Jan/Feb 19 - ChannelVision Magazine

Cyber Patrol that will stop recasting threat data as intelligence and instead focus on generating actionable insights from this data, the prerequisite for “threat intelligence.” Unfortunately, the vast majority still won’t take any action from the data presented, which means they won’t actually have any intelligence – only an interesting storyline. Artificial intelligence and machine learning will play a more prominent role as the velocity and variety of attacks makes conventional approaches – such as blacklists – outdated and ill-equipped to deal with modern cyber threats. The average phishing site, for example, is online only for a few hours. With such a crowded domain space, attackers have to be clever about the domains they reg- ister and exploit. Luckily, these domains generally have certain characteristics, which machine learning algorithms can exploit and detect, while other properties of attack vectors also can be recognized by appropriately trained AI. AI also will be used to detect break- ins, spam, phishing and more. Although it will mostly work well, look out for the occasional mistake: these will be utterly incomprehensible to humans and very hard for vendors to explain to their customers. From financial gain to life-and-death As our world becomes increasingly digitized and connected devices con- tinue to permeate every aspect of our daily lives, the risks posed by cyber- criminals are escalating. A large-scale attack on critical infrastructure such as energy services, water supplies or even hospitals could cause massive dam- age and even loss of life. Autonomous vehicles, although not prevalent on our shores yet, are attractive targets for the more ruthless type of cybercriminal. And with the growth in digital medical devices, hackers could directly target an individual and interfere with their pacemakers or heartrate monitors. Privacy also will become a key con- cern: consumer connected devices such as cameras, microphones and wear- ables will become a major security issue as hackers discover ways to see live au- dio and video of unsuspecting people’s lives. The fallout of such an incident be- ing exposed could drastically erode trust in technology and make people treat technology with greater caution, as they realize the devices they have enjoyed without concern carry immense risk to their personal privacy and security. Even though the threat landscape keeps changing, the common thread seems to be that email continues to be the most common – and least protected – attack vector. We can’t predict exactly what 2019 threats will look like, but we can predict that if email remains vulner- able it will continue to be the preferred entry point for criminals to deliver threats to organizations. o Brian Pinnock is a cybersecurity specialist at Mimecast. Source: Aruba survey of IT/security professionals Sourc 10% 20% 30% 40% 50% 60% 1% It is difficult to protect complex and dynamically changing attack surfaces (mobile, byod, cloud, ioT, etc.) There is a lack of adequate staff with the necessary skills Attackers are persistent, sophisticated, well trained and well financed Human error Complexity and the inability to integrate security solutions Lack of visibility into the network Threats that have v ded traditional security defenses and are now inside the IT ecosystem Other 35% 36% 42% 43% 46% 48% 49% 1% The top security benefits from ML and advanced analytics Source: Aruba survey of IT/security professionals Three responses permitted 0% 10% 20% 30% 40% 50% 60% 70% 63% 60% 56% 44% 32% 28% 18% Increase effectiveness of security teams More efficient investigations Find stealthy threats that have evaded the standard security defenses Better integration with threat intelligence source Automate routine tasks Reduction in white noise/false positives Supplement to Security Information and Event Management Systems (SIEM) Current Adoption of Collaborative Chat Apps Source: Spiceworks By ompany size Skype for Business M crosoft Teams Slack Google Hangouts Workplace by Facebook 10% 0% 20% 30% 40% 50% 60% 36% 46% 54% 17% 22% 25% 17% 14% 13% 8% 11% 18% 2% 1% 2% Small Businesses Mid-size businesses Large businesses Business Adoption Plans for Collaborative Chat Apps January - February, 2019 | Channel Vision 29