Biblio
Industrial Internet-of-Things has been touted as the next revolution in the industrial domain, offering interconnectivity, independence, real-time operation, and self-optimization. Integration of smart systems, however, bridges the gap between information and operation technology, creating new avenues for attacks from the cyber domain. The dismantling of this air-gap, in conjunction with the devices' long lifespan -in the range of 20-30 years-, motivates us to bring the attention of the community to emerging advanced persistent threats. We demonstrate a threat that bridges the air-gap by leaking data from memory to analog peripherals through Direct Memory Access (DMA), delivered as a firmware modification through the supply chain. The attack automatically adapts to a target device by leveraging the Device Tree and resides solely in the peripherals, completely transparent to the main CPU, by judiciously short-circuiting specific components. We implement this attack on a commercial Programmable Logic Controller, leaking information over the available LEDs. We evaluate the presented attack vector in terms of stealthiness, and demonstrate no observable overhead on both CPU performance and DMA transfer speed. Since traditional anomaly detection techniques would fail to detect this firmware trojan, this work highlights the need for industrial control system-appropriate techniques that can be applied promptly to installed devices.
Tactics Techniques and Procedures (TTPs) in cyber domain is an important threat information that describes the behavior and attack patterns of an adversary. Timely identification of associations between TTPs can lead to effective strategy for diagnosing the Cyber Threat Actors (CTAs) and their attack vectors. This study profiles the prevalence and regularities in the TTPs of CTAs. We developed a machine learning-based framework that takes as input Cyber Threat Intelligence (CTI) documents, selects the most prevalent TTPs with high information gain as features and based on them mine interesting regularities between TTPs using Association Rule Mining (ARM). We evaluated the proposed framework with publicly available TTPbased CTI documents. The results show that there are 28 TTPs more prevalent than the other TTPs. Our system identified 155 interesting association rules among the TTPs of CTAs. A summary of these rules is given to effectively investigate threats in the network.
Conducting active cyberdefense requires the acceptance of a proactive framework that acknowledges the lack of predictable symmetries between malicious actors and their capabilities and intent. Unlike physical weapons such as firearms, naval vessels, and piloted aircraft-all of which risk physical exposure when engaged in direct combat-cyberweapons can be deployed (often without their victims' awareness) under the protection of the anonymity inherent in cyberspace. Furthermore, it is difficult in the cyber domain to determine with accuracy what a malicious actor may target and what type of cyberweapon the actor may wield. These aspects imply an advantage for malicious actors in cyberspace that is greater than for those in any other domain, as the malicious cyberactor, under current international constructs and norms, has the ability to choose the time, place, and weapon of engagement. This being said, if defenders are to successfully repel attempted intrusions, then they must conduct an active cyberdefense within a framework that proactively engages threatening actions independent of a requirement to achieve attribution. This paper proposes that private business, government personnel, and cyberdefenders must develop a threat identification framework that does not depend upon attribution of the malicious actor, i.e., an attribution agnostic cyberdefense construct. Furthermore, upon developing this framework, network defenders must deploy internally based cyberthreat countermeasures that take advantage of defensive network environmental variables and alter the calculus of nefarious individuals in cyberspace. Only by accomplishing these two objectives can the defenders of cyberspace actively combat malicious agents within the virtual realm.