The Common Vulnerability Scoring System (CVSS) is the state-of-the art system for assessing software vulnerabilities. However, it has been criticized for lack of validity and practitioner relevance. In this paper, the credibility of the CVSS scoring data found in five leading databases – NVD, X-Force, OSVDB, CERT-VN, and Cisco – is assessed. A Bayesian method is used to infer the most probable true values underlying the imperfect assessments of the databases, thus circumventing the problem that ground truth is not known. It is concluded that with the exception of a few dimensions, the CVSS is quite trustworthy. The databases are relatively consistent, but some are better than others. The expected accuracy of each database for a given dimension can be found by marginalizing confusion matrices. By this measure, NVD is the best and OSVDB is the worst of the assessed databases

Securing IoT devices is gaining attention as the security risks associated with these devices increase rapidly. TrustZone-M, a Trusted Execution Environment (TEE) for Cortex-M processors, ensures stronger security within an IoT device by allowing isolated execution of security-critical operations, without trusting the entire software stack. However, TrustZone-M does not guarantee secure cross-world communication between applications in the Normal and Secure worlds. The cryptographic protection of the communication channel is an obvious solution; however, within a low-power IoT device, it incurs high overhead if applied to each cross-world message exchange. We present ShieLD, a framework that enables a secure communication channel between the two TrustZone-M worlds by leveraging the Memory Protection Unit (MPU). ShieLD guarantees confidentiality, integrity and authentication services without requiring any cryptographic operations. We implement and evaluate ShieLD using a Musca-A test chip board with Cortex-M33 that supports TrustZone-M. Our empirical evaluation shows, among other gains, the cross-zone communication protected with ShieLD is 5 times faster than the conventional crypto-based communication. 

Time Division Multiple Access (TDMA) is often used in Wireless Sensor Networks (WSNs), especially for critical applications, as it provides high energy efficiency, guaranteed bandwidth, bounded and predictable latency, and absence of collisions. However, TDMA is vulnerable to selective jamming attacks. In TDMA transmission, slots are typically pre-allocated to sensor nodes, and each slot is used by the same node for a number of consecutive superframes. Hence, an adversary could thwart a victim node’s communication by simply jamming its slot(s). Such attack turns out to be effective, energy efficient, and extremely difficult to detect. In this paper, we present JAMMY, a distributed and dynamic solution to selective jamming in TDMA-based WSNs. Unlike traditional approaches, JAMMY changes the slot utilization pattern at every superframe, thus making it unpredictable to the adversary. JAMMY is decentralized, as sensor nodes determine the next slot utilization pattern in a distributed and autonomous way. Results from performance analysis of the proposed solution show that JAMMY introduces negligible overhead yet allows multiple nodes to join the network, in a limited number of superframes.