decisions about what the public sentiment really is. “With regard to socially relevant topics such as the student protests, having cyber intelligence at work can assist in gleaning vital insight,” says the co-founder. “At Snode, we believe having such knowledge can not only help us understand the climate better, but also assist law enforcement and government services to predict and respond to critical events more efficiently,” Naidoo concluded.