Detecting, catching and successfully prosecuting cybercrime requires collaboration across private sector, law enforcement, insurance companies and national security agencies. In this session, approaches to collect, analyze, store and share digital evidence will be examined. Methods of safely transmitting data between private sector and law enforcement will be discussed. Demonstration of workflows between investigators, law enforcement, prosecutors and insurance adjusters will be covered.
I also reference this 2021 DarkReading Article: Handcuffs over AI.
An updated deck for my talk on Big Data in Cybersecurity can be downloaded here.
Machine learning (ML) is arguably the most potent advancement in technology since atomic fission with similar benefit and risk extremes. The outcome driven nature of machine learning allows computers to rapidly test theories to find pathways to support specific goals. These approaches applied to social engineering can be used to manipulate human factors for purposes including cybersecurity breach. This session will cover the philosophies, strategies and tactics used to accomplish a successful campaign to recruit human assets to a cause. Factors to mitigate risk in these advanced social engineering attacks will also be examined.
Slides for our talk at Secure360 2020 can be downloaded here.
Details on the session are posted here: https://secure360.org/session/charles-herring-metric-driven-secdevops/?conference=11809&date=20200505
From IIA/ISACA IT Hacking Conference : Developing software that changes the world, exceeds customer expectations, provides turn-key functionality in diverse scenarios while meeting security and compliance requirements is the holy grail of Security Development Operations (SECDEVOPS). There are thousands of variables that need to be constantly addressed to find the balance that delivers sustainable and secure success. In this session, WitFoo’s chief engineers will outline an innovative approach to secure devops called Metric Driven Development.
From DEFCON & GrrCON: Network Behavior Anomaly Detection (NBAD) and User and Entity Behavior Analytics (UEBA) are heralded as machine learning fueled messiahs for finding advanced attacks. The data collection and processing methodologies of these approaches create a series of new exploitable vectors that can allow attackers to navigate network and systems undetected. In this session, methods for poisoning data, transforming calculations and preventing alerts will be examined. Proof of concept code will be demonstrated and made available. Approaches to harden against these attacks will also be discussed as well as outlining needed changes in detection standards.
I am looking forward to speaking at the Georgia Annual ISSA Meeting on 11/15. The blog series that the talk is based on is below.