Decision support model for effects estimation and proportionality assessment for targeting in cyber operations

Cyber operations are relatively a new phenomenon of the last two decades.During that period,they have increased in number,complexity,and agility,while their design and development have been processes well kept under secrecy.As a consequence,limited data(sets)regarding these incidents are available.Although various academic and practitioner public communities addressed some of the key points and dilemmas that surround cyber operations(such as attack,target identification and selection,and collateral damage),still methodologies and models are needed in order to plan,execute,and assess them in a responsibly and legally compliant way.Based on these facts,it is the aim of this article to propose a model that i))estimates and classifies the effects of cyber operations,and ii)assesses proportionality in order to support targeting decisions in cyber operations.In order to do that,a multi-layered fuzzy model was designed and implemented by analysing real and virtual realistic cyber operations combined with interviews and focus groups with technical-military experts.The proposed model was evaluated on two cyber operations use cases in a focus group with four technical-military experts.Both the design and the results of the evaluation are revealed in this article.     

The case for demilitarising Lesotho

ABSTRACT

The Kingdom of Lesotho spends around five per cent of its annual budget – some 700 million Maloti ($US52.6 million) in 2017 – on the Lesotho Defence Force (LDF). Lesotho’s geographical position means that the LDF has no meaningful role regarding its primary function of defending the country from external aggression and it hardly engages in its secondary functions. In addition, the LDF has a long history of interference with democratic processes and engaging in human rights abuse. The financial resources currently allocated to the LDF could do far more for security, widely defined, if they were allocated to a number of other government expenditure categories.     

On the production of victory: Empirical determinants of battlefield success in modern war

Using a data set of historical battles from 1600 to 1973, this paper analyzes the empirical determinants of tactical success in modern war. Based on a reduced form approach we consider key elements of military theory as production factors for combat success as an output of a military production function. The paper focuses on the relationship of material and non-material factors to battlefield success, and especially on the role of superior force strengths. Contrary to the emphasis on technology which can be found in the recent literature, our estimation results indicate that numerical superiority has retained its crucial role for battlefield performance throughout history. In general, human elements of warfare, like leadership, morale and surprise, have continued to be important determinants of battle outcome despite technological progress in weapons.     

Book reviews

John Lawrence Tone, The Fatal Knot: The Guerrilla War in Navarre and the Defeat of Napoleon in Spain. Chapel Hill and London; The University of North Carolina Press 1994. Pp.vii + 239, 1 map, biblio., index. $34.95 (cloth). ISBN 0–8078–2169–1.

Robert Holland (ed), Emergencies and Disorder in the European Empires after 1945. London: Frank Cass, 1994. Pp.x + 256; index. £32 (cloth); £15 (paper). ISBN 0–7146–4516–8 and 4109 X

Deborah L. Norden, Military Rebellion in Argentina: Between Coups and Consolidation. Lincoln, NE: University of Nebraska Press, 1996. Pp.242, index, $35/$17.50 (paper). ISBN 0–8032–8369–5.

William M. Minter, Apartheid's Contras: An Inquiry into the Roots of War in Angola and Mozambique. London and Atlantic Highlands, NJ: Zed Books Ltd; Johannesburg: Witwatersrand University Press, 1994. Pp. xii +308, 3 maps, biblio., index. $69.95/£39.95 (cloth); $29.95/£16.95(paper). ISBN 1–85649–266–4 and 266–4.     

A lagrangean relaxation algorithm for the constrained matrix problem

We present variants of a convergent Lagrangean relaxation algorithm for minimizing a strictly convex separable quadratic function over a transportation polytope. The algorithm alternately solves two “subproblems,” each of which has an objective function that is defined by using Lagrange multipliers derived from the other. Motivated by the natural separation of the subproblems into independent and very easily solved “subsubproblems,” the algorithm can be interpreted as the cyclic coordinate ascent method applied to the dual problem. We exhibit our computational results for different implementations of the algorithm applied to a set of large constrained matrix problems.