6 research outputs found
Detecting semantic social engineering attacks with the weakest link: Implementation and empirical evaluation of a human-as-a-security-sensor framework
The notion that the human user is the weakest link in information security has been strongly, and, we argue, rightly contested in recent years. Here, we take a step further showing that the human user can in fact be the strongest link for detecting attacks that involve deception, such as application masquerading, spearphishing, WiFi evil twin and other types of semantic social engineering. Towards this direction, we have developed a human-as-a-security-sensor framework and a practical implementation in the form of Cogni-Sense, a Microsoft Windows prototype application, designed to allow and encourage users to actively detect and report semantic social engineering attacks against them. Experimental evaluation with 26 users of different profiles running Cogni-Sense on their personal computers for a period of 45 days has shown that human sensors can consistently outperform technical security systems. Making use of a machine learning based approach, we also show that the reliability of each report, and consequently the performance of each human sensor, can be predicted in a meaningful and practical manner. In an organisation that employs a human-as-a-security-sensor implementation, such as Cogni-Sense, an attack is considered to have been detected if at least one user has reported it. In our evaluation, a small organisation consisting only of the 26 participants of the experiment would have exhibited a missed detection rate below 10%, down from 81% if only technical security systems had been used. The results strongly point towards the need to actively involve the user not only in prevention through cyber hygiene and user-centric security design, but also in active cyber threat detection and reporting
Adjuvant bevacizumab for melanoma patients at high risk of recurrence: survival analysis of the AVAST-M trial (vol 29, pg 1843, 2018)
Adjuvant bevacizumab for melanoma patients at high risk of recurrence: survival analysis of the AVAST-M trial
Background: Bevacizumab is a recombinant humanised monoclonal antibody to vascular endothelial growth factor shown to improve survival in advanced solid cancers. We evaluated the role of adjuvant bevacizumab in melanoma patients at high risk of recurrence. Patients and methods: Patients with resected AJCC stage IIB, IIC and III cutaneous melanoma were randomised to receive either adjuvant bevacizumab (7.5?mg/kg i.v. 3 weekly for 1?year) or standard observation. The primary end point was detection of an 8% difference in 5-year overall survival (OS) rate; secondary end points included disease-free interval (DFI) and distant metastasis-free interval (DMFI). Tumour and blood were analysed for prognostic and predictive markers. Results: Patients (n=1343) recruited between 2007 and 2012 were predominantly stage III (73%), with median age 56?years (range 18-88?years). With 6.4-year median follow-up, 515 (38%) patients had died [254 (38%) bevacizumab; 261 (39%) observation]; 707 (53%) patients had disease recurrence [336 (50%) bevacizumab, 371 (55%) observation]. OS at 5?years was 64% for both groups [hazard ratio (HR) 0.98; 95% confidence interval (CI) 0.82-1.16, P?=?0.78). At 5?years, 51% were disease free on bevacizumab versus 45% on observation (HR 0.85; 95% CI 0.74-0.99, P?=?0.03), 58% were distant metastasis free on bevacizumab versus 54% on observation (HR 0.91; 95% CI 0.78-1.07, P?=?0.25). Forty four percent of 682 melanomas assessed had a BRAFV600 mutation. In the observation arm, BRAF mutant patients had a trend towards poorer OS compared with BRAF wild-type patients (P?=?0.06). BRAF mutation positivity trended towards better OS with bevacizumab (P?=?0.21). Conclusions: Adjuvant bevacizumab after resection of high-risk melanoma improves DFI, but not OS. BRAF mutation status may predict for poorer OS untreated and potential benefit from bevacizumab. Clinical Trial Information: ISRCTN 81261306; EudraCT Number: 2006-005505-64
The evolution of IoT Malwares, from 2008 to 2019: Survey, taxonomy, process simulator and perspectives
Autoliikenteen työntekijäin palkkatilasto, III vuosineljännes 1967
Suomen virallinen tilasto (SVT